# data[].attributes.headline
Retrieval Practice: Powerful Teaching@ SXSW EDU

# data[].attributes.subject
Retrieval Practice: Powerful Teaching@ SXSW EDU

# data[].attributes.attachment_link.readable_text
Teaching might be an art, but learning is a science! In her opening keynote at SXSW EDU , Pooja K. Agarwal, Ph.D. (@RetrieveLearn ), cognitive scientist and author of the book Powerful Teaching: Unleash the Science of Learning , shares practical teaching strategies-based on 100 years of research-that dramatically improve student learning. Equipped with scientific knowledge and evidence-based tools, turn your teaching into POWERFUL teaching and unleash the science of learning in your classroom.

# data[].attributes.attachment_link.title
Powerful Teaching at SXSW EDU: Keynote by Dr. Pooja K. Agarwal - Retrieval Practice

# data[].attributes.attachment_link.description
At SXSW EDU, keynote speaker Dr. Pooja K. Agarwal, cognitive scientist and author of Powerful Teaching: Unleash the Science of Learning, shares evidence-based teaching strategies that dramatically improve student learning. Join us!

# data[].attributes.attachment_link.authors[].name
Celebrate women in STEM by citing women in STEM

# data[].attributes.attachment_link.title
What is retrieval practice? – Retrieval Practice

# data[].attributes.attachment_link.description
Retrieval practice is a strategy in which bringing information to mind enhances and boosts learning. Deliberately recalling information forces us to pull our knowledge “out” and examine what we know.

# data[].attributes.attachment_link.readable_text
What is Retrieval Practice?

Retrieval practice is the strategy of recalling facts, concepts, or events from memory in order to enhance learning. The act of retrieving something from your memory actually strengthens the connections holding it there, making it more likely that you'll be able to recall it in the future. A classic example of retrieval practice is using flashcards as a study tool. Sometimes called the "testing effect," retrieval practice in teaching is not limited to quizzes or exams, but can include any exercise where students attempt to retrieve what they have learned from their memory.

Evidence shows that retrieval practice is especially effective at increasing longer-term retention and generally outperforms more common strategies such as repeated studying or even more elaborate ones like concept mapping (McDermott, 2021; Karpicke & Blunt, 2011; Roediger & Karpicke, 2006). Research in classrooms demonstrates that retrieval practice is an extremely robust strategy across age groups and subject domains (McDermott, 2021). Retrieval practice also aids in higher-order thinking; it's not just for memorization. Students who use retrieval practice perform better on complex tasks and show improved metacognition (Pooja & Bain, 2019).

Incorporating activities using retrieval practice into your teaching can increase your students' learning.

Three Ways to Use Retrieval Practice in During Class

There are many ways to use retrieval practice in your instruction (Agarwal & Bain, 2019). Here are three easy ways to get started:

1) Low-stakes Quizzes

Frequent low-stakes quizzes are an easy way to incorporate retrieval practice. Quizzes can be free response, multiple choice, or another format. In-class polling works well too. Student feedback can be automatic (in the case of online quizzes), from the instructor, or from peers.

Questions should be neither too hard nor too easy. The goal is to achieve "desirable difficulty."

2) Two Things Activity

Ask students to recall and write down two things they learned today, last class or within a unit of your course. Feedback can come from peers (in pairs or groups), and/or class discussion.

3) Brain Dumps

Ask students to write down everything they know about a certain topic. The exact prompt used can be narrow (e.g., What is the definition of culture from our textbook?) or broad (e.g., Why does social mobility vary across social groups?), depending on your learning goals. Optionally, students can then compare and contrast their answers with peers in small groups or breakout rooms. A full class discussion can be used to provide instructor feedback.

Tips for Teaching with Retrieval Practice

Keeping these general tips in mind can help maximize the benefits of retrieval practice exercises for students.

Giving feedback to students is an important part of retrieval practice, especially when multiple-choice questions are used (Agarwal & Bain, 2019; Brown et al., 2014). Feedback lets the learners know about any errors they made and helps prevent accidentally encoding the wrong material into memory. It can also focus and motivate further study (i.e. it provides formative feedback).

Retrieval practice activities designed to engage every student are more effective than those that primarily engage only a few students at once. For example, a writing activity where everyone writes works better than asking the class a question and calling on a single student for an answer because the writing activity engages all students in the retrieval activity.

Most retrieval practice exercises are designed to be closed book in order to maximize "desirable difficulty." There is evidence, however, that retrieval practice works in both open- and closed-book settings (Agarwal et al., 2008). One possible disadvantage to open-book settings is that they may have the unintended effect of reducing student time spent studying if the students know that the future activity will be open book. In general, we suggest closed-book conditions for most retrieval practice exercises, unless other considerations make this impractical (e.g. online quizzes in remote or hybrid courses).

Explaining to students that the goal of the activity is learning and not assessment can increase student buy-in.

Not all activities need to be collected or graded, although sometimes collecting even ungraded tasks increases participation.

References

Agarwal, P. K., & Bain, P. M. (2019). Powerful teaching: Unleash the science of learning. Jossey-Bass.

Agarwal, P. K., Karpicke, J. D., Kang, S. H. K., Roediger, H. L., & McDermott, K. B. (2008). Examining the testing effect with open- and closed-book tests. Applied Cognitive Psychology, 22(7), 861-876. https://doi.org/10.1002/acp.1391

Brown, P. C., Henry L. Roediger III, & McDaniel, M. A. (2014). Make it stick: The science of successful learning. Belknap Press: An Imprint of Harvard University Press.

Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), 772-775. https://doi.org/10.1126/science.1199327

McDermott, K. B. (2021). Practicing retrieval facilitates learning. Annual Review of Psychology, 72(1), 609-633. https://doi.org/10.1146/annurev-psych-010419-051019

Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249-255. https://doi.org/10.1111/j.1467-9280.2006.01693.x

# data[].attributes.attachment_link.title
Using Retrieval Practice to Increase Student Learning - Center for Teaching and Learning

# data[].attributes.attachment_link.description
Retrieval practice is a powerful evidence-based teaching strategy that can easily be incorporated into you existing courses.

# data[].attributes.attachment_link.readable_text
Teachers are often concerned with getting vital information into students' heads, but it's just as important to give students frequent opportunities to externalize and manipulate recently learned materials. Simple retrieval activities like flash cards, "brain dumps," and low-stakes quizzes remain among the most effective tactics to move learners from a hazy recollection of something towards more clarity and "permanence," writes Ulrich Boser, the CEO and founder of the Learning Agency Lab, in a new post "The Five Things You Need to Know About Retrieval Practice."

Retrieval becomes even more impactful when teachers keep considerations like mental agility and the spacing of materials in mind. The practice of interleaving-mixing together two or more related concepts or skills instead of focusing on one at a time-keeps learners from relying on rote methods and forces them into a more productive "thinking on their feet" posture. Asking students to practice basic mathematical operations like addition, subtraction, multiplication, and division, for example, tends to work better when you ask students to move between the operations, rather than practice each operation separately. Research also demonstrates that retrieving stored information at regular intervals-a practice called spacing-encodes the learning far more durably.

Finally, to connect recently learned material to prior knowledge and build more durable webs of student insight, teachers should consider "mapping exercises" like hexagonal thinking and concept maps. Here are some deeper dives into seven retrieval practices that work:

Low-stakes Quizzes

"One of the easiest ways to incorporate retrieval practice into learning and teaching is via low-stakes tests or quizzes," Boser writes.

Quizzes and practice tests help students gauge how well they understand recently learned material, and identify areas of strength and areas where they need to grow. Research shows that when students become too reliant on strategies like rereading or highlighting material they tend to develop a false impression of how much they know-quizzes close that gap.

To get the most out of quizzes, the research suggests that it's better to make them low-stakes-worth little or no grade-which can reduce test anxiety, prompt more honest reflection, and improve student focus and performance. Timing also matters: It's helpful to give a practice test right after a lesson, and then continue visiting the concept through review and quizzes throughout the school year. To make low-stakes quizzes part of your repertoire, you can try clickers to do quick checks for understanding, use engaging apps like Kahoot! Or Quizziz, or opt for free online alternatives like Poll Everywhere.

Brain Dumps

Giving students just a couple of minutes in class to stop and write down everything they can think of about a specific topic or question is a great way to test their knowledge.

A " brain dump " exercise can take five minutes or less, and even the simplest version of it can help generate knowledge and create longer term retention. But it can also be modified to include collaboration with other students, says Boser: Ask them to compare their work to identify gaps, similarities, and differences, for example-and if large enough gaps and misconceptions are apparent, have them research the answers together.

Flashcards

Despite the ubiquity of flashcards, to make the most out of them requires explaining to students how they should be used-and might even require some modeling in the classroom.

For example, students should understand that for information to really stick, they should go through their card deck multiple times, and attempt to verbalize as much of the information on the back as possible before flipping them. Boser suggests that students keep cards in their deck until they are able to successfully retrieve the information by saying it out loud-in its entirety-at least three times.

Hexagonal Thinking

Hexagonal thinking is a mixed retrieval and elaboration strategy that uses hexagonal cards, paper, or even programs like PowerPoint or Google Slides to investigate how ideas and concepts are connected. For example, students who have just finished learning about World War II might generate a list of historical events and forces-treaties, battles, and more-and then write each of these items on hexagons before beginning to arrange them in cause and effect relationships.

When students work in a small group attempting to connect the hexagons, they inevitably come up with different combinations and different rationales. The proposed connections can be explained using arrows and an attached, written document and then shared with the whole class. An example of students exploring the forces involved in global warming is below:
Courtesy of Betsy Potash / Cult of Pedagogy Courtesy of Betsy Potash / Cult of Pedagogy
Concept Maps

Concept maps are visual tools that help students organize and articulate what they know about a given concept or topic. Important concepts are generally enclosed in a circle or box and then connected to other concepts by a line that might include explanatory phrases to define the relationship. Examples of linking phrases are typically things like "begins with", "includes", or "aids."

An example map about specific types of bacteria could look something like this:

To facilitate the activity, students can be presented with a guiding question, such as "How is ice formed?" and use the question as a springboard to help them map out their understanding of the physical process.

Research shows this strategy is far superior to rote memorization because it encourages students to make rich, meaningful connections within a topic. Writing for Edutopia, educator Dr. Kripa Sundar said the strategy can be easily adapted for early learners by replacing words in the concept maps with pictures.

Jigsaw Method

You can use the Jigsaw Method to help students retrieve information, process it again, and then practice teaching it to their peers. After splitting students up into small groups of four to six, each should be assigned to specialize in one "chunk" of content related to a topic or lesson, as seen in Cult of Pedagogy's excellent video tutorial.

For example, a history teacher focusing on an overview about the various forms of government could divide the content into chunks such as democracy, dictatorship, monarchy, republic, etc. After each chunk is assigned to an individual student in the group, they go off to read and study their chunk independently. Later the group will reconvene, and each student will teach from their special knowledge base. Consider ending the activity by directing tough questions to each group, or letting the groups quiz each other.

Think, Pair, Share

Similar to brain dumps, "think, pair, share" is a low-stakes retrieval activity that's relatively easy to set up. Ask students to dwell on a particular topic or question you're already covered and get them to come up with as many facts or important ideas as they can. Once they have a list-you might want to specify how many items are ideal-the students then pair up with a partner to talk out what they know, compare notes, and help each other identify gaps in their understanding.

According to Rosie Reid, a high school English teacher in California, tweaking this activity to " write, pair, share " can help "improve the quality of the conversation" students have with each other. It can also help teachers get real time feedback on students' understanding of the material as they walk around the room during the writing portion and do a check to see how many students are having trouble coming up with points.

# data[].attributes.attachment_link.description
Effective retrieval practice strategies help students identify what they know about a given concept and retain that information for the long-term.

# data[].attributes.attachment_link.readable_text
The ability to effect change is essential for individuals, families and their enterprises to thrive. We all know that change is difficult - but why is it so difficult? To answer that question, we need to understand more about the science of neuroplasticity and how the human brain works.

We are standing at an inflection point as families of wealth and their advisors strive to harness scientific advances that measurably foster agility and performance while promoting and protecting health and well-being, both today and in the future. The ability to effect change - and neuroplasticity, more specifically - is essential for individuals, families and their enterprises to thrive. Despite the profusion of available advice about improving and enhancing our lives and businesses, meaningful change remains extraordinarily challenging. There is still an insatiable demand for yet more information and assistance.

"The world of business is evolving at an exponential rate, new multi-billion dollar industries emerging rapidly and old, established industries becoming obsolete. In this fast-changing environment, operating with agility and a purpose-driven, innovative mindset is key to the sustained success of modern enterprises."

- Francois Botha (Founder, &Simple)

Podcasts are a relatively recent and popular iteration of information sharing. from spring 2021 indicates there are over two million different podcasts with more than 48 million outstanding podcast episodes. That's a lot of information - and yet we still want more.

The continued yearning and desire for personal and professional assistance suggests that despite the proliferation of advice and information, our needs are fundamentally not being met. Contemporary neuroscience not only explains why change is so difficult but now offers us a remarkable array of specific, actionable tools to effect meaningful and enduring change.

The science of change

Based on an understanding of neuroscience and human behaviour, we know that information and advice alone are not effective at producing satisfying behavioural or emotional change. In fact, our neurobiological makeup does not support the straightforward utilization of information as the basis for change.

We are all experiencing a kind of paradox - we have "information overload" with an "application breakdown". There is a disconnect between the advice tendered, its successful application and its conversion into meaningful change.

Change manifests itself in many forms: alteration of our emotional, cognitive and/or physical states to improve mood, resilience and our relationships; enhancing our professional lives, performance, health and spiritual well-being. We yearn to develop meaning and purpose, connection to nature, stewardship of our environment, and to create an enduring legacy. Indeed, these are all powerful epigenetic interventions that support the favourable expression of our genes.

We all know that change is difficult. But why is it so difficult? To answer that question, we need to understand more about how the human brain works.

Achieving neuroplasticity in order to change

Neuroplasticity is the capacity of our nervous system to learn new things - to change. Achieving neuroplasticity is the first step to optimizing our brain to effect change.

Yet, neuroplasticity alone is never the goal. The goal is to access neuroplasticity and then direct it towards particular changes we want to achieve. With practice and reinforcement, the changes we learn become increasingly reflexive. As an example, at a certain point in our development, we no longer had to be conscious of every step we took, we simply "knew" how to walk. The same could be said for learning a new language or navigating a new computer program.

Neuroplasticity enables behaviour that is initially tentative and deliberate to become automatic and reflexive.

Learning as a child vs learning as an adult

The human brain develops over time. Young brains are neuroplasticity machines. In the first few years of life, more than one million new neural connections form every second. After this period of rapid proliferation, connections are reduced through a process called "pruning" which allows brain circuits to become more efficient. This dynamic process never stops and our brain becomes a roadmap informed by the experiences of our life.

By the adult brain has fully . In order for adults to effect change, we have to engage in a different set of processes to successfully effect change and, more specifically, to endure. Adults cannot change the mind simply by using the mind. Words alone have the lowest currency to alter the brain. We can only change the mind through experience, but we can prime the brain for change with specific interventions that are fully under our control.

To effect meaningful change as an adult we must undergo a series of very deliberate steps to alter our internal state in ways that then allow us to change our brains.

Deep learning

For adults, change requires deep learning . Deep learning has two essential components: deep attention and deep rest.

Deep Learning =

Deep Attention (Alertness + Focus) + Deep Rest (Sleep + Recovery)

Alertness: Alertness is the state of feeling awake and alive. It involves the release of a neurotransmitter called adrenaline (sometimes referred to as epinephrine). You may recognize this as the primary neurotransmitter involved in the stress response. Alertness is also a state of vigilance, being aware of potential danger. The release of this neurotransmitter will often trigger a feeling of distress, agitation or discomfort. The levels of adrenaline are lower for deep learning than they are in dangerous contexts, but the feelings, albeit less intense, are much the same.

Focus: Focus involves suppressing surrounding noise to hone in on a specific task. When done right, focus is like casting a spotlight, eliminating unnecessary external stimuli. The neurotransmitter chemical responsible for focus is acetylcholine. This "focus" molecule highlights the areas of your brain that are involved in learning, marking those areas for change.

Distress and dopamine: The simultaneous release of adrenaline and acetylcholine produces a state of feeling that tends to be unpleasant, agitating and uncomfortable. This distressed state can be offset by dopamine, another neurotransmitter that is often associated with pleasure.

Small amounts of dopamine can be self-administered by celebrating small wins and reframing distress as a positive step necessary for change. Dopamine cannot be consumed or injected. It is up to the individual to generate the release of dopamine into the brain.

Deep rest: Change, or neuroplasticity, doesn't occur during the "deep attention" phase of work outlined above. Change occurs during periods of "deep rest", primarily sleep and recovery.

# data[].attributes.attachment_link.title
Neuroplasticity and Change: Tools for Peak Performance - Aspen Brain Institute

# data[].attributes.attachment_link.description
The ability to effect change is essential for individuals, families and their enterprises to thrive. We all know that change is difficult - but why is it so difficult? To answer that question, we need to understand more about the science of neuroplasticity and how the human brain works.

# data[].attributes.attachment_link.readable_text
The cognitive load of an eLearning module-that is, the amount of brainpower it demands of learners so that they can process and understand the information-varies. Some of the factors are under the control of the instructional designer; some are not. Cognitive load is an intersection of:

Intrinsic cognitive load-the inherent complexity of a learning task-is not directly controlled by the designer. However, some approaches to eLearning design can help reduce cognitive overload, even when teaching complex processes and concepts.

Germane cognitive load refers to activities and presentation of material that enhance learning. Instructional designers have considerable control here. One factor they do not control, but can make allowances for, is the level of expertise of learners using the eLearning.

Extraneous cognitive load, also a function of the presentation of the material and activities required, impairs learning. Extraneous cognitive load is created when learners are asked to do tasks that are not connected to the learning goals. This is entirely a function of design.

Designers can create dynamic and engaging eLearning using these seven popular approaches, while also reducing cognitive load:

1. Microlearning or chunking-In the lingo of cognitive-load theorists, material that has "high-element interactivity" is high in intrinsic cognitive load: It's complex, multistep, and the pieces must all be mastered before the material as a whole becomes comprehensible. However, each step or element can become a separate "schema" or element of learning. Once a learner has mastered a series of schemas-chunks-a different eLearning activity can pull the pieces together into a coherent process or unit of information.

2. Multimodal presentation-Humans process information differently if they are seeing it versus hearing it. Presenting some material visually, via text, diagrams, color schemes, or icons, and presenting additional material verbally, using narration, reduces cognitive load and allows many learners to process the information better.

3. Content curation-Rather than include everything, even the kitchen sink, in an eLearning course, offer curated content as supplementary material. Novice learners can focus on the essential information, presented clearly in the eLearning; expert learners can explore more deeply by reading linked content, watching optional videos, and engaging in advanced activities.

4. Just-in-time learning or job aids-Provide some instruction, particularly instructions for short procedures or fact sheets on products, in handy, easily accessible (mobile-friendly) formats: short videos, checklists, or flash cards. Learners can easily find and use these at the moment they need the information. By reducing the amount learners are expected to memorize or learn at once, designers can reduce the potential for cognitive overload.

5. Ease off on the bells and whistles-Game mechanics or interactivity are appropriate for some eLearning, but not all. If the subject matter has a high intrinsic cognitive load, the presentation should probably tend toward the simple; save the special effects for livening up topics that might be important but that are not inherently engaging.

6. Keep activities relevant-Ask learners to apply learning in activities that make sense and reflect how they will actually use the information on the job. A simulation where learners practice actual skills and are required to generate their own response to a prompt is more helpful (and realistic) than a multiple-choice quiz where they select from a list of canned-but improbable-responses.

7. Simplify, simplify, simplify-Use plain English and make sure to include simple, complete, andclear instructions. Keep the design clean and logical, with navigation elements like buttons obvious. Use large, clear fonts. In short, don't make learners work so hard to get into and understand the workings of the eLearning that they have no brain power left to tackle the actual material.

# data[].attributes.attachment_link.title
Design eLearning to Reduce Cognitive (Over)Load

# data[].attributes.attachment_link.description
The cognitive load of an eLearning module-that is, the amount of brainpower it demands of learners so that they can process and understand the information-varies. Some of the factors are under the control of the instructional designer; some are not.

# data[].attributes.body
https://www.insidehighered.com/digital-learning/views/2017/09/06/how-provide-meaningful-feedback-online-course

# data[].attributes.body
https://www.shiftelearning.com/blog/design-elearning-to-protect-the-learner-from-overload

# data[].attributes.attachment_link.readable_text
Low-stakes assignments are forms of evaluation that do not heavily impact students' final grades or other educational outcomes. The purpose of low-stakes assignments is to provide students with an indication of their performance while taking a course and give students an opportunity to improve their performance prior to receiving a final grade, either on an assignment or in a course.

As Vincent Tinto writes in Completing College: Rethinking Institutional Action (2012), "To be effective, assessments must be frequent, early, and formative." At colleges and universities recognized by the National Survey on Student Engagement for their success in promoting student's active engagement in their learning: "Feedback from faculty to students is timely and frequent, as documented both by NSSE data and by interviews with students and faculty members" (Kuh, et al. 2010).

Low-stakes assignments tend to work best when they generate formative feedback regarding where students are in the course, what they are doing well, and where they may need development to ultimately succeed in the class. At DePaul, there is a general expectation that students will be given feedback early in the quarter or term, and low-stakes assignments are a powerful method of doing so.

For students in their first year, whether as freshmen or transfers, such feedback is especially important in order to help them understand the expectations at DePaul. Early feedback also enables faculty to use DePaul's BlueStar system to identify students who may need additional assistance and share that information with the students and their academic advisors.

Benefits of Low-Stakes Assignments

Low-stakes assignments

Give students a realistic idea of their performance early in the term, enabling them to seek appropriate resources as needed

Open up lines of communication between students and their instructors, and may increase students' willingness to ask for help

Provide feedback for instructors on how well students are absorbing information and progressing in their skill development

Allow instructors to direct students to resources if they need further assistance or support

Give students an opportunity to be active participants in the evaluation of their own learning

Increase the likelihood that students will attend class and be active and engaged

Low Stakes-Assignments in Online and Flex Modality Courses

While all classes can benefit from frequent low-stakes assignments, it's especially important in online and Flex modalities. In a face-to-face classroom, instructors may assess student learning in informal ways using nonverbal cues-a puzzled look or an affirming nod, for example. In a online and Flex courses, instructors may have more difficulty picking up these cues from students, especially if they don't always have their cameras on or you're not meeting synchronously. In Flex classes, it can also be more challenging to pick up on nonverbal cues among in-person students if also trying to monitor engagement and participation among remote students at the same time. ​​

D2L Tools for Low-Stakes Assignments

​D2L tools will help you to implement low-stakes assignments in all types of courses and course modalities.

Quizzes are often used for multiple-choice or other objective question types because they can be graded automatically, allowing students to get feedback immediately. For low-stakes assignments, you may want to allow students to review the questions and their answers after they take the quiz. You can set up Submission Views to allow for this. Instructors can also view quiz statistics to see if the class is struggling with a particular concept and review that topic with them.

Discussions

Discussions allow students to share short pieces of writing or other media with you and their classmates. They work well for sharing rough drafts or other early-stage components of larger projects for peer review or for certain journaling assignments.

Submissions

Submission folders allow students to submit work privately to you. You may be used to using Submissions for major assignments like research papers. For shorter, less formal pieces of writing, you can change the Submission Type to "Text" to allow students to type their response directly into D2L rather than uploading a file from their computer.

Examples of Low-Stakes Assignments

Though given less weight, low-stakes assignments may be similar in type and kind to high-stakes assignments: they tend to reflect the kind of work students are going to be expected to do for a final exam, paper, or other summative project.

Components of a Larger Project

When assigning students a writing or research project, break down the elements of the project and use one or more as a low-stakes assignment. Require students to submit their works-in-progress so that they can receive early written feedback and a small grade, which could consist simply of a check or check-minus. Any one (or more) of the following elements could be collected and used as a low-stakes assignment:

Prospectus or proposal

Abstract

Thesis statement

Outline

Annotated bibliography

Specific sections of the final project (e.g., introduction, methods, lit. review)

Early-stage drafts of a paper

Early Drafts and Peer Review

Midway through a writing project, have students bring a full or partial draft of their paper to class and then exchange feedback with a peer. Students will receive valuable feedback that they can use to revise their work.

Try providing students with a rubric to help them give their peers targeted, assignment-specific feedback. Also, consider inviting Writing Center tutors to your class to model how peer review can be conducted effectively.

Mid-Project/Quarter Conferences

Around midterm or during the planning stages of a major course project, ask students to meet with you for conferences. If the class is too large for you to meet with each student individually, assign students to meet with you in groups, or one-on-one with their TA. The conference time might be dedicated to discussing the students' progress towards course goals or providing feedback on a particular project.

To get the most out of your conference time, ask students to complete and bring with them a self-assessment form or project proposal. Alternatively, ask students to write down one question they have about the course, content covered in class, or an assignment they are currently working on. Having a document to reference will keep the conversation on track and help put both you and your students at ease.

Group Work Planning and Reflection

When students are working in groups, require them to submit a statement outlining each group members' responsibilities and/or a timeline that measures their progress. Periodically throughout the group project, ask students to submit short reflections detailing their progress and any areas where they need support.

Weekly Quizzes

For a course where exams are the primary means of summative assessment, give students a quiz at the end of each week with questions based on content covered up to that point. Although the quiz might not count for credit (or might only count for a very small portion of the final grade), it will give students an idea of what they already learned and which concepts they need to spend more time with. Quizzes can be paper-based, conducted during class using Polling or posted online in D2L Quizzes.

Class Problem Solving

In a course where students learn new computational or mathematical concepts, have a problem posted on the board or screen at the start of each class, or in a collaborative document. Students can work individually, in pairs, or in small groups to find the solution. Spend part of class going over the problem as a big group, or review the problem in a short video.

Course Concept Journals

Consider having students keep a regular journal where they can engage with and apply course concepts. For example, in an Introduction to Political Science course, ask students to read the politics section of the New York Times and keep a weekly concept-application journal. For each entry, students should select one article that they read, summarize it, and show how the article demonstrates a theoretical concept discussed that week in class. Review students' journals every other week or so and give each entry brief feedback.

Reading Journals

In a course where students are required to do weekly readings, assign a reading journal. Entries might require students to summarize and respond to the source, or to answer a set of questions provided by the instructor. Students can submit their journal entries through D2L, by handing in hard copies every other week, or by posting them on a course blog.

Short Writing Assignments

Give students a prompt that corresponds to a class reading assignment, concept, or activity and have them turn in a short written response. Return the students' responses with your brief feedback, indicating whether the students are on track or not (a simple "check plus" or "check minus" could be used). In large classes where you might not have time to give individualized written feedback to each student, share and discuss one or two anonymous students responses at the next class meeting or in a D2L News item or weekly introduction.

Discussion Questions

Post open-ended questions designed to promote engagement with the current course content or an upcoming project or assignment. Invite students to ask questions and identify areas of confusion, and answer the questions posted by their peers. See Facilitating Discussions for additional suggestions.

Support for Low-Stakes Assignments at DePaul

University Center for Writing-based Learning (UCWbL)
Discuss how you can incorporate writing in a low-stakes assignment by contacting Matthew Pearson, Director of the UCWbL. You can also invite peer tutors to your classroom to demonstrate effective peer review before having your own students give feedback to one another.

University Libraries
If you're interested in using an element of a research project as a means of giving early feedback to students, connect with a university librarian. University librarians can offer feedback and resources for designing research projects for students.

Center for Teaching and Learning (CTL)
Have a question about integrating discussion forums in your classes? Not sure which platform might be best for setting up a course blog? Contact the CTL for help identifying and implementing a technology tool to help meet your goals.

Further Reading

Angelo, T., & Cross, K.P. (1993). Classroom assessment techniques. San Francisco: Jossey-Bass, Inc.

Bean, J. C. (1996). Engaging ideas: the professors guide to integrating writing,critical thinking and active learning in the classroom. San Francisco: Jossey-Bass Publishers.

Kuh, G. D., Kinzie, J., Schuh, J.S., and Whitt, E.J. (2010). Student success in college: Creating conditions that matter. San Francisco, CA: Jossey-Bass.

Lang, J. M. (2013). Cheating Lessons: Learning from Academic Dishonesty. Cambridge, MA: Harvard University Press.

Nilson, L. B. (2010). Teaching at its best: A research-based resource for college instructors. San Francisco: Jossey-Bass.

Tinto, Vincent. (2012). Completing college: Rethinking institutional action. Chicago, IL: University of Chicago Press.

Warnock, Scott. (2013). Frequent, low-stakes grading: Assessment for communication, confidence. Faculty Focus. Madison, WI: Magna Publications.

​

# data[].attributes.attachment_link.description
Low-stakes assignments are forms of evaluation that do not heavily impact students' final grades or other educational outcomes. The purpose of low-stakes assignments is to provide students with an indication of their performance while taking a course and give students an opportunity to improve their performance prior to receiving a final grade, either on an assignment or in a course.

# data[].attributes.headline
Assessment: Diagnostic, Formative, and Summative (Harvard U.)

# data[].attributes.subject
Assessment: Diagnostic, Formative, and Summative (Harvard U.)

# data[].attributes.attachment_link.readable_text
As we discussed in our page on learner-centered design, at the core of this approach is the notion that the only way to measure (and therefore adjust) what students are learning is by creating frequent opportunities for you and your students to generate evidence of their mastery. The evidence produced in this way, through in-class assessment techniques as well as low- and high-stakes assignments, provides multiple opportunities for feedback. Student work is simultaneously a form of feedback for instructors, insofar as it allows them to gauge the efficacy of their teaching, and an opportunity for students to receive feedback from their instructors, insofar as their instructors make graded work an occasion to update students on their progress.

As an instructor, you can elicit essentially three kinds of evidence for you and your students, each of which might be useful at a different juncture in the semester. Depending on where you are in the semester, you might want to surface:

1. What your students already think/know/know how to do. All students enter the classroom with prior knowledge, and both you and your students need to know what kinds of prior conceptions (and perhaps misconceptions) they have at the outset of the course (or of a particular unit within it). This is called diagnostic evidence.

2. How your students' mastery is developing; and how they can continue to develop, course-correct, and improve "in-flight." Students need opportunities to practice; these should be frequent and low-stakes-perhaps even ungraded. This is called formative evidence.

3. How close your students have come to achieving mastery of one or more of the skills and concepts active in your course. Assignments testing mastery should come at key inflection points and/or endpoints within the overall scheme of the course, whether that be the end of a unit, at the midterm, or at the conclusion of the semester. This is called summative evidence.

So if you're sold on this idea about putting evidence before "content," there's one more thing you have to do. You can't generate evidence about students' learning unless you know pretty clearly what you want them to learn. That would be like trying count something without knowing what to count. That means you need some goals.

Mayer, Norma, Lovette, DiPietro, Bridge, and Ambrose, How Learning Works; Healy, Clawson, and McNamara, 1993; Martin, Klein, & Sullivan, 2007

# data[].attributes.attachment_link.description
As we discussed in our page on learner-centered design, at the core of this approach is the notion that the only way to measure (and therefore adjust) what students are learning is by creating frequent opportunities for you and your students to generate evidence of their mastery.

# data[].attributes.headline
Assessment: Formative and Summative (Yale U.)

# data[].attributes.subject
Assessment: Formative and Summative (Yale U.)

# data[].attributes.attachment_link.readable_text
Examples of Formative and Summative Assessments

Both forms of assessment can vary across several dimensions (Trumbull and Lash, 2013):

Informal / formal

Immediate / delayed feedback

Embedded in lesson plan / stand-alone

Spontaneous / planned

Individual / group

Verbal / nonverbal

Oral / written

Graded / ungraded

Open-ended response / closed/constrained response

Teacher initiated/controlled / student initiated/controlled

Teacher and student(s) / peers

Process-oriented / product-oriented

Brief / extended

Scaffolded (teacher supported) / independently performed

Recommendations

Formative Assessment Ideally, formative assessment strategies improve teaching and learning simultaneously. Instructors can help students grow as learners by actively encouraging them to self-assess their own skills and knowledge retention, and by giving clear instructions and feedback. Seven principles (adapted from Nicol and Macfarlane-Dick, 2007 with additions) can guide instructor strategies:

Keep clear criteria for what defines good performance - Instructors can explain criteria for A-F graded papers, and encourage student discussion and reflection about these criteria (this can be accomplished though office hours, rubrics, post-grade peer review, or exam / assignment wrappers). Instructors may also hold class-wide conversations on performance criteria at strategic moments throughout a term.

Encourage students' self-reflection - Instructors can ask students to utilize course criteria to evaluate their own or a peer's work, and to share what kinds of feedback they find most valuable. In addition, instructors can ask students to describe the qualities of their best work, either through writing or group discussion.

Give students detailed, actionable feedback - Instructors can consistently provide specific feedback tied to predefined criteria, with opportunities to revise or apply feedback before final submission. Feedback may be corrective and forward-looking, rather than just evaluative. Examples include comments on multiple paper drafts, criterion discussions during 1-on-1 conferences, and regular online quizzes.

Encourage teacher and peer dialogue around learning - Instructors can invite students to discuss the formative learning process together. This practice primarily revolves around mid-semester feedback and small group feedback sessions, where students reflect on the course and instructors respond to student concerns. Students can also identify examples of feedback comments they found useful and explain how they helped. A particularly useful strategy, instructors can invite students to discuss learning goals and assignment criteria, and weave student hopes into the syllabus.

Promote positive motivational beliefs and self-esteem - Students will be more motivated and engaged when they are assured that an instructor cares for their development. Instructors can allow for rewrites/resubmissions to signal that an assignment is designed to promote development of learning. These rewrites might utilize low-stakes assessments, or even automated online testing that is anonymous, and (if appropriate) allows for unlimited resubmissions.

Provide opportunities to close the gap between current and desired performance - Related to the above, instructors can improve student motivation and engagement by making visible any opportunities to close gaps between current and desired performance. Examples include opportunities for resubmission, specific action points for writing or task-based assignments, and sharing study or process strategies that an instructor would use in order to succeed.

Collect information which can be used to help shape teaching - Instructors can feel free to collect useful information from students in order to provide targeted feedback and instruction. Students can identify where they are having difficulties, either on an assignment or test, or in written submissions. This approach also promotes metacognition, as students are asked to think about their own learning. Poorvu Center staff can also perform a classroom observation or conduct a small group feedback session that can provide instructors with potential student struggles.

Instructors can find a variety of other formative assessment techniques through Angelo and Cross (1993), Classroom Assessment Techniques (list of techniques available here).

Summative Assessment Because summative assessments are usually higher-stakes than formative assessments, it is especially important to ensure that the assessment aligns with the goals and expected outcomes of the instruction.

Use a Rubric or Table of Specifications - Instructors can use a rubric to lay out expected performance criteria for a range of grades. Rubrics will describe what an ideal assignment looks like, and "summarize" expected performance at the beginning of term, providing students with a trajectory and sense of completion.

Design Clear, Effective Questions - If designing essay questions, instructors can ensure that questions meet criteria while allowing students freedom to express their knowledge creatively and in ways that honor how they digested, constructed, or mastered meaning. Instructors can read about ways to design effective multiple choice questions.

Assess Comprehensiveness - Effective summative assessments provide an opportunity for students to consider the totality of a course's content, making broad connections, demonstrating synthesized skills, and exploring deeper concepts that drive or found a course's ideas and content.

Make Parameters Clear - When approaching a final assessment, instructors can ensure that parameters are well defined (length of assessment, depth of response, time and date, grading standards); knowledge assessed relates clearly to content covered in course; and students with disabilities are provided required space and support.

Consider Blind Grading - Instructors may wish to know whose work they grade, in order to provide feedback that speaks to a student's term-long trajectory. If instructors wish to provide truly unbiased summative assessment, they can also consider a variety of blind grading techniques.

Considerations for Online Assessments

Effectively implementing assessments in an online teaching environment can be particularly challenging. The Poorvu Center shares these recommendations.

References

Nicol, D.J. and Macfarlane-Dick, D. (2006) Formative assessment and self‐regulated learning: a model and seven principles of good feedback practice. Studies in Higher Education 31(2): 2-19.

Theall, M. and Franklin J.L. (2010). Assessing Teaching Practices and Effectiveness for Formative Purposes. In: A Guide to Faculty Development. KJ Gillespie and DL Robertson (Eds). Jossey Bass: San Francisco, CA.

Trumbull, E., & Lash, A. (2013). Understanding formative assessment: Insights from learning theory and measurement theory. San Francisco: WestEd.

# data[].attributes.attachment_link.description
Examples of Formative and Summative Assessments Examples of Formative and Summative Assessments Formative Summative In-class discussions Instructor-created exams Clicker questions Standardized tests Low-stakes group work Final projects

# data[].attributes.attachment_link.readable_text
Why do we build instruction? Seems like a "duh" kind of question for those of us who build instructional materials for a living, but it actually deserves more thought than you might expect.
Editor's Note: Parts of this article may not format well on smartphones and smaller mobile devices. We recommend viewing on larger screens.
There are many reasons for building instruction, but one of the more critical reasons is to impact what people can do in the real world. Students are not taught math so they can solve problems at the end of each chapter. They are taught math so they can handle purchases, understand mortgages and other financing, and complete mathematical tasks required by their jobs.

Management training is not provided so that managers can perform well during instruction. The desired outcome is good performance on the job. As developers of instruction, we often expect learning to be applied in numerous situations, but our expectations and reality are quite different.

Consider the following scenarios:

Teachers teach how to do percentages. Their students can solve percentages problems in class but they can't determine the final price of a sale item in the store, given the discount amount.

A training group provides instruction on legally defensible hiring practices but afterwards, managers' actual interviewing practices contain critical legal inadequacies. In addition, many of these managers don't apply these concepts to the wording of job descriptions.

What we have in these (and similar) situations is a problem with transfer of learning. Transfer of learning means that something learned in one situation can be applied in another. In these two examples, transfer has not occurred to the degree needed.

What is transfer?

Unfortunately, situations like these aren't unusual. Research shows that transfer doesn't happen just because instruction is provided. Rather, the preponderance of evidence, from Thorndike's studies in the early 20 th century through more recent research, shows that the desired transfer from instruction to application happens relatively infrequently. People often do not understand how what they know can be applied in various situations because they often don't make the connections we expect them to make. This is undeniably a problem since transfer is the primary goal of instruction. Although studies have shown that certain instructional strategies can dramatically improve transfer, another problem is that many e-Learning applications aren't designed to take advantage of them.

Why don't we regularly design for transfer, if transfer is so critical to our success and the success of our stakeholders? Here are a few reasons. Many folks who design instruction think transfer takes care of itself (it certainly doesn't). Many don't know how to create online instruction that makes transfer more likely. Many realize transfer is important, but design for relatively low levels of transfer (what I will be calling near(er) transfer) when higher levels (what I will be calling far(ther) transfer) are needed.

Back to my initial question about why we design instruction - if we don't design for transfer, why design instruction at all? Let's look at some of the basics that help us understand how transfer works and then consider how this information can be used to build e-Learning that creates more transferable skills and knowledge.

"Learning" vs. transfer

The student who can solve the percentage problems at the end of the percentages chapter in his math text has "learned" how to do percentages. A manager who can select the unlawful phrases in a simulated interview has "learned" which phrases are unlawful. What does it mean, then, if they cannot solve percentage problems in a store or build a lawfully worded real-life job interview? It means that there is a critical difference between learning during instruction and application of that learning in the real world. Consider this: It takes far more skill to actually do the interview than just discriminate between good and bad wording. The bottom line is that real life application is almost always much more complex than the instruction. Unless we take into account the inevitable complexities of real-world application, the instruction we design is likely to be far too simplistic for transfer to occur to the degree needed. And that means the instruction we build is less effective (often by far) than is needed to justify the time and expense.

Near(er) vs. far(ther) transfer

You may have noticed that I have referred a few times to the degree of transfer needed. Degree of transfer refers to whether application in the real world is a lot like the instructional context or quite different from it. For example, Mary takes a class on how to handle an angry customer. She learns a three-step process in the course that includes very careful listening, repeating back to the customer what she has heard, and then suggesting solutions. In the course, learners practice this process over and over in a variety of cases in order to get practice with the wide range of situations where this may be useful. If she goes back to the job and is able to use the process exactly as she was taught, the degree of transfer isn't terribly far. Being able to adapt this process when the exact sequence doesn't make sense means the degree of transfer is far(ther), because she is using the skill in a new context.

This concept is called near and far transfer. That's a bit of a misnomer because it's a continuum from near(er) to far(ther) transfer, with potentially higher degrees of transfer along the way. Near(er) transfer is transfer between very similar contexts. For example, a technician is trained to replace the hard drive on a computer with a similar or the same type of hard drive. Or a clerk receives training to use and troubleshoot the mail sorting equipment and then performs these exact same skills on the job. Near(er) transfer is generally what is needed for tasks that are routine and consistent.

Far(ther) transfer refers to learning applied in real life situations that are somewhat to greatly different than the learning contexts. This is most needed for tasks that are executed differently depending on the situation. The hallmark of far(ther) transfer is the need to adapt actions based on judgment. Knowing how to use the knowledge of percentages to determine the discount on a sale is farther transfer than being able to do percentage problems in a math text. Applying project management lessons to home construction projects is farther transfer than applying it on the job, where the learning occurred.

Instructional strategies for transfer

So, how can we help transfer occur to a greater degree? Research shows that the strategies summarized in Table 1 can dramatically improve transfer from instruction to the real world.

David Perkins and Gavriel Salomon synthesized research findings about transfer and concluded that there are two mechanisms for transfer that they called "low road" and "high road." Low road transfer relates to near transfer situations, where instruction and learning are similar. In that case, teaching learners to perform relatively automatically with extensive practice makes sense. On the other hand, what is needed in high road transfer, where performance requires a fair degree of judgment and skills are performed differently in different circumstances, is varied practice, self-monitoring, and generalizing about how the learning will be applied in the real world.

Transfer and learning objectives

Because e-Learning designers are accustomed to thinking about outcomes of instruction in terms of learning objectives, it may be helpful to see how these concepts tie into learning objectives. Learning objectives can be divided into two types: procedural and declarative. Procedural objectives involve a sequence of steps. An example of a procedural objective is: The learner will be able to replace the hard drive in the XYZ computer chassis in less than 15 minutes. Declarative objectives, on the other hand, involve conceptual knowledge and fundamental principles - for example: The learner will determine what course of action to take if the circumstances violate company ethics policies.

Procedural objectives generally involve near(er) transfer. The role of instructional activities and practice is to help learners gain skill in utilizing a fairly consistent set of rules. Similar contexts, seeing connections, extensive practice, and self monitoring make sense as instructional strategies.

Declarative objectives generally involve far(ther) transfer. The role of instructional activities and practice is to help learners gain skill with determining the best course of action. What is desired, for declarative objectives, is flexible adaptation of skills to a variety of contexts and situations. Similar contexts, seeing connections. extensive and varied practice, extracting underlying principles, and self monitoring make sense as instructional strategies.

In general, research shows that behavioral training methods tend to better promote procedural objectives and near(er) transfer, while more cognitive methods tend to better promote declarative objectives and far(ther) transfer. (Note: Bill Brandon's June 1, 2004 article in " Learning Solutions Magazine, How Do People Learn? Some New Ideas for e-Learning Designers, " provides a good overview of these learning theories.)

Applying transfer theory

So how does all this apply to our initial scenarios? Let's first consider learning how to calculate percentages. Being able to solve a simple percentage problem, say 20% of 136, might be considered near(er) transfer, as there is a routine and consistent series of steps to follow (convert the % to a decimal, then multiply the decimal by...). But what if we go into a store and see a jacket we'd like to buy, and the sign says all jackets are on sale for 25% off? Not only that, today there's an extra 10% off! The rote steps don't work as well here. The price tag says $245. Do we start by multiplying .25 or .75 times $245? And where does the extra 10% come off? Add to the 25% (.35) or multiply the first result by .90? This is a far(ther) transfer situation. If you're a math expert who has been called in to assist with development of an e-Learning application to teach percentages, you realize people will, no doubt, regularly come upon this challenge in real life. You'll also realize that learners will need to do extensive practice with a variety of near and far transfer contexts. You might use a pie analogy at first to help people see that 1/4 of a pie (make mine pecan!) is 25%. And it would be helpful to demonstrate a variety of examples where percentages are used (sales, mortgages, etc.) and help learners use strategies for solving all sorts of percentage problems.

What about the legally defensible hiring practices scenario? This is a far(ther) transfer situation because a great deal of judgment is needed and we can't put a rote process into place that will take into account every circumstance. We can't know everything that a potential hire might say or ask. What we do will change depending on the specific circumstances, even though the underlying principles remain the same. In this case, realistic practice with a wide range of situations will always be needed. Learners will need to establish and then utilize underlying principles (such as which types of questions are a definite no-no).

Activities for transfer

If we want to improve transfer, we need instructional activities that involve learners in the types of activities that allow them to practice using the content as it is used in real-life situations. And they need to deal with increasingly complex uses of the content as a whole (not just the parts), and get meaningful feedback and necessary support along the way. That's a big charge, but that's what it takes.

Although many folks are charged with developing self-paced online learning because it's supposed to be less expensive, how cheap is it really if it doesn't transfer? Research shows that self paced and collaborative activities have different best uses, as Table 2 shows. (They can be used together for maximum effectiveness.)

Self-paced activities work well for: Collaborative activities work well for:

Procedural objectives

Simpler, right or wrong answers

Extensive practice for routine skills with feedback and remediation

The ability to try without fear

Declarative objectives

Multiple views and diverse perspectives

Complex decision making

Complex feedback and remediation,

Realistic practice with people

What I hope you see in Table 2 is that while self-paced activities can be very useful, collaborative activities are often needed as well for instruction where far(ther) transfer is desirable. That doesn't mean that these collaborative activities have to happen online (many certainly can), but they absolutely need to happen in order for the types of transfer desired to occur.

Example: The time-off policy

Just to make sure this makes sense, let's reflect on the transfer needs of a situation that I regularly use when I help e-Learning designers learn to support transfer in their online instruction. I like this example because it comes from a real training project. It provides great food for thought, and since the objectives are both procedural and declarative. Here's the situation:

Company executives want your department to create an e-Learning application for managers who need to appropriately apply Human Resource policies related to time off (unpaid leave, earned vacation time, paid sick leave). The company has experienced myriad problems over the last few years because some managers have applied these policies in problematic ways. Executives fear that lawsuits, and productivity and morale problems, will result if managers don't apply these polices more appropriately.

What kind of transfer is needed? There may be some rote application (looking up the policy, documenting actions and conversations) but the skill as a whole is pretty complex, requiring myriad decision points and practice application in a wide variety of situations. It is critical that learners extract the fundamental principles and then apply these principles across multiple contexts. Instructional activities will likely revolve around cases, simulations, and problems to solve. Collaborative activities would be appropriate for providing complex feedback, and there will likely be a need to extend the training beyond a single "event," because mastery of complex skills occurs over time and this is indeed a complex skill.

To give you a feel for the end result of this exercise in designing for transfer, Table 3 illustrates the second of four terminal objectives (and corresponding enabling objectives) that resulted from this design process, the activities selected, information and support tools used during instruction (and later), and graphics and multimedia to support the activities.

Terminal objective and enabling objectives
Activities
Information and support Graphics and multimedia

Establish policy relevance

Online policy manual with search

FAQs for common problem areas

Ask the expert discussion forum (feeds FAQs)

HR phone list

Methods to gain help with all activities

Process model with search

Case graphics/audio

Determine if the policy applies

Practice determining if policy(ies) applies/apply in a wide range of common situations

Determine if exceptions apply in this situation

Practice determining whether exceptions apply, and interpreting implications of exception(s) in a wide range of common situations

If exception applies, determine implications

Practice determining how to recognize need for and gain help in a wide range of common situations

Get help as needed

Practice with cases that involve entire process

What I hope you see here is that the activities (and supporting information, graphics, and multimedia) are designed specifically to involve learners in gaining skill with the wide range of contexts in which judgments need to be made. (For another view of complex design, see " How to Build Composite Learning Progressions Using Approximations" in the December 16, 2002 issue of Learning Solutions Magazine.)

Six mastery problems

Why do folks who build online learning too often concentrate on near(er) transfer and procedural objectives (e.g., simple content interactions like drag and drop exercises and simple quizzes) when far(ther) transfer and declarative objectives (e.g., in-depth tutorials, simulations, feedback and coaching over time, discussions with experts, realistic activities, field work) are what's needed for learners to gain the desired level of mastery? There are many reasons for this, but here are six really problematic ones, in my opinion:

Not knowing what critical outcomes are needed from the instruction

Not influencing stakeholders towards interventions needed for the critical outcomes to occur

Not realizing that far(ther) transfer is needed for certain critical outcomes

Deficient skills at designing for transfer

Mistaken assumptions that online learning has to be all online

Selecting one tool and building only what that tool will allow

Recognize some common issues here? Yeah, I'd agree that realities and practicalities often make it hard to do what might be totally optimal to ensure transfer. In my mind, however, that doesn't give us permission to develop the simplistic learning environments I see so often. Many instructional developers think they can choose only between the most expensive forms of instruction (high-fidelity simulations, for example) and the worst forms of instruction (simplistic page turners). That's simply wrong-headed thinking, in my opinion. There's a continuum between better and worse choices for instructional strategies. Selecting those that are on the better end doesn't necessarily have to mean they're more expensive or time consuming to design and build.

Clients sometimes tell me they just want to build awareness-level training and transfer isn't a major consideration. I gently (well, maybe not so gently) push back. Is "awareness" training really what's needed or do people need to be able to do something as a result of the instruction? Sometimes information is enough and formal training with practice and feedback is overkill. But when critical instructional outcomes are needed, designing for adequate transfer isn't just a nice-to-do activity. We can have a conversation about designing for box-checking another time.

A final question: Did transfer occur?

If we design for transfer, it often makes sense to gauge whether transfer occurred. The classic summative evaluation model was developed by Donald Kirkpatrick in 1975. (Summative evaluation helps summarize the results of instruction, and is conducted after the instructional materials have been used by actual learners and results measured. This is distinguished from "formative evaluation," which is part of the instructional design process and helps formulate instruction before the materials are delivered to a majority of the targeted learners.) See Table 4 for an outline of the Kirkpatrick model. It purports to evaluate instruction at these four levels. (I say "purports" because it depends on how the evaluation is done.)

Transfer is Level 3 (I could easily argue that Level 4 is about transfer as well) and asks "Can learners apply the knowledge and skills to the job?" If you have put in the effort to design for transfer, it is important to establish the critical outcomes needed from instruction at the front end and figure out what indicators (of progress, mastery, attitudes, or effect) can be used to show that transfer occurred. The key here is to plan, in the beginning stages, when and how to collect and analyze this data. Planning should, of course, involve discussions with stakeholders about what they desire as evidence because their opinions may be different than our own.

The bottom line

We build instruction to impact what people can do in the real world, not what they can do during instruction. For our efforts to be successful and worth the resources put into them, it's not enough for learners to show "learning" in the classroom, they need to show appropriate application (transfer) in the real world. But research shows that the desired level of transfer happens fairly infrequently. This is a huge problem, but there are effective solutions, even if many instructional experiences don't take advantage of them.

Instructional strategies that promote transfer include making the context of learning like the context of application, fostering connections between previous and new knowledge, providing extensive and varied practice, providing activities that help learners mine differing situations for underlying principles, and helping learners monitor their learning. Different types of learning objectives have different goals, necessitating different activities and practice opportunities. Procedural, how-to-do, objectives generally involve near(er) transfer, requiring activities and practice that help learners gain skill with utilizing a fairly consistent set of rules. Declarative objectives or why-to-do objectives generally involve far(ther) transfer, requiring activities and practice to help learners gain skill with determining the best course of action.

What transfer concepts tell us is how to be more effective at what we do. Folks who build online learning too often concentrate on near(er) transfer even when far(ther) transfer is what's needed for learners to gain the desired level of mastery. This is a shame because it often reduces impact and makes it look like it's online learning, rather than inadequate design, to blame for inadequate outcomes.

If you're looking for additional ideas on how to design for transfer, check out my earlier columns on designing online interactions (Learning Solutions Magazine, May 3, 2004 and June 29, 2004) and the resources listed below.

References and resources

Clark, R.E. & Voogel, A. (1985). Transfer of Training Principles for Instructional Design. Educational Communications and Technology Journal, 33(3), 113-123.

Greeno, J.G., Smith, D.R., & , J.L. (1993). Transfer of situated learning. In Douglas K. Detterman & Robert J. Sternberg (Eds.) Transfer on trial: intelligence, cognition, and instruction. : Ablex Publishing.

Gruber, H., Law, L-C, Mandl, H., & Renkl, A. (1995). Situated Learning and Transfer. In P. Reimann & H. Spada (Eds.), Learning in humans and machines. : Elsevier Science.

Perkins, D.N. & Salomon, G. (1994). Transfer of Learning. In Torsten Husén & T. Neville Postlethwaite (Eds.), International Encyclopedia of Education, Second Edition. : Pergamon Press. Available: http://learnweb.harvard.edu/alps/thinking/docs/traencyn.htm

Perkins, D. N. & Salomon, G. (1987). Transfer and teaching thinking. In: Perkins D N, Lochhead J, Bishop J (eds.) 1987 Thinking: The second international conference (pp. 285-303). Erlbaum,

Perkins, D.N. & Salomon, G. The Science and Art of Transfer. Available: http://learnweb.harvard.edu/alps/thinking/docs/trancost.htm

Van Merriënboer, J. J. G., Clark, R. E., & De Croock, M. B. M. (2002). Blueprints for complex learning: The 4C/ID-model. Educational Technology, Research and Development, 50(2), 39-64. Available: http://www.ou.nl/otecresearch/publications/Jeroen%20van%20Merrienboer/Jeroen%20vanMerrienboer%20etrd.pdf

# data[].attributes.attachment_link.title
Can They Do It in the Real World? Designing for Transfer of Learning

# data[].attributes.attachment_link.description
The purpose of e-Learning is to improve the accomplishment of real tasks in the real world. Transfer is the key to achieving this purpose, and designers shou...

# data[].attributes.attachment_link.readable_text
Notice: This HTML version is intended only to facilitate reading. If you want to quote the paper, please use PDF version, which contains page numbers.
﻿

Geri Manning

Definitions and Parameters

The relationship between adult learning and self‑directed learning is a topic worth exploring on both theoretical and practical grounds. Mezirow points out that, "no concept is more central to what adult education is all about than self‑directed learning".[1]

Knowles describes self‑directed learning as "a process in which individuals take the initiative without the help of others in diagnosing their learning needs, formulating goals, identifying human and material resources, and evaluating learning outcomes". [2]

What and who is an adult learner? A person is an adult to the extent that he or she is performing social roles typically assigned by our culture to those it considers adults, and to the extent that the individual perceives him or herself to be essentially responsible for his or her life. A child is not responsible for his or her life even from a legal point of view. According to Neimi, the adult learner is one who returns to study, on a full‑time or part‑time basis, after a period of time spent in other pursuits.[3] Freedman states that the adult learner is someone who is motivated enough to want to pin further education at the end of a working day or is required to come to a program for certification.[4]

Conceptual Framework of Adult Learning Theory‑Literature Review and Critique

Modem adult learning theory has its foundations in the following assumptions of Lindeman:

1. Adults are motivated to learn as they experience needs and interests that learning will satisfy.

2. Adults' orientation to learning is life‑centered.

3. Experience is the richest source for adults' learning.

4. Adults have a deep need to be self‑directing.

5. Individual differences among people increase with age.[5]

The first three assumptions clearly demonstrate a very pragmatic orientation towards learning. The fourth assumption is clearly the most important for this paper because of its obvious relation to self‑directed learning. The last assumption is interesting and demonstrates the value of self‑directed learning, where there is variation in both the form and the speed of learning.

The implications of these assumptions are clearly that learning should be largely based on individuals' experiences and focused on life situations and life goals. Instruction should emphasize the analysis of experiences and the role of the instructor should be that of a facilitator or engager rather than a transmitter of knowledge. The last assumption would indicate that teaching strategies should take into account differences in style, time, place, and pace.

The roots of adult learning theories can be traced to research in group dynamics approaches in the late 1940s and 1950s. According to this early theory, the adult learner mobilized a set of motivational, perceptual, emotional, and attitudinal ‑systems to resist learning and changing unless the climate was safe to do so. Thus, learning and changing could be viewed as either safe or unsafe strategies. Knowles's theory of adult education suggested that adults succeed in situations where they are highly motivated, where they can participate in the learning process, and where learning content had practical applications. This modem approach to adult learning theory had a very pragmatic orientation. In addition, Knowles also found that adults find an informal setting conducive to learning, and they want exact details of what is expected of them, opportunities to practice their new skills and immediate feedback on their learning process[6]. Are adults sometimes slightly demanding?

Knowles also asserted that learners themselves are important resources for teaching; activating and incorporating rich experiences into the teaching material making it more relevant.[7] Therefore, the education of adult learners has to go beyond the transmission of knowledge to helping persons in directing and managing their own learning. Again, a possible reference to self‑directed learning. Adult learning according to Knowles should also include a psychological climate favorable to learning.

After Knowles' theory of andragogy appeared, Tough reported the results of seven years work on efforts of adults to learn, change and grow. Tough's research was not only concerned with why adults learn, but also with how they learn. He found that adults organized their learning efforts around "projects ... defined as a series of related episodes, adding up to at least seven hours. In each episode, more than half of the person's total motivation is to gain and retain certain fairly clear knowledge and skill, or to produce some other lasting change in himself.[8] Tough concluded that adult learners proceed through several phases in the process of engaging in a learning project. He speculated that helping them gain increased competence in dealing with each phase with decreasing amounts of assistance might be one effective way of improving their learning.[9]

Mezirow's perspective transformation centered upon his work with community college re‑entry programs for women. He described what the women experienced as a unique kind of learning: Learning the psychological and cultural assumptions that influenced how they saw themselves and their relationships. Later, Mezirow grounded his observations in the critical theory of Jurgen Haberman, who described three areas in which people sought knowledge: work, relationships, and emancipatory action. Mezirow translated these areas into domains of adult learning, each with its own distinctive model and needs. Habermas' domain of emancipatory action, the uniquely adult domain of learning, is what Mezirow means by perspective transformation. According of this theory, the most important task for adult educators is assisting people become aware of the psychocultural assumptions that have shaped how they see themselves and others.

More recently, in developing college courses based on adult learning theory, Brookfield suggested six principles of effective practice in facilitating learning: (1) voluntary participation in learning; (2) mutual respect; (3) collaborative spirit; (4) action and reflection; (5) critical reflection; and (6) self‑direction[10]. The latter principle is most closely associated with self‑directed learning.

Conceptual Framework of Self‑Directed Learning ‑ Literature Review and Critique

What is this notion of self‑directed learning that keeps being mentioned as a part of adult education? When an individual or group decides that they want to learn certain information, knowledge or skill, they often seek the help of a teacher or professional instructor to tell them how to proceed and to supervise the learning process. However, another alternative for an individual is to assume the primary responsibility for planning, initiating, and conducting the learning project. Such behavior can be called either self‑instruction, self‑education, independent study, individual study self‑teaching, or self-directed learning.

Knowles identifies three reasons for self‑directed learning as follows:

1. Individuals who take the initiative in learning, learn more things and learn better, than do people who sit at the feet of teachers possibly waiting to be taught.

2. Self‑directed learning is more in tune with our natural processes of psychological development.

3. Many of the new developments in education ... put a heavy responsibility on the learners to take a good deal of initiative in their own learning.[11]

He continues with three implications as follows:

1. It is no longer realistic to define the purpose of education as transmitting what is known.

2. There must be somewhat different ways of thinking about learning.

3. It is no longer appropriate to equate education with youth.[12]

Knowles also states five key assumptions which underlie self‑directed learning:

1. Self‑directed learning assumes that the human being grows in capacity and needs to be self‑directing as an essential component in maturing.

2. Self‑directed learning assumes that the learners' experiences become an increasingly rich resource for learning that should be exploited along with the resources of experts.

3. Self‑directed learning assumes that individuals become ready to learn what is required to perform their evolving life task or to cope more adequately with their life problems.

4. Self‑directed learning assumes that the natural orientation of individuals is task or problem‑centered.

5. Self‑directed learning assumes that learners are motivated by internal incentives such as the need for self‑esteem.[13]

However, it is interesting that Knowles does acknowledge that there are situations where the learners' experience is of little value including: when they have no previous experience in the subject matter, where readiness to learn is governed by one's level of maturity, and when the learner is motivated by external pressures[14]. Confessore and Confessore explain, "The point is made that there may be situations where teacher‑directed learning is to be preferred over self‑directed learning[15]. But even here Knowles continues to emphasize learner responsibility and critical thought"[16].

Throughout history, some adults have planned and conducted their own learning. For example, Socrates, Benjamin Franklin, Abraham Lincoln, and John Stuart Mill were considered self‑educated men. The earliest tradition in American schools was that of each student learning his lessons by himself; during the nineteenth century graded classrooms and group instruction became common in North American schools. During the 1950's and 1960's, self‑teaching became an important component of a variety of experimental programs in both elementary and secondary schools. Tough points to three specific attempts to promote self‑teaching in schools.

First is self‑selection where children or adults will actually select books that meet their level of maturity and their learning needs[17]. My problem with this approach is that many individuals do not know what they need to learn in subjects for which they have little knowledge.

A second example of self‑teaching is the use of programmed instruction and teaching machines. Tough points to three major principles of programmed instruction: (1) The student should learn from printed materials rather than from the teacher or the group; (2) He should learn at his own pace; and (3) He should test his own progress[18]. It is interesting to note that when Tough wrote these principles he had no idea the potential of personal computers and their effect on methods of education.

Finally, is the attempt in colleges and universities to promote independent study. One of the early attempts to promote independent study was conducted at Stanford University in the 1930's. During later years, many other universities have encouraged independent study where students make decisions about learning with little assistance from faculty members. Bonthuis pointed out that independent study is called by various names such as honors courses, senior thesis, individual study, and independent reading; and that it can be defined as "the pursuit of special topics or projects by individual students under the guidance of faculty advisers apart from organized courses"[19].

Forster proposes a more comprehensive definition of independent study in terms of four variables: (1) Where students acquire knowledge by his or her own efforts and develop the ability for inquiry and critical evaluation; (2) it includes freedom of choice in determining those objectives; (3) it requires freedom of process to carry out the objectives; and (4) it places increased educational responsibility on the student for achieving course objectives. Clearly, there is a trade‑off here where more control also means accepting more responsibility.

Applications to Lifelong Learning Situations

An interesting question is whether self‑directed learning implies a life‑long education. The obvious answer is "no" because it is clear that an individual can elect to complete only one self‑directed learning course and not choose to continue with any form of education. However, Candy has a more enlightened view of this issue: "The relationship between self‑directed learning and life‑long education is a reciprocal one. On the one hand, self‑directed learning is one of the most common ways in which adults pursue learning throughout their life span, as well as being a way in which people supplement learning received in formal settings. On the other hand, lifelong learning takes, as one of its principle aims, equipping people with skills and competencies required to continue their own self‑education beyond the end of formal schooling. In this sense, self‑directed learning is viewed simultaneously as a means and an end of lifelong education"[20].

According to the definition of lifelong education adopted by the Unesco Institute of Education, it should have the following characteristics:

1. Last the whole life of each individual;

2. Lead to the systematic acquisition, renewal, upgrading and completion of knowledge, skills, and attitudes made necessary by the constantly changing conditions in which people now live;

3. Have, as its ultimate goal, promotion of the self‑fulfillment of each individual;

4. Acknowledge, the contribution of all available educational influences, including formal, nonformal, and informal; and most importantly,

5. Be dependent for its successful implementation on people's increasing ability and motivation to engage in self‑directed learning activities.

An important distinction regarding self‑directed learning is whether it is a goal or a process. For some authors and researchers, self‑directed learning is simply a method of organizing instruction. The best example of this approach is found in Tough's list of 13 steps in beginning a self‑directed learning project:

1. Deciding what detailed knowledge and skill to learn;

2. Deciding the specific activities, methods, resources, or equipment for learning;

3. Deciding where to learn;

4. Setting specific deadlines or intermediate targets;

5. Deciding when to begin a learning episode;

6. Deciding the pace at which to proceed during a learning episode;

7. Estimating the current level of knowledge and skill and progress in gaining the desired knowledge and skill;

8. Detecting any factor that has been backing or hindering learning;

9. Obtaining the desired resources or equipment;

10. Preparing or adapting a room;

11. Saving or obtain the money necessary for the use of certain human or nonhuman resources;

12. Finding time for the learning; and

13. Taking certain steps to increase the motivation for learning[21].

It is interesting to note that although this list includes many practical issues regarding self‑directed learning, Tough did not ignore motivation, which is especially important for self‑directed learning. Another observation about this list is that Tough does not ignore the important issue of necessary resources and time which are often difficult to obtain.

Potential Characteristics of Self‑Directed Learners

For other authors and researchers, self‑directed learning is not so much a method of organizing instruction as it is a characteristic of learners. This leads logically to the following question or issue: what do we want self‑learners to become--perhaps, some form of self‑directed individuals? Candy explains: "Most government policies on education, and many institutional policies and mission statements as well, stress the development of independence, autonomy, and the ability to control their own affairs as major objectives for learners of all ages. Indeed, the rapid rate of political social, and technological change with which we are currently confronted has increased, rather than diminished, the need for self‑directed citizens"[22].

One potential characteristic of self‑directed learners is the striving for the democratic ideal. As Naisbitt points out, there is a trend in America from representative to participatory democracy brought about by the increasingly widespread belief that "people whose lives are affected by a decision must be a part of the process of arriving at that decision"[23]. As Candy explains, "As people become more accustomed to, and skilled at, informed participation and choosing in these aspects of their lives, they have made increasing demands for similar power sharing in relation to their education. These demands go far beyond so‑called participatory learning methods, and extend into all aspects of the educative process, from the assessment of needs through the design of programs to the evaluation of learning outcomes"[24].

Another potential characteristic of self‑directed learners is an increased emphasis on the ideology of individualism. Keddie points out that "the notion of individuality as a desirable personality goal is not universal, but is cultural specific and tends to be found in those cultures (such as ours) where high status is obtained by competitive individual achievement"[25].Also, there is a class dimension to individualism. Also, Keddie explains, "Nor is it valued equally by all groups within our society. The force of the research which has attempted to distinguish between middle and working class cultures has stressed that while the middle class are oriented towards the value of individual achievement, working class culture places emphasis on collective values"[26].This point is confirmed by Brookfield who, in his review of self‑directed learning research, laments the failure to deal with working class learners[27].

A final potential characteristics of self‑directed learners involves the concept of egalitarianism. As Candy explains, "The broad area of egalitarianism in adult education is a conceptual and terminological minefield, concerned as it is with issues of equity as well as equality-‑of opportunity, of participation, and of outcomes"[28]. There are two broad categories of reasons why adult learners might choose to treat learners as equals. First, the adult learner may be seen to be as autonomous as the teacher, capable of making enlightened choices both as to the content of the curriculum and the method of instruction. Second, since there is a pragmatic threat that adult students will not submit to learning that is not acceptable and useful to them, there is a belief among teachers that they should not strictly impose their values and beliefs if they can avoid doing this.

Open Education

Closely related to the idea of egalitarianism is Lawson's notion of "the democratization of knowledge," where the creation, distribution, and interpretation of knowledge are seen as social processes involving everyone[29]. It is interesting to note that this trend according to Crittenden is, in fact "reacting to the excesses of the mechanistic, positivist account of knowledge"[30].

In opposition to the positivist account of knowledge, where knowledge is objective and external to the learner, are two alternative paradigms. The first, called radical subjectivism, holds that each person is entirely the author of his or her own knowledge, and that there is no independent objective world outside of the individual mind. A second, less radical approach, is the relativistic view of knowledge which is expounded by Rathbone under the rubric of "open education." Their tenets include:

1. Knowledge is idiosyncratically formed, individually conceived, fundamentally individualistic. Theoretically, no two people's knowledge can be the same, unless their experience is identical.

2. Because knowledge is basically idiosyncratic, it is most difficult to judge whether one person's knowledge is better than another's.

3. Knowledge does not exist outside of individual knowledge; it is not a thing apart.

4. Knowledge is not inherently ordered or structured.

5. People do not make their cognitive way up any universal ladder. On the contrary, the learner envisioned by open education faces a world open to a plurality of interpretations[31].

Given these beliefs about the nature of knowledge, it is not surprising, that in open education, we move away from the concept of master and apprentice and towards notions such as facilitators, resource persons, and self‑directed learning. In fact, under this paradigm, since knowledge is fundamentally individualistic, self‑directed learning is perhaps the most valid form of learning.

What factors inhibit or encourage the use of self‑directed learning? Kops points to a variety of enhancing factors that include: good availability of resources, supportive and consistent leadership, and learning opportunities available from external colleagues[32]. Some negative factors include: Negative micro‑climates, restrictive policies, limited delegation of authority that restricts initiative, and constrained economic condition.

Interpretive Summary ‑ A Critical Review of Self‑Directed Learning Research

The efforts of Tough, Knowles, and others to understand and develop self-directed learning as a critical component of adult education have been the subject of this paper. In terms of self‑directed learning and social settings, Tough, Brookfield and Moore have argued that the self‑directed learner should not be thought of as an intellectual Robinson Crusoe, but, instead, as someone with a strong reliance on external resources, both human and material, in the conduct of learning, projects[33].

In terms of self‑directed learning and independence, Tough and Knowles emphasize the fact of the learner's control over the planning and execution of learning.

In terms of self‑directed learning and middle‑class life styles, many researchers have focused on educationally advantaged populations including Tough and Brookfield . Thus, there is an issue regarding the resultant generalizations about self‑directed learning and if they are culture and class specific.

In terms of self‑directed learning and its applications in schools, Tough Bonthuis and Forster point to self‑selection, programmed instruction, and independent study.

In terms of self‑directed learning and lifelong education, Candy and the Unesco Institute of Education point to self‑education as both a means and an end in supplementing formal schooling.

In terms of how to organize self‑directed learning, Tough outlines 13 steps which represents the best summary available on how to conduct self‑directed learning including steps on deciding what to learn and motivation for learning.

In terms of potential characteristics of self‑directed learners, Naisbitt points to the democratic ideal; Keddie and Brookfield point to the notion of individualism; and Candy points to egalitarianism.

Finally, in terms of self‑directed learning and open education, Rathbone, points to five key tenets including the fact that knowledge is fundamentally individualistic.

Refbacks

There are currently no refbacks.

This work is licensed under a Creative Commons Attribution 3.0 License.

(c) Washington Institute of China Studies

We encourage you to visit CEOpedia - The Management Online

# data[].attributes.attachment_link.title
Self-Directed Learning: A Key Component of Adult Learning Theory | Business and Public Administration Studies

# data[].attributes.attachment_link.description
Notice: This HTML version is intended only to facilitate reading. If you want to quote the paper, please use PDF version, which contains page numbers. ﻿ Geri Manning The relationship between adult learning and self‑directed learning is a topic worth exploring on both theoretical and practical grounds.

# data[].attributes.headline
Neuroscience and Implications for Learning

# data[].attributes.subject
Neuroscience and Implications for Learning

# data[].attributes.attachment_link.readable_text
Cite this

Brabeck, M., & Jeffrey, J. (2015, March 9). Practice for knowledge acquisition (not drill and kill). American Psychological Association. https://www.apa.org/education-career/k12/practice-acquisition

Designing activities with the goal of transferring knowledge

It doesn't matter what subject you teach, differences in students performance are affected by how much they engage in deliberate practice. Researchers who have investigated expert and novice performance have uncovered important distinctions between deliberate practice and other activities, such as play or repetition.

Deliberate practice is not the same as rote repetition. Rote repetition - simply repeating a task - will not by itself improve performance. Deliberate practice involves attention, rehearsal and repetition and leads to new knowledge or skills that can later be developed into more complex knowledge and skills. Although other factors such as intelligence and motivation affect performance, practice is necessary if not sufficient for acquiring expertise (Campitelli & Gobet, 2011).

Define practice:

"Deliberate practice (DP) occurs when an individual intentionally repeats an activity in order to improve performance. The claim of the DP framework is that such behavior is necessary to achieve high levels of expert performance." (Campitelli & Gobet, 2011, p. 280).

"Deliberate practice consists of activities purposely designed to improve performance." (Gobet & Campitelli, 2007, p. 160).

Benefits of deliberate practice

Practice is important for teaching and learning in at least five ways:

1. Practice greatly increases the likelihood that students will permanently remember new information (Anderson, 2008).

2. Practice increases student facility or automaticity (learning to apply elements of knowledge automatically, without reflection). Automaticity is usually only achieved through extensive rehearsal and repetition. Automaticity frees up students cognitive resources to handle more challenging tasks (Brown & Bennett, 2002; Moors & De Houwer, 2006).

3. When students practice solving problems, they increase their ability to transfer practiced skills to new and more complex problems. This is true in childhood (Glover, Ronning, & Bruning, 1990) and adult years (Li, Schmiedek, Huxhold, Röcke, Smith, & Lindenberger, 2008).

4. Practice helps students acquire expertise in subject matter and, therefore, it helps to distinguish novices from experts in given subjects (Ericsson, Krampe, & Clemens, 1993)

5. Cognitive gains from practice often bring about motivation for more learning (Kalchman, Moss, & Case, 2001).

Teachers should think of practice not as rote repetition, but as deliberate, goal-directed rehearsal paired with reflection on problem-solving processes. For example, when teachers have students practice identifying phonemes, the ultimate goal is for students to read with fluency and comprehension. Although fluent reading may be too complex a task for beginning readers to tackle, the more manageable task of identifying phonemes may scaffold students learning to achieve the ultimate goal of reading. That is, teachers should always design practice activities with the goal of transferring knowledge to new and more complex problems in mind.

General recommendations for practice and instruction

Research (Anderson, 2008; Campitelli & Gobet, 2011; Ericsson, Krampe, & Clemens, 1993) suggests several conditions that must be in place in order for practice activities to be most effective in moving students closer to skillful performance. Each of these conditions can be met with carefully designed instruction:

Because practice requires intense, focused effort, students may not find it inherently enjoyable. Therefore, teachers can encourage students to practice more by pointing out every time that practice has actually improved their performance. Motivate your students to practice by:

Expressing confidence in students' ability to succeed in solving practice problems.

Designing activities that maximize opportunities for students to succeed.

Teachers should design practice tasks with students existing knowledge in mind. When students succeed at practice problems, the benefits of practice are maximized. But when students become frustrated with unrealistic or poorly designed practice problems, they often lose motivation, will not receive the full benefits of the practice they have done, and will be less motivated to attempt future practice problems.

Students receive the greatest benefits from practice when teachers provide them with timely and descriptive feedback.

Students should have repeated opportunities to practice a task through practicing other tasks like it.

What type of feedback is most effective?

Feedback is most effective when it contains descriptions of how students work meets performance criteria and what students can do to improve. This kind of descriptive feedback is more effective than feedback consisting of vague, general comments (e.g., "nice work or "needs improvement).

Feedback should also be focused on the learning process. That is, teachers should focus their feedback on helping students reflect on their problem solving skills, as well as on progress they have made.

Do's:

1. Vary practice activities.

2. Distribute practice over extended periods of time.

3. Provide clear instructions on performance expectations and criteria.

4. Before asking students to practice independently, model the problem-solving process that you expect students to use.

5. Break complex problems into their constituent elements, and have students practice on these smaller elements before asking them to solve complex problems independently.

6. Guide students through sample practice problems by using prompts that help them reflect on problem-solving strategies.

7. Provide students with fully completed sample problems as well as partially completed sample problems before asking them to apply new problem-solving strategies on their own.

8. Wait until students actually need more information to solve a complex problem before you give them more information. This strategy - known as "just-in-time instruction" - helps keep the amount of information that students must hold in their short-term memories to a manageable level as they practice (Linneman & Plake, 2006; Simkins & Maier, 2008).

9. Provide plenty of opportunities for students to practice applying problem-solving skills before you test them on their ability to use those skills.

Don'ts:

1. Don't ask students to practice complex problem solving without providing them with plenty of guidance and feedback.

2. Don't overload students by presenting information in redundant formats.

3. Don't give your students complex practice problems before they have the skills they need to succeed.

Research suggests that when teachers construct problems for students to practice, they should keep in mind the limitations of human memory.

Moving information to permanent storage is often explained as a multistore model of memory (Atkinson & Shiffrin, 1968; 1971; Baddeley, 1996; 2002). According to this model, our brains have three memory storage systems: sensory memory, short-term memory and long-term memory (Baddeley, 1996; 2002; Carlson, Sullivan, & Schneider, 1989). Learning occurs when we move information from working memory to long-term memory, and practice helps with this process.

Deliberate practice (sometimes called 'rehearsal') keeps the information in our short-term memory long enough for it to move to long-term memory. Once it is in long-term memory, it can be built upon to create more and more complex associations (Baddeley, 2002).

Most researchers agree that there are forms of Short-Term Memory (STM) for different modalities, such as visual STM, auditory STM and motor STM. For example, Baddeley (1992; 1996; 2002) suggests that short-term memory is a dynamic place where sounds and images are turned into verbal and pictorial models. STM is also thought to have a "central executive" that manages the information it is holding. This central executive also controls our awareness of that information (Baddeley, 2002).

The implication for teachers is that they should present material in multiple modalities. If a child who is learning to read hears a word, sees the word and a picture of the word, there will be more learning. The child can get the visual information from the visual STM and additional auditory information in the auditory STM. These two sensory sources of information supplement and complement one another (Liao, 2014). However, teachers must be careful not to have too much extraneous information in the classroom. Over stimulation can put too much demand on working memory (Pass & Kester, 2006).

Short-term or working memory

Working memory or short-term memory, is stored for very short periods of time - minutes at most. Information in our short-term memory is generally housed in the temporal lobe of the brain (the hippocampal region). It allows you to remember phone numbers and also information that comes from long-term memory right before you need to use it. Short-term memory is also the memory system that is used when we cram for a test at the last minute. Attention difficulties, distractions and overload of too much information all negatively impact our short-term memory and cause it to fail. We all have a limited ability to focus on too much stimuli at the same time, and if we don't process the information, we lose it. Practice helps us increase our ability to access information rapidly and automatically.

Practice also frees our brains to process more challenging information and problems. For example, if a child has memorized the multiplication table and can retrieve it automatically, working memory is freed to do more complicated computations.

Practice can improve children's working memory and enhance learning of academic skills, such as reading comprehension and mathematical reasoning (e.g., Dahlin, 2011; Gersten, Fuchs, Williams, & Baker, 2001; Holmes, Gathercole, & Dunning, 2009), verbal learning (Liao, Kronemer, Yau, Desmond, & Marvel, 2014) and motor skills (Gomes, Ugrinowitsch, Marinho, Shea, Raisbeck, & Benda, R., 2014).

And practice using visual spatial tasks can improve visual-spatial working memory (Melby-Lervag & Hulme, 2012; Shipstead, Redick, & Engle, 2012). Likewise, children can be taught a rehearsal or practice strategy to help them improve their reading comprehension (e.g., Gersten, Fuchs, Williams, & Baker, 2001; Rose, Cundick, & Higbee, 1983). Moreover, rehearsal is easier to learn and less demanding than other strategies (Turley-Ames & Whitfield, 2003).

Long-term memory

When working-memory is stored, it becomes long-term memory. Long-term memory is the depository of memories throughout the brain that results from the ongoing chemical processes that changes neuronal connections. The formation of long-term memories takes place over the span of days, weeks and in some cases years. As the memories are consolidated, neuron connections become more and more efficient, and in the process, connections that are no longer useful are discarded from lack of use.

Although the capacity of our long-term memory is apparently limitless (as far as we know, no one has ever stored all that the brain is capable of storing), working memory can typically hold only seven items (plus or minus 2) at any given time, and these items "decay" rapidly (Miller, 1956; Baddeley, 2002).

Research on the brains of rats has shown that relatively short periods of practice can enhance the plasticity of the brain and actually change its structure (Rioult-Pedotti, Friedman, Hess, & Donoghue, 1998). Brain imaging has shown that even a brief lesson on new words changes brain circuits (Allami, Brovelli, Hamzaoui, Regragui, Paulignan, & Boussaoud, 2014; Abdullaev & Posner, 1998; Raichle et al., 1994) and retrieval (Habib, Nyberg, & Tulving, 2003).

Experts and novices differ in the amount and structure of information stored in their long-term memories. These cognitive differences occur in large part because of differences in the amount of deliberate practice in which each has engaged (Cantor & Engle, 1993).

Extensive and deliberate practice makes it possible for students to access and apply increasingly complex information without explicitly thinking about it. In other words, it increases automaticity (see earlier discussion of automaticity) (Anderson, 2008; Case, 1985, 1991). Automaticity leaves students' working memories free to process new information (Kotovsky, Hayes, & Simon, 1985). Since working memory can be overloaded at any time, 'savings' from automaticity become very important. When there is too much information in our working memory it will fail, and the chemical processes that transfer information to our long-term memories also fail. Long-term learning is enhanced by a distribution process in which information is repeated, allowing time with time in between practice sessions, rather than crammed practice.

Reviews and tests are forms of practice that can improve learning. Tests (or quizzes) that are given immediately after a learning exercise give children opportunities to practice. Because learning is recent, students tend to do well on these tests. However, their success does not ensure long-term retention. Teachers can provide time during class to give students additional practice in taking tests. Some tests, such as tests with open-ended answers have been shown to enhance learning because they involve students in the "retrieval" of information from long-term memory. Tests are more effective when they are given at spaced intervals and when they are given frequently (Cull, 2000; Dempster; 1991; Rodriguez, Michael, 2004;Roediger & Karpicke, 2006).

Chunking information, or combining small bits together in short-term memory, is another strategy that students can use to increase their STM holding capacity. Although chunking gives a student more capacity in their STM, its usefulness depends on how much knowledge a person already has. The more knowledge one has on a topic, the more likely that one can "chunk" incoming information into larger and more meaningful chunks. This is why knowledge itself adds to one's ability to solve complex problems. Children who use chunking are more likely to be strategic about their learning. Teachers can help children become more strategic by explicitly teaching them strategies like chunking.

Example of chunking information

The following digits can be seen as a random list of numbers: 14921776. Random or meaningless information taxes the limited capacity of short-term memory (STM). However, if a student "chunks" the information into two dates (1492: Columbus discovered America; and 1776: the year the Declaration of Independence was signed) it is learned as 1492 1776. This leaves room in the short-term memory for more information.

Chunking allows several units of information to be compressed into a single meaningful unit or chunk (e.g., whereas a random number string above represents 8 discrete units to be stored in short-term memory (near its maximum capacity), the two meaningful dates represent only two chunks of information to be stored. This leaves space in the STM for more information to be held. And when more information is held in STM, there is more information available for transfer to long-term memory where it can be permanently stored (Gobet et al., 2001).

Chunking can develop experts' schema. Information stored in the brain in larger chunks of integrated concepts are known as "schemas." For example, a novice chess player who does not yet have complex schemas for chess playing has to devote his or her limited working memory to processing large amounts of information while playing (Anderson, 1996).

An expert, on the other hand, can easily access schemas from long-term memory (deGroot, 1966; Cantor & Engle, 1993). With practice, a novice player can construct chess-playing schemas and therefore increase the amount of information stored in long-term memory. In this way, practice accessing and applying knowledge helps one to transfer that knowledge into a "permastore" of long-term memory so that he or she can more efficiently utilize space available in the working memory (Elo, 1978; Kotovsky & Fallside, 1989).

Theories explaining expert performance

1. Many researchers (e.g., Ericsson et al., 1993; Baddeley, 2002) argue that differences in the amount of practice account for the majority of performance differences between individuals, resulting from differences in the amount and structure of knowledge stored in long-term memory.

2. Other researchers emphasize innate, genetic differences or talent as the main factor accounting for differences between expert and novice performance (Mosing, et.al., 2014; Plomin, DeFries, McClearn, & Rutter, 1997).

3. More recently, researchers have emphasized an interaction between innate and behavioral factors in accounting for differences in performance levels (Gobet & Campitelli, 2007).

Overall, the research supports the view that deliberate practice plays a role in performance differences and can reduce performance differences between individuals who are thought to possess talent and those who do not (Chase & Ericsson, 1981). See Gobet and Campitelli (2007), Mosing, et.al., (2014) and Macnamara, et.al., (2014) for a comprehensive review of this debate.

What can a teacher do to maximize the positive effect of practice?

When teachers assign students to complete practice problems that are structurally similar but different in surface features, it helps them discriminate between relevant and irrelevant information in a given problem. This outcome makes it more likely that students will be able to transfer knowledge gained from practice to new and more complex problems (Paas, 1992). As with all scaffolds, they should be diminished gradually as learners become increasingly more independent.

Students' problem-solving skills also increase when teachers distribute practice over time rather than "cramming" practice into short periods (Bahrick & Hall, 2005). Assignments involving practice are more effective when they are shorter, more frequent and distributed over longer periods of time (Cooper, 2007; Cooper, Robinson, & Patall, 2006; Epstein & Van Voorhis, 2010). This distributive effect is particularly important because it also makes it more likely that students will recall information over longer periods of time. Therefore, distributed practice helps students transfer information into their long-term memory.

Teachers should also have students begin homework during class. By doing so, teachers can monitor students to ensure they understand and can solve practice problems correctly before they practice independently. If teachers are unable to monitor this initial practice, they should explain to their students where they can obtain the information (textbooks, web sites, handouts, etc.) they need to complete the assigned practice problems correctly.

Reviews and tests are a form of practice that can improve learning. Tests provide opportunities for practice that enhance learning. Open-ended test questions also provide practice in retrieving information. Both reviews and tests are most effective when they are well spaced and frequent (Dempster, 1991).

Teachers can train students to reflect on their thinking when solving problems by providing them with lists of questions. This kind of "strategy instruction" helps students to construct schemas more efficiently by facilitating a metacognitive awareness of the problem-solving process. That is, students learn more about how they learn and this helps them with new learning.

Teachers can increase students' abilities to transfer existing problem-solving knowledge to new problems when they prompt students to deliberately reflect on problem-solving strategies they have used before. (Renkl, Stark, Gruber, & Mandl, 1998; Rosenshine & Meister, 1992; Stark, Mandl, Gruber, & Renkl., 2002).

Is homework always effective practice?

There is no question that homework can provide students with opportunities for practice but there are more and less effective homework assignments. Research on homework (Cooper, 2001, 2006; Epstein & Van Voorhis, 2010) suggests that the relationship between time spent on homework and students' academic achievement varies with grade level. When parental involvement is well structured it can also enhance the effectiveness of homework on learning (Epstein & Van Voorhis, 2010; Marzano & Pickering, 2007).

How much time should be spent on homework?

Although high school students appear to benefit from at least two hours of homework per night, there is little or no relationship between time spent on homework and academic achievement for young (grades 1-3) students (Marzano, & Pickering, 2007). Younger students may benefit more from supervised in-school practice than from homework. Middle school students may benefit from one to two hours of homework per night (Cooper, 2007).

Will practice activities negatively affect students' motivation? Aren't practice activities the same as "drill and kill" instruction?

Although deliberate practice is often confused with rote learning, researchers emphasize that there is a difference between mere repetition and deliberate practice. For practice to be effective, appropriate instruction, guided practice, as well as descriptive and timely feedback must all be present.

Does practice with "authentic" problems increase learning?

Due to their relevance, "authentic" problems or "real-life" problems may motivate students. However, the positive effect of practice is only realized when teachers provide instructional supports that address the limitations of students' working memories (Anderson, Reder, & Simon, 1996, 2000; Sweller, van Merrienboer, & Paas, 1998; van Merrienboer, Kirschner, & Kester, 2003). If there is cognitive overload and the working memory is taxed beyond its capacity, students will lose motivation even if a problem is highly relevant to them.

Although "authentic" practice problems sound like they would motivate students with their real-world context; they may also include too many variables at the same time. Students' working memories are thus required to manage too many bits of information, and many of these bits may not be directly involved with the construction of the desired schema (Sweller & Chandler, 1994).

Is there such a thing as too much practice?

Merely repeating a task will not automatically improve performance. Deliberate practice is most effective when it involves intense concentration, rehearsal and reflection. For that reason, students are more likely to benefit from frequent, short practice sessions than from long "cramming" sessions. Teachers can foster this meta-cognitive learning process by providing students with frequent opportunities to discuss their problem-solving strategies (National Research Council, 2005).

Even in early grades when students are acquiring foundational knowledge, practice should not be confused with rote learning. For example, phonics instruction is most effective when it is practiced alongside more complex skills like identifying main ideas in stories (National Institute of Child Health and Human Development, 2000).

Does practice work for all academic subjects?

Practice is correlated with student achievement across all developmental levels and across all subjects. NICHD's (2000) analysis of strategies for reading instruction suggests that several kinds of practice activities are beneficial to students. Phonemic awareness practice, phonics practice and read-aloud practice all showed significant positive effects on student achievement in the early grades. Teachers should always keep long-term goals in mind when they are designing practice activities. The ultimate purpose of phonics instruction is not for students to identify phonemes, but rather, to improve their reading comprehension. The goal of practice is to transfer acquired skills to new and more complex problems. Therefore, practice activities should always be designed with that transfer process in mind.

Studies in mathematics education show that practice is effective when teachers design appropriate practice problems, distribute them over time, and provide students with sufficient feedback. Practice is ineffective when it is not appropriately designed, not well distributed, and when adequate feedback is not provided.

Deliberate practice is also effective in learning complex skills from musical fluency to athletic expertise.

When does the strategy work?

All students benefit from well-designed, developmentally-appropriate deliberate practice activities. A meta-analysis (Macnamara, Hambrick, & Oswald, 2014) showed that the effects of deliberate practice are robust for games, music and sports, and modestly effective in education.

Deliberate practice can also provide a bridge over the gaps that exist between different achievement levels. Achievement gaps often exist because of unequal opportunities for students to engage in appropriate deliberate practice rather than unequal learning abilities. As children grow older, they become better able to benefit from instruction on appropriate strategies like rehearsal, reflection and "chunking" information.

Special populations benefit from practice activities that are designed to meet their needs (Chapman, & Mudar, 2014; Nunes, Barros, Evans, & Burman, 2014; Rose, Cundick, & Higbee, 1983). For example, research on children with language processing problems suggests that their difficulties are due to sensory perception rather than an inability to learn. One reason that language-learning impaired students have difficulty learning to read is that their phonemic recognition and spatial discrimination perceptions are impaired. Appropriate practice activities have been shown to help these students compensate for their difficulties (Merzenich et al., 1996). Cooper's (2001) examination of homework practice suggests that students with learning disabilities benefit most from short, skill-reinforcing activities that are carefully monitored (see also Marzano & Pickering, 2007).

Description of research on the use of practice activities with children with learning disabilities

An extensive meta-analysis of interventions for students with learning disabilities found that practice-drill-review instructional strategies were generally effective across academic subjects (Swanson, Hoskyn, & Lee, 1999). Another meta-analysis of inclusion settings found that time-on-task correlated with student achievement across subject areas (Brophy & Good, 1986). Therefore, practice activities appear to be a key factor in student achievement across grade levels, skill levels and academic domains.

In summary, well-designed practice activities result from careful planning where teachers:

Model problem-solving processes.

Design partially-completed examples on which students can practice.

Sequence activities logically.

Space practice activities appropriately.

Monitor student practice providing guidance and feedback.

Is practice effective across the age span?

Children grow more strategic as they get older. Younger children are less strategic - are less likely to rehearse, practice, or chunk spontaneously or to know how to do these things well. They are also less likely to monitor their own knowledge or to use metacognitive strategies. Younger children are less likely than older children to know what they need to rehearse or practice more. Therefore, teachers of younger children should introduce them to strategies such as rehearsal and practice, and in this way can help students improve their learning.

Deliberate practice is effective across all school age levels. Fundamental practice skills are more appropriate for earlier grades than it is for later grades. Teachers can focus younger students on the skills they will need later when they tackle more complex tasks. For example, phonemic awareness instruction is more effective for preschool students than for older elementary school students (NICHD, 2000), but it remains a skill that is very useful in later grades.

Teachers should design developmentally appropriate practice problems for students. Students' memories and attention spans develop with age (Gomez-Perez & Ostrosky-Solis, 2006; Lechuga, Moreno, Pelegrina, Gomez-Ariza, & Bajo, 2006). In general, older students have greater attention spans and greater memory capacity than younger students. This may account for developmental differences seen in the benefits of homework (Cooper, 2001; Muhlenbrook, Cooper, Nye, & Lindsay, 1999) and age differences in the amount of practice that learners engage in outside the classroom (Ericsson et al., 1993). Teachers should plan the type and amount of practice students are expected to do with these developmental differences in mind.

Research on expert performance shows that experts increase the amount of deliberate practice they engage in over time. For example, research by Ericsson and colleagues (1993) on expert violinists revealed that in early childhood they practiced no more than five hours per week. However, by their early twenties, they practiced around thirty hours per week. Because deliberate practice is so taxing, it should be balanced with sufficient periods of rest. Younger learners tire more quickly and lose their motivation to persist if they are not allowed sufficient rest (Ericsson et al., 1993; NICHD, 2000).

Elementary

Early elementary students benefit little or not at all from homework (Campitelli & Gobet, 2011; Cooper, 2001; Halford, Maybery, & Bain, 1986).

Expert violinists practiced fewer than 5 hours per week at the early childhood stage (Ericsson et al., 1993; Macnamara et al., 2014).

Research supports the idea that practice can help elementary students overcome processing deficits (Merzenich et al., 1996).

Practice with phonemic awareness has been shown to have a positive effect on reading outcomes in elementary readers through 6th grade. Effects were not as strong for disabled readers as they were for at-risk and normally progressing readers. The effects of phonemic-awareness instruction were strongest when it was provided in earlier grades (especially pre-K and kindergarten), in small group settings, in shorter training programs and to English-speaking students (NICHD, 2000).

Research suggests that systematic phonics instruction helps students learning to read. The effects of systematic phonics instruction were greater when it was provided in earlier grades (especially kindergarten and 1st grade) (Dahlin, 2011; Gersten, Fuchs, Williams, & Baker, 2001; NICHD, 2000).

A meta-analysis of intervention strategies for students with learning disabilities found that phonics instruction positively affects development of vocabulary, although the results on comprehension were unclear (Swanson et al., 1999). (The mean age for the study participants was 11; 78% of the studies targeted 9-14 year age range.).

Research suggests that repeated and guided-repeated oral reading strategies have a positive effect on reading performance through grade four, especially for non-impaired readers (Dahlin, 2011; Gersten, et al., 2001; Rose et al., 1983).

Swanson et al.'s (1999) meta-analysis suggests that "the teaching of whole language without due attention to decoding places LD children at greater risk than the use of more traditional programs" (p. 254).

Vocabulary instruction (both explicit and implicit) has a positive effect on vocabulary acquisition. Research indicates that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that reading comprehension strategy instruction (e.g., cognitive and meta-cognitive strategies) has a positive effect on reading comprehension and memory in grades 3-6. The effects were greater when strategy instruction was more intensive and when students were instructed in multiple strategies (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

Middle School

Middle school students may benefit from one to two hours of homework per night (Cooper, 2001; Campitelli & Gobet, 2011).

Research suggests that partial-task practice problems are more effective than whole-task practice problems for some 13 year-old math students. Partial-task practice lowered the processing demands on working memory for all students, but it only increased learning for students with low prior knowledge. Students with high prior knowledge benefited more from whole-task practice (Ayres, 2006).

Research suggests that when modeling problem-solving strategies, the use of worked examples is beneficial for middle school students' writing performance. As with Ayres' (2006) study, however, the positive effects were limited to low-performing students. The results suggested that "low-level" writers benefited from worked-example practice problems, while "high-level" writers benefited from "goal-free" practice problems.

Research suggests that the use of repeated and guided-repeated oral reading strategies positively affect students' reading performance. This is especially true for students with reading problems (NICHD, 2000).

Programs aimed at encouraging students to read more (e.g., self-selected, silent reading) yielded no significant positive effects on reading achievement (NICHD, 2000).

Swanson et al.'s (1999) meta-analysis suggests that "the teaching of whole language without due attention to decoding places LD children at greater risk than the use of more traditional programs" (p. 254).

Results that support the positive effects of vocabulary instruction (both explicit and implicit) on vocabulary acquisition indicate that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that reading-comprehension-strategy instruction (e.g., cognitive and meta-cognitive strategies) has a positive effect on reading comprehension and memory in grades 3-6. The effects were greater when strategy instruction was more intensive and when students were instructed on multiple strategies (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

High School

High school students appear to benefit from at least two hours of homework per night, (Campitelli & Gobet, 2011; Cooper, 2001).

Students may benefit from more practice with the transfer of component skills than from practicing whole-task transfer (Pollock, Chandler, & Sweller, 2002). Examples worked out in advance for students were more effective for algebra problem solving transfer than were conventional problems for 9th and 11th grade students (Sweller & Cooper, 1985).

Repeated and guided-repeated oral reading strategies positively affect reading performance. This is especially true for high school students with reading problems (NICHD, 2000).

Programs aimed at encouraging students to read more (e.g., self-selected, silent reading) yielded no significant positive effects on reading achievement (NICHD, 2000).

Although research supports a positive effect of vocabulary instruction (both explicit and implicit) on vocabulary acquisition in grades 9-11, few studies have been conducted at that level. Results that do exist suggest that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

Where can teachers get more information?

Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51(4), 355-368. http://dx.doi.org/10.1037/0003-066X.51.4.355

Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school. Washington, D.C.: National Academy Press. ISBN 0-309-07036-8

Carver, S. M. & Klahr, D. (Eds.). (2001). Cognition and instruction: Twenty-five years of progress. Mahwah, NJ: Erlbaum.

# data[].attributes.attachment_link.title
Practice for knowledge acquisition (not drill and kill)

# data[].attributes.attachment_link.description
Researchers who have investigated expert and novice performance have uncovered important distinctions between deliberate practice and other activities, such as work, play and rote repetition.

# data[].attributes.attachment_link.readable_text
Learning how to learn cannot be left to students. It must be taught. ( Gall et al., 1990 )

Imagine yourself as the instructor of an introductory undergraduate biology course. Two students from your course independently visit your office the week after the first exam. Both students are biology majors. Both regularly attend class and submit their assignments on time. Both appear to be eager, dedicated, and genuine students who want to learn biology. During each of their office hours visits, you ask them to share how they prepared for the first exam. Their stories are strikingly different (inspired by Ertmer and Newby, 1996 ).

During office hours, Josephina expresses that she was happy the exam was on a Monday, because she had a lot of time to prepare the previous weekend. She shares that she started studying after work on Saturday evening and did not go out with friends that night. When queried, she also shares that she reread all of the assigned textbook material and made flashcards of the bold words in the text. She feels that she should have done well on the test, because she studied all Saturday night and all day on Sunday. She feels that she did everything she could do to prepare. That said, she is worried about what her grade will be, and she wants you to know that she studied really hard, so she should get a good grade on the exam.

Later in the week, Maya visits your office. When asked how she prepared for the first exam, she explains that she has regularly reviewed the PowerPoint slides each evening after class since the beginning of the term 4 weeks ago. She also read the assigned textbook pages weekly, but expresses that she spent most of her time comparing the ideas in the PowerPoint slides with the information in the textbook to see how they were similar and different. She found several places in which things seemed not to agree, which confused her. She kept a running list of these confusions each week. When you ask what she did with these confusions, she shares that she brought them to her weekly study group with peers from her course lab section. There, she says, she got most of her questions answered and lots of her confusions cleared up. She has come to office hours to ask you about a couple of things that she did not figure out before the exam that she thinks she probably missed. She is not too worried about her score on the exam, because most of the material related to problems and concepts that she felt had been thinking about a lot.

So, what is different about Josephina and Maya? No doubt many things, including their educational histories, their personalities, and more. However, one key difference in their approach to their studies is evident from their stories. They appear to be strikingly different in knowing how to learn, being able to monitor their own understanding, being reflective about what they understand and do not understand, and being able to strategize about how to resolve their confusions. They are different in their ability to use metacognitive approaches in their learning.

INTRODUCING METACOGNITION

The importance of metacognition in the process of learning is an old idea that can be traced from Socrates' questioning methods to Dewey's twentieth-century stance that we learn more from reflecting on our experiences than from the actual experiences themselves ( Dewey, 1933 ). What is more recent is the coining of the term "metacognition" and the emergence of a metacognition research field in the last four decades. Credited to developmental psychologist John Flavell in a publication from the 1970s, metacognition is used in different disciplines in different ways, and a common, succinct definition appears to be elusive in the literature. Below is an excerpt from Flavell's original writing, as well as several additional definitions and conceptualizations from different sources:

Metacognition refers to one's knowledge concerning one's own cognitive processes or anything related to them, e.g., the learning-relevant properties of information or data. For example, I am engaging in metacognition if I notice that I am having more trouble learning A than B; if it strikes me that I should double check C before accepting it as fact. (Flavell, 1976)

Metacognition also includes self-regulation-the ability to orchestrate one's learning: to plan, monitor success, and correct errors when appropriate-all necessary for effective intentional learning... Metacognition also refers to the ability to reflect on one's own performance. (National Research Council, 2000)

These multiple perspectives on what metacognition might entail-which expand on Flavell's original definition to include an emphasis on planning, monitoring, and evaluating one's own learning processes-are likely related to the relative youth of the metacognition research field and the associated growing pains of an emerging discipline ( Flavell, 1979 Schraw, 1998 Zohar, 2009 Schraw et al., 2006 Schraw et al., 2006 Bandura, 1977 ). Because the goal of this feature is to translate ideas from other disciplines that may have immediate, practical relevance for biology education, I will leave these intriguing overlaps and areas of active inquiry for the exploration of interested readers. ) and self-efficacy (an individual's conceptualization of his or her own competency; ). In addition, there are complex overlaps between metacognition research and other research arenas focused on self-regulated learning (an individual's ability to take control of his or her learning; ; ). Delineation of distinct aspects of metacognition, development of tools for measuring these aspects, and strategies for teaching them to students are all active areas of inquiry among researchers across several social science disciplines ( ;

So, let us reconsider Josephina and Maya. Their stories are likely familiar to anyone who has taught college biology even for a short period of time. And the reactions from faculty to these two kinds of students might be briefly summarized as exasperation with Josephina and elation with Maya. Faculty are often perplexed by students like Josephina, who do not seem to have mastered learning how to learn, and some faculty will assert that it is their job to "teach biology, not study strategies." Yet metacognition, which represents more than just study skills, has been linked to improving thinking skills and promoting conceptual change in younger students ( Nickerson et al., 1985 White and Gunstone, 1989 Georghiades, 2000 Adey and Shayer, 1993 Kuhn and Pearsall, 1998 Kruger, 1999 Dunning et al., 2003 ). But there remains much to be learned about the influence of metacognition on learning, especially among college-age students and within particular disciplinary contexts (e.g., biology vs. physics vs. music theory). So, how can we as biology educators use what is currently known about metacognition to our and our students' advantage to support biology teaching and learning? What could integrating student metacognition into a college biology course look like? And how might active learning look different with more emphasis on metacognition? ; ). Evidence indicates that individuals with poor metacognitive skills perform less well academically than peers ( ; ). Additionally, there is evidence that improved metacognition is associated with promoting young students' overall academic success ( ; ;

USING METACOGNITION TO HELP STUDENTS LEARN TO THINK LIKE BIOLOGISTS

With the recent publication of the 2011 American Association for the Advancement of Science (AAAS) report, Vision and Change for Undergraduate Biology Education, and the 2012 President's Council of Advisors on Science and Technology (PCAST) report, Engage to Excel, considerable attention is being paid to transforming the learning experiences of undergraduate students in the sciences ( AAAS, 2011 PCAST, 2012 ). An example of our collective aspirations as a biology education community for what we want students to be able to do at the conclusion of their undergraduate biology education is stated as follows in ; Vision and Change:

Biology in the 21st century requires that undergraduates learn how to integrate concepts across levels of organization and complexity and to synthesize and analyze information that connects conceptual domains.

This aspiration can be approximated by the assertion that we want undergraduate learning experiences to help students learn to think like biologists. Promoting student metacognition-teaching students to think about how they are thinking about biology and how they approach learning about biology-would seem to be a useful strategy in striving to reach these kinds of goals for students ( NRC, 2000 D'Avanzo, 2003 Crowe et al., 2008 ). Below, I describe potential approaches to increasing attention to metacognition in undergraduate biology classrooms, including: 1) explicitly teaching students metacognitive strategies, and 2) more generally building a classroom culture grounded in metacognitive strategies by modifying what we are already doing. ; ;

EXPLICITLY TEACHING STUDENTS METACOGNITIVE STRATEGIES IN BIOLOGY COURSES

Teaching students to use metacognition to understand how they are thinking about biology provides an important step on the path to thinking like a biologist ( AAAS, 2011 ). In the context of undergraduate biology teaching, this need not take much time, and it is an effort that is in the service of learners and learning, as well as teachers and teaching. Table 1 provides examples of self-questions that metacognitive undergraduate biology learners might ask in the process of planning, monitoring, and evaluating their learning in the context of a single class session, a homework assignment, an exam, or an entire course. While this collection of questions by no means represents the entire landscape of what metacognition could involve, it does provide starting points for faculty who wish to talk with students explicitly about metacognitive strategies. These questions can be shared directly with students and/or embedded into particular assignments. Several examples of how these student self-questions can be explicitly used in teaching a biology course are considered below.

Table 1.

Class session

Active-learning task and/or homework assignment

Quiz or exam

* What strategies will I use to study (e.g., study groups, problem sets, evaluating text figures, challenging myself with practice quizzes, and/or going to office hours and review sessions)?
* How much time do I plan on studying? Over what period of time and for how long each time I sit down do I need to study?
* Which aspects of the course material should I spend more or less time on, based on my current understanding?

Overall course

* In what ways is the teaching in this course supportive of my learning? How could I maximize this?
* In what ways is the teaching in this course not supportive of my learning? How could I compensate for or change this?
* How interested am I in this course? How confident am I in my learning? What could I do to increase my interest and confidence?

Preassessments-Encouraging Students to Examine Their Current Thinking

The importance of instructors knowing what students are thinking about a topic prior to trying to teach them something new has been written about extensively. However, preassessment can also be helpful for the learner and is a wonderful opportunity for promoting metacognition among students. "What do I already know about this topic that could guide my learning?" is an example of a self-question that it at the core of most preassessments used by instructors. It takes no more than a few simple statements by an instructor to transform an existing preassessment prompt-be it a homework assignment, an index card, or a clicker question-into a metacognitive activity for students, directing them not only to complete the task as part of the course, but also to be metacognitive in doing so and to use the information given on the preassessment to help them begin thoughtful planning of how they might approach learning this new idea.

The Muddiest Point-Giving Students Practice in Identifying Confusions

Reflective Journals-Providing a Forum in Which Students Monitor Their Own Thinking

In the case of Josephina, one of the metacognitive strategies that she simply does not seem to possess is to be analytical about what did or did not work well for her in studying for the last exam, and to then use that information in preparing for future exams. Instructors can assign something as simple as a low-stakes, low-points writing assignment after a first exam, asking students to reflect and write a brief letter to their future selves covering: "What about my exam preparation worked well that I should remember to do next time? What did not work so well that I should not do next time or that I should change?" If an instructor assigns such writing, either in conjunction with an exam or as part of a specific reflective writing assignment, he or she is explicitly giving students a strategy for developing metacognitive approaches, as well as practice using that approach in the context of their disciplinary course. To extend this, instructors can also assign a reread of this writing before the next exam and a second writing assignment on how well students followed their own advice to themselves. In addition, students can be asked to share their strategies with fellow students and to identify at least two new exam preparation strategies used by their peers. If such writing about their metacognitive, thinking, and learning strategies is done regularly, students can create a reflective/biologist journal and can be rewarded with some form of credit, as for other course activities.

BUILDING A BIOLOGY CLASSROOM CULTURE GROUNDED IN METACOGNITION

While using specific individual assignments to teach students metacognitive strategies is one explicit approach, there are more subtle ways that metacognition can be integrated into the fabric of any course and become part of the everyday language of both teacher and students. This is particularly useful in helping students to become aware of when it is appropriate to apply their own metacognitive strategies-for example, identifying confusions-that they may have learned through previous assignments. The point at which students have both learned metacognitive strategies and have become aware of when to apply these strategies is hypothetically the point at which they have matured into lifelong learners within their disciplines. Below are several starting points for thinking about how the language and habit of metacognition could become part of everyday classroom culture. In addition, provides some sample prompts that can be used to add a metacognitive aspect to learning activities that may already be in use in your teaching, such as pair discussions after clicker questions, a variety of types of homework assignments, and the ever-present exams and quizzes. Simply adding one additional question or using some of the language in the table in making the assignment can demonstrate to students the value you as an instructor place on their efforts to develop metacognitive habits of mind as a biology student. Below are four general ways that instructors might build a classroom culture that promotes metacognition and conveys that culture to students.

Table 2.

Pair discussion after a clicker question

Active-learning tasks and/or homework assignments (e.g., case studies, concept maps, problem sets)

Preparation for quizzes or exams

Share how you thought about what the question was asking.
Share the process you used to arrive at an answer you wanted to choose.
What was your main reason for choosing your answer, and what were the main reasons you did not choose each of the other answers?
How did your ideas compare with your neighbor's ideas?
What was most confusing to you about this question?
How confident are you in your answer? Why? What else would you need to know to increase your confidence?

Integrating Reflection into Credited Course Work

Integrating reflection into any course can be achieved by a relatively simple tweaking of existing course assignments. In addition to having students respond to homework questions or solve problems, instructors need only add one or more questions that push students to consider their own thinking (see ). These questions can be as simple as "What was most challenging to you about this assignment?" to "What questions arose during your work on this assignment that you had not considered before?" The instructor's decision to make these kinds of questions part of an assignment-and part of the grading scheme for the assignment-can prompt students to bring a more metacognitive stance to their everyday coursework. Similarly, for assignments that involve diagramming or concept mapping, instructors can encourage (or require) students to indicate in their work what questions arose and which concepts they found most confusing. In this more subtle approach, what changes is not the assignment itself, but the nature of the assignment.

Metacognitive Modeling by the Instructor for Students

As a professional, practicing biologist, it can be almost impossible to remember a time when you did not think biologically, to remember the nature of your own biological confusions as a student, and to be able to offer up self-reflective examples of your own transitions in thinking for your students. As researchers, we think metacognitively all the time, reflecting on our current understanding of our research system, what the burning questions are, and how our thinking has changed over the years with new data. Showing students explicitly how you, as a biologist, think procedurally in solving a problem-how you start, how you decide what to do first and then next, how you check your work, how you know when you are done-is one example of metacognitive modeling. A teaching colleague of mine shared that he was perplexed as to why students were unable to make accurate predictions about the proportions of different phenotypes in the offspring from a specific cross, as required in response to a homework question. But when he asked all of the students to do a problem in class one day, he noticed that only a minority of them were drawing a Punnett square. When he asked several students why they did not have pencil and paper out, they said they thought they should just be able to do it mentally. My colleague then went to the stage and proceeded to metacognitively present how he thinks through a problem similar to their homework question. His first step-always, even as a practiced biologist-is to get out a pencil and a piece of paper and to translate the problem into a Punnett square! Showing students how we think about a biology concept, or how biologists more generally have thought about a concept over the history of biology, illustrates how the entire field of biology has changed its collective understanding. For example, what biologists think about how plants grow and build mass has undergone multiple revisions over time. In addition, our collective understanding of how genetic information is transferred from parent to offspring across all species is ripe for analysis of how "thinking like a biologist" looked different in Mendel's time versus the modern era.

ON INSTRUCTOR METACOGNITION AND BIOLOGY TEACHING

We began this exploration of metacognition by considering two contrasting students-Josephina and Maya. Now, imagine that you have the opportunity to talk to two of your biology faculty colleagues about their approaches to teaching. Both are research-active, full professors in biology. Both regularly teach introductory courses for biology majors. Both appear to be genuinely eager to help their students succeed in their biology courses. In your conversation with each of them, you begin by asking them about how their teaching is going this semester. In addition, you ask each of them how they prepare for class each week. Their stories are strikingly different.

Kara expresses dissatisfaction with the students in her upper-division biology course. She thinks that the students are getting worse every year, even though she works harder and harder to bring them more cutting-edge research in the field. She shares that she has committed to updating all of her PowerPoint lectures this semester, even though she already has tenure, and has often stayed up very late the night before to make sure that her slides are really clear. When queried about how she gets insights into how students are thinking, she shares that she has added an additional exam between the mid-term and the final to motivate students to keep up with the reading. She is also very frustrated that no students come to her office hours. She feels like she is doing everything she can to help students understand the material, but they do not seem to be willing to work as hard in a course as she did when she was an undergraduate. She is worried about her student evaluation scores, which have declined over the years, and she thinks it is not fair to be evaluated by students who do not seem to care about their learning.

In contrast, another faculty colleague, Aerial, seeks your input on a new series of clicker questions she has developed as the basis of a classroom activity she is trying out with her students the next day. From prior experience, she knows that few students are able to connect the ideas of photosynthesis with those of climate change, and she wants to start her new unit on transformation of matter and energy with an assessment question that will really get students thinking about their prior ideas. She has changed this unit of her course each time she has taught it over the last several years, based on all the information she has collected from students about their ideas on the topic. She is aware that the more she knows about how students are thinking, the more ideas she has about new things to try in her teaching. She also shares that many of the homework writing assignments students have already submitted before the midnight deadline show that they have identified exactly the confusions she wants to alert them to tomorrow! When you ask her if she is concerned about how students will react to her new clicker-based classroom activity, she is not too worried. She regularly shares with students her own rationale for why she has developed a particular learning activity for them and gets their feedback on it through an index card or homework assignments so that she will have insights for the next time she teaches the same activity.

So, what is different about Kara and Aerial? No doubt many things, but one key difference is their ability as faculty members to be metacognitive about their teaching. Similar to the contrast between Josephina and Maya's abilities to be metacognitive about their learning, there is a difference in the extent to which each of these faculty members is thinking about how they think about their teaching. While instructors no doubt bring a deeply metacognitive approach to their field of scientific research, cultivating a metacognitive lens toward one's teaching does not appear to automatically or easily transfer. However, developing a metacognitive stance toward one's own teaching-thinking about how you think about teaching-can be a wonderfully natural entry point into iteratively changing one's own teaching practice. Self-analysis about one's own ideas about teaching could include: What assumptions do I hold about students? To what extent do I have evidence for those assumptions? Why do I make the instructional decisions that I make? What do I know about teaching? What would I like to learn? What am I confused about? These analyses can also become more specific to particular granularities, ranging from an individual class session to the scope of an entire course. provides some starting points in the form of sample self-questions for faculty that may aid them in becoming more metacognitive about their teaching.

Table 3.

Class session

* What do I notice about how students are behaving during this class session? Why do I think this is happening?
* What language or active-learning strategies am I using that appear to be facilitating learning? impeding learning?
* How is the pace of the class going? What could I do right now to improve the class session?

* How do I think today's class session went? Why do I think that? What evidence do I have?
* How did the ideas of today's class session relate to previous class sessions? To what extent do I think students saw those connections?
* How will what I think about how today's class session went influence my preparations for next time?

Overall course

* Why do I think it's important for students pursuing a variety of careers to learn the ideas in my course? What are my assumptions?
* How does success in this course relate to my students' career goals? How might I reveal these connections to them?
* What do I want students to be able to do by the end of this course? Still be able to do 5 yr later?

* In what ways am I effectively reaching my goals for students through my teaching? How could I expand on these successful strategies?
* In what ways is my approach to teaching in this course not helping students learn? How could I change my teaching strategies to address this?
* How is my approach to teaching this course different from last time I taught it? Why?

Postscript 1: Using Metacognition to Make the Most of Active Learning-Learning from History

As stated above, attention to improving undergraduate biology education is high at present, and active-learning strategies are a central approach among suggested changes ( AAAS, 2011 Ebert-May et al., 2011 Tanner, 2011 ). Metacognition is not generally central, or even included, in discussions and articles about active learning. In fact, the term "active learning" is prominent and often used in the AAAS, 2011 ). One possible difference in the effectiveness of active-learning pedagogies in the hands of different instructors may lie in the extent to which these instructors consider student metacognition when they implement active-learning strategies. ; ). However, what different instructors mean by active learning and what active learning actually looks like in a different classrooms has not been well documented or investigated ( Vision and Change for Undergraduate Biology Education report, whereas "metacognition" does not make an appearance (

During the 1980s, K-12 science education experienced a period of intense focus on hands-on learning, which might be considered parallel to the recent rise in emphasis on active learning in undergraduate biology education. However, there was a general dissatisfaction, with reports that K-12 students were doing a lot of activities but not necessarily very much thinking. The hands-on era in K-12 science education was followed a shift in both the language and emphasis in policy documents to minds-on and inquiry-based learning in the 1990s ( National Research Council, 1996 ). One aspect of this shift in emphasis in K-12 science education reform was an increased emphasis on student metacognition, students thinking about what they were thinking while they were doing, as opposed to just doing hands-on, active things without the thinking. As such, attention to student metacognition may be especially salient at this moment in the history of the undergraduate biology education revolution. To avoid repeating the trajectory of K-12 science education reform, explicit attention to integrating metacognition into undergraduate biology classrooms could help keep a focus on the learning part of active learning.

Postscript 2: On Thinking about Your Thinking about This Article...

Why, in the first place, did you choose to read this feature? Was it the title? The term "metacognition"? What did you already know or think about metacognition before reading this feature? How, if at all, have your ideas changed? What in this article was most intriguing to you? What are you thinking about in terms of how you might use those ideas? What in the article was most confusing? How do you plan to follow up on that to clarify your ideas and learn more? Will you? Why or why not? As you read, what, if anything, came to mind that you already do with your students that may promote their use of metacognitive strategies? Are you thinking about how explicit you are with your students about the thinking strategies and processes that you yourself use as a practicing biologist? What is the most important thought you had in reading this article? Did it even have anything to do with metacognition?

# data[].attributes.attachment_link.description
Learning how to learn cannot be left to students. It must be taught. ( Gall et al., 1990 ) Imagine yourself as the instructor of an introductory undergraduate biology course. Two students from your course independently visit your office the week after the first exam. Both students are biology majors.

# data[].attributes.attachment_link.readable_text
Practice is a physical activity, of course, but it's also hard mental work - if you're doing it right. A new video published by TED Ed gets down to the scientific nitty-gritty of what good practice looks like, and what it does to your brain. (Think axons and myelin, not "muscle memory" - muscles don't have "memory.")

As Annie Bosler and Don Greene, the creators of this TED Ed lesson, point out, this advice can apply to everything from music to sports. They define effective practice as "consistent, intensely focused and target[ing] content or weaknesses that lie at the edge of one's current abilities." That's another way of saying: Don't waste your time practicing the stuff you already know, just to fill up those minutes.

More of their specific advice, with each point bolstered by research:

"Focus at the task on hand." Shut off all those digital distractions. No excuses.

"Start out slowly, or in slow motion. Coordination is built with repetitions." Get it right at a slow pace and then work on increasing your speed while still playing the music correctly.

"Frequent repetition with allotted breaks are common practice habits of elite performers." Do what many pros do: split your practice time into smaller, super-concentrated chunks, working multiple times a day.

"Practice in your brain, in vivid detail." Visualize playing your music without actually playing it. Put yourself through the music, note by note. Imagine what it feels like to press that key, or take that breath, every step of the way.

Of course, their advice about practicing isn't new; quite a bit of it has been floating around for some time now, like in a series of posts published here on Deceptive Cadence a few years ago. But having a better understanding why and how it works is inspiring - and helps you reinforce good habits.

# data[].attributes.attachment_link.title
How To Practice Effectively, According To Science

# data[].attributes.attachment_link.description
Want to boost those neural pathways? TED Ed offers practical suggestions: Practice in concentrated bursts, work through passages slooowly -- and step away from Facebook.

# data[].attributes.attachment_link.readable_text
Practice is a physical activity, of course, but it's also hard mental work - if you're doing it right. A new video published by TED Ed gets down to the scientific nitty-gritty of what good practice looks like, and what it does to your brain. (Think axons and myelin, not "muscle memory" - muscles don't have "memory.")

As Annie Bosler and Don Greene, the creators of this TED Ed lesson, point out, this advice can apply to everything from music to sports. They define effective practice as "consistent, intensely focused and target[ing] content or weaknesses that lie at the edge of one's current abilities." That's another way of saying: Don't waste your time practicing the stuff you already know, just to fill up those minutes.

More of their specific advice, with each point bolstered by research:

"Focus at the task on hand." Shut off all those digital distractions. No excuses.

"Start out slowly, or in slow motion. Coordination is built with repetitions." Get it right at a slow pace and then work on increasing your speed while still playing the music correctly.

"Frequent repetition with allotted breaks are common practice habits of elite performers." Do what many pros do: split your practice time into smaller, super-concentrated chunks, working multiple times a day.

"Practice in your brain, in vivid detail." Visualize playing your music without actually playing it. Put yourself through the music, note by note. Imagine what it feels like to press that key, or take that breath, every step of the way.

Of course, their advice about practicing isn't new; quite a bit of it has been floating around for some time now, like in a series of posts published here on Deceptive Cadence a few years ago. But having a better understanding why and how it works is inspiring - and helps you reinforce good habits.

# data[].attributes.attachment_link.title
How To Practice Effectively, According To Science

# data[].attributes.attachment_link.description
Want to boost those neural pathways? TED Ed offers practical suggestions: Practice in concentrated bursts, work through passages slooowly -- and step away from Facebook.

# data[].attributes.attachment_link.title
CBC.ca - Interactive: Map of the human brain

# data[].attributes.attachment_link.description
Map of the human brain: A region-by-region exploration of how the brain works - Its functions and symptoms of damage

# data[].attributes.attachment_link.title
Microsoft HoloLens | Mixed Reality Technology for Business

# data[].attributes.attachment_link.description
Introducing HoloLens 2, an untethered mixed reality headset that's designed to help you solve real business problems today using intelligent apps and solutions.

# data[].attributes.body
w

# data[].attributes.attachment_link.readable_text
Low-stakes assignments are forms of evaluation that do not heavily impact students' final grades or other educational outcomes. The purpose of low-stakes assignments is to provide students with an indication of their performance while taking a course and give students an opportunity to improve their performance prior to receiving a final grade, either on an assignment or in a course.

As Vincent Tinto writes in Completing College: Rethinking Institutional Action (2012), "To be effective, assessments must be frequent, early, and formative." At colleges and universities recognized by the National Survey on Student Engagement for their success in promoting student's active engagement in their learning: "Feedback from faculty to students is timely and frequent, as documented both by NSSE data and by interviews with students and faculty members" (Kuh, et al. 2010).

Low-stakes assignments tend to work best when they generate formative feedback regarding where students are in the course, what they are doing well, and where they may need development to ultimately succeed in the class. At DePaul, there is a general expectation that students will be given feedback early in the quarter or term, and low-stakes assignments are a powerful method of doing so.

For students in their first year, whether as freshmen or transfers, such feedback is especially important in order to help them understand the expectations at DePaul. Early feedback also enables faculty to use DePaul's BlueStar system to identify students who may need additional assistance and share that information with the students and their academic advisors.

Benefits of Low-Stakes Assignments

Low-stakes assignments

Give students a realistic idea of their performance early in the term, enabling them to seek appropriate resources as needed

Open up lines of communication between students and their instructors, and may increase students' willingness to ask for help

Provide feedback for instructors on how well students are absorbing information and progressing in their skill development

Allow instructors to direct students to resources if they need further assistance or support

Give students an opportunity to be active participants in the evaluation of their own learning

Increase the likelihood that students will attend class and be active and engaged

Low Stakes-Assignments in Online and Flex Modality Courses

While all classes can benefit from frequent low-stakes assignments, it's especially important in online and Flex modalities. In a face-to-face classroom, instructors may assess student learning in informal ways using nonverbal cues-a puzzled look or an affirming nod, for example. In a online and Flex courses, instructors may have more difficulty picking up these cues from students, especially if they don't always have their cameras on or you're not meeting synchronously. In Flex classes, it can also be more challenging to pick up on nonverbal cues among in-person students if also trying to monitor engagement and participation among remote students at the same time. ​​

D2L Tools for Low-Stakes Assignments

​D2L tools will help you to implement low-stakes assignments in all types of courses and course modalities.

Quizzes are often used for multiple-choice or other objective question types because they can be graded automatically, allowing students to get feedback immediately. For low-stakes assignments, you may want to allow students to review the questions and their answers after they take the quiz. You can set up Submission Views to allow for this. Instructors can also view quiz statistics to see if the class is struggling with a particular concept and review that topic with them.

Discussions

Discussions allow students to share short pieces of writing or other media with you and their classmates. They work well for sharing rough drafts or other early-stage components of larger projects for peer review or for certain journaling assignments.

Submissions

Submission folders allow students to submit work privately to you. You may be used to using Submissions for major assignments like research papers. For shorter, less formal pieces of writing, you can change the Submission Type to "Text" to allow students to type their response directly into D2L rather than uploading a file from their computer.

Examples of Low-Stakes Assignments

Though given less weight, low-stakes assignments may be similar in type and kind to high-stakes assignments: they tend to reflect the kind of work students are going to be expected to do for a final exam, paper, or other summative project.

Components of a Larger Project

When assigning students a writing or research project, break down the elements of the project and use one or more as a low-stakes assignment. Require students to submit their works-in-progress so that they can receive early written feedback and a small grade, which could consist simply of a check or check-minus. Any one (or more) of the following elements could be collected and used as a low-stakes assignment:

Prospectus or proposal

Abstract

Thesis statement

Outline

Annotated bibliography

Specific sections of the final project (e.g., introduction, methods, lit. review)

Early-stage drafts of a paper

Early Drafts and Peer Review

Midway through a writing project, have students bring a full or partial draft of their paper to class and then exchange feedback with a peer. Students will receive valuable feedback that they can use to revise their work.

Try providing students with a rubric to help them give their peers targeted, assignment-specific feedback. Also, consider inviting Writing Center tutors to your class to model how peer review can be conducted effectively.

Mid-Project/Quarter Conferences

Around midterm or during the planning stages of a major course project, ask students to meet with you for conferences. If the class is too large for you to meet with each student individually, assign students to meet with you in groups, or one-on-one with their TA. The conference time might be dedicated to discussing the students' progress towards course goals or providing feedback on a particular project.

To get the most out of your conference time, ask students to complete and bring with them a self-assessment form or project proposal. Alternatively, ask students to write down one question they have about the course, content covered in class, or an assignment they are currently working on. Having a document to reference will keep the conversation on track and help put both you and your students at ease.

Group Work Planning and Reflection

When students are working in groups, require them to submit a statement outlining each group members' responsibilities and/or a timeline that measures their progress. Periodically throughout the group project, ask students to submit short reflections detailing their progress and any areas where they need support.

Weekly Quizzes

For a course where exams are the primary means of summative assessment, give students a quiz at the end of each week with questions based on content covered up to that point. Although the quiz might not count for credit (or might only count for a very small portion of the final grade), it will give students an idea of what they already learned and which concepts they need to spend more time with. Quizzes can be paper-based, conducted during class using Polling or posted online in D2L Quizzes.

Class Problem Solving

In a course where students learn new computational or mathematical concepts, have a problem posted on the board or screen at the start of each class, or in a collaborative document. Students can work individually, in pairs, or in small groups to find the solution. Spend part of class going over the problem as a big group, or review the problem in a short video.

Course Concept Journals

Consider having students keep a regular journal where they can engage with and apply course concepts. For example, in an Introduction to Political Science course, ask students to read the politics section of the New York Times and keep a weekly concept-application journal. For each entry, students should select one article that they read, summarize it, and show how the article demonstrates a theoretical concept discussed that week in class. Review students' journals every other week or so and give each entry brief feedback.

Reading Journals

In a course where students are required to do weekly readings, assign a reading journal. Entries might require students to summarize and respond to the source, or to answer a set of questions provided by the instructor. Students can submit their journal entries through D2L, by handing in hard copies every other week, or by posting them on a course blog.

Short Writing Assignments

Give students a prompt that corresponds to a class reading assignment, concept, or activity and have them turn in a short written response. Return the students' responses with your brief feedback, indicating whether the students are on track or not (a simple "check plus" or "check minus" could be used). In large classes where you might not have time to give individualized written feedback to each student, share and discuss one or two anonymous students responses at the next class meeting or in a D2L News item or weekly introduction.

Discussion Questions

Post open-ended questions designed to promote engagement with the current course content or an upcoming project or assignment. Invite students to ask questions and identify areas of confusion, and answer the questions posted by their peers. See Facilitating Discussions for additional suggestions.

Support for Low-Stakes Assignments at DePaul

University Center for Writing-based Learning (UCWbL)
Discuss how you can incorporate writing in a low-stakes assignment by contacting Matthew Pearson, Director of the UCWbL. You can also invite peer tutors to your classroom to demonstrate effective peer review before having your own students give feedback to one another.

University Libraries
If you're interested in using an element of a research project as a means of giving early feedback to students, connect with a university librarian. University librarians can offer feedback and resources for designing research projects for students.

Center for Teaching and Learning (CTL)
Have a question about integrating discussion forums in your classes? Not sure which platform might be best for setting up a course blog? Contact the CTL for help identifying and implementing a technology tool to help meet your goals.

Further Reading

Angelo, T., & Cross, K.P. (1993). Classroom assessment techniques. San Francisco: Jossey-Bass, Inc.

Bean, J. C. (1996). Engaging ideas: the professors guide to integrating writing,critical thinking and active learning in the classroom. San Francisco: Jossey-Bass Publishers.

Kuh, G. D., Kinzie, J., Schuh, J.S., and Whitt, E.J. (2010). Student success in college: Creating conditions that matter. San Francisco, CA: Jossey-Bass.

Lang, J. M. (2013). Cheating Lessons: Learning from Academic Dishonesty. Cambridge, MA: Harvard University Press.

Nilson, L. B. (2010). Teaching at its best: A research-based resource for college instructors. San Francisco: Jossey-Bass.

Tinto, Vincent. (2012). Completing college: Rethinking institutional action. Chicago, IL: University of Chicago Press.

Warnock, Scott. (2013). Frequent, low-stakes grading: Assessment for communication, confidence. Faculty Focus. Madison, WI: Magna Publications.

​

# data[].attributes.attachment_link.description
Low-stakes assignments are forms of evaluation that do not heavily impact students' final grades or other educational outcomes. The purpose of low-stakes assignments is to provide students with an indication of their performance while taking a course and give students an opportunity to improve their performance prior to receiving a final grade, either on an assignment or in a course.

# data[].attributes.attachment_link.readable_text
Cite this

Brabeck, M., & Jeffrey, J. (2015, March 9). Practice for knowledge acquisition (not drill and kill). American Psychological Association. https://www.apa.org/education-career/k12/practice-acquisition

Designing activities with the goal of transferring knowledge

It doesn't matter what subject you teach, differences in students performance are affected by how much they engage in deliberate practice. Researchers who have investigated expert and novice performance have uncovered important distinctions between deliberate practice and other activities, such as play or repetition.

Deliberate practice is not the same as rote repetition. Rote repetition - simply repeating a task - will not by itself improve performance. Deliberate practice involves attention, rehearsal and repetition and leads to new knowledge or skills that can later be developed into more complex knowledge and skills. Although other factors such as intelligence and motivation affect performance, practice is necessary if not sufficient for acquiring expertise (Campitelli & Gobet, 2011).

Define practice:

"Deliberate practice (DP) occurs when an individual intentionally repeats an activity in order to improve performance. The claim of the DP framework is that such behavior is necessary to achieve high levels of expert performance." (Campitelli & Gobet, 2011, p. 280).

"Deliberate practice consists of activities purposely designed to improve performance." (Gobet & Campitelli, 2007, p. 160).

Benefits of deliberate practice

Practice is important for teaching and learning in at least five ways:

1. Practice greatly increases the likelihood that students will permanently remember new information (Anderson, 2008).

2. Practice increases student facility or automaticity (learning to apply elements of knowledge automatically, without reflection). Automaticity is usually only achieved through extensive rehearsal and repetition. Automaticity frees up students cognitive resources to handle more challenging tasks (Brown & Bennett, 2002; Moors & De Houwer, 2006).

3. When students practice solving problems, they increase their ability to transfer practiced skills to new and more complex problems. This is true in childhood (Glover, Ronning, & Bruning, 1990) and adult years (Li, Schmiedek, Huxhold, Röcke, Smith, & Lindenberger, 2008).

4. Practice helps students acquire expertise in subject matter and, therefore, it helps to distinguish novices from experts in given subjects (Ericsson, Krampe, & Clemens, 1993)

5. Cognitive gains from practice often bring about motivation for more learning (Kalchman, Moss, & Case, 2001).

Teachers should think of practice not as rote repetition, but as deliberate, goal-directed rehearsal paired with reflection on problem-solving processes. For example, when teachers have students practice identifying phonemes, the ultimate goal is for students to read with fluency and comprehension. Although fluent reading may be too complex a task for beginning readers to tackle, the more manageable task of identifying phonemes may scaffold students learning to achieve the ultimate goal of reading. That is, teachers should always design practice activities with the goal of transferring knowledge to new and more complex problems in mind.

General recommendations for practice and instruction

Research (Anderson, 2008; Campitelli & Gobet, 2011; Ericsson, Krampe, & Clemens, 1993) suggests several conditions that must be in place in order for practice activities to be most effective in moving students closer to skillful performance. Each of these conditions can be met with carefully designed instruction:

Because practice requires intense, focused effort, students may not find it inherently enjoyable. Therefore, teachers can encourage students to practice more by pointing out every time that practice has actually improved their performance. Motivate your students to practice by:

Expressing confidence in students' ability to succeed in solving practice problems.

Designing activities that maximize opportunities for students to succeed.

Teachers should design practice tasks with students existing knowledge in mind. When students succeed at practice problems, the benefits of practice are maximized. But when students become frustrated with unrealistic or poorly designed practice problems, they often lose motivation, will not receive the full benefits of the practice they have done, and will be less motivated to attempt future practice problems.

Students receive the greatest benefits from practice when teachers provide them with timely and descriptive feedback.

Students should have repeated opportunities to practice a task through practicing other tasks like it.

What type of feedback is most effective?

Feedback is most effective when it contains descriptions of how students work meets performance criteria and what students can do to improve. This kind of descriptive feedback is more effective than feedback consisting of vague, general comments (e.g., "nice work or "needs improvement).

Feedback should also be focused on the learning process. That is, teachers should focus their feedback on helping students reflect on their problem solving skills, as well as on progress they have made.

Do's:

1. Vary practice activities.

2. Distribute practice over extended periods of time.

3. Provide clear instructions on performance expectations and criteria.

4. Before asking students to practice independently, model the problem-solving process that you expect students to use.

5. Break complex problems into their constituent elements, and have students practice on these smaller elements before asking them to solve complex problems independently.

6. Guide students through sample practice problems by using prompts that help them reflect on problem-solving strategies.

7. Provide students with fully completed sample problems as well as partially completed sample problems before asking them to apply new problem-solving strategies on their own.

8. Wait until students actually need more information to solve a complex problem before you give them more information. This strategy - known as "just-in-time instruction" - helps keep the amount of information that students must hold in their short-term memories to a manageable level as they practice (Linneman & Plake, 2006; Simkins & Maier, 2008).

9. Provide plenty of opportunities for students to practice applying problem-solving skills before you test them on their ability to use those skills.

Don'ts:

1. Don't ask students to practice complex problem solving without providing them with plenty of guidance and feedback.

2. Don't overload students by presenting information in redundant formats.

3. Don't give your students complex practice problems before they have the skills they need to succeed.

Research suggests that when teachers construct problems for students to practice, they should keep in mind the limitations of human memory.

Moving information to permanent storage is often explained as a multistore model of memory (Atkinson & Shiffrin, 1968; 1971; Baddeley, 1996; 2002). According to this model, our brains have three memory storage systems: sensory memory, short-term memory and long-term memory (Baddeley, 1996; 2002; Carlson, Sullivan, & Schneider, 1989). Learning occurs when we move information from working memory to long-term memory, and practice helps with this process.

Deliberate practice (sometimes called 'rehearsal') keeps the information in our short-term memory long enough for it to move to long-term memory. Once it is in long-term memory, it can be built upon to create more and more complex associations (Baddeley, 2002).

Most researchers agree that there are forms of Short-Term Memory (STM) for different modalities, such as visual STM, auditory STM and motor STM. For example, Baddeley (1992; 1996; 2002) suggests that short-term memory is a dynamic place where sounds and images are turned into verbal and pictorial models. STM is also thought to have a "central executive" that manages the information it is holding. This central executive also controls our awareness of that information (Baddeley, 2002).

The implication for teachers is that they should present material in multiple modalities. If a child who is learning to read hears a word, sees the word and a picture of the word, there will be more learning. The child can get the visual information from the visual STM and additional auditory information in the auditory STM. These two sensory sources of information supplement and complement one another (Liao, 2014). However, teachers must be careful not to have too much extraneous information in the classroom. Over stimulation can put too much demand on working memory (Pass & Kester, 2006).

Short-term or working memory

Working memory or short-term memory, is stored for very short periods of time - minutes at most. Information in our short-term memory is generally housed in the temporal lobe of the brain (the hippocampal region). It allows you to remember phone numbers and also information that comes from long-term memory right before you need to use it. Short-term memory is also the memory system that is used when we cram for a test at the last minute. Attention difficulties, distractions and overload of too much information all negatively impact our short-term memory and cause it to fail. We all have a limited ability to focus on too much stimuli at the same time, and if we don't process the information, we lose it. Practice helps us increase our ability to access information rapidly and automatically.

Practice also frees our brains to process more challenging information and problems. For example, if a child has memorized the multiplication table and can retrieve it automatically, working memory is freed to do more complicated computations.

Practice can improve children's working memory and enhance learning of academic skills, such as reading comprehension and mathematical reasoning (e.g., Dahlin, 2011; Gersten, Fuchs, Williams, & Baker, 2001; Holmes, Gathercole, & Dunning, 2009), verbal learning (Liao, Kronemer, Yau, Desmond, & Marvel, 2014) and motor skills (Gomes, Ugrinowitsch, Marinho, Shea, Raisbeck, & Benda, R., 2014).

And practice using visual spatial tasks can improve visual-spatial working memory (Melby-Lervag & Hulme, 2012; Shipstead, Redick, & Engle, 2012). Likewise, children can be taught a rehearsal or practice strategy to help them improve their reading comprehension (e.g., Gersten, Fuchs, Williams, & Baker, 2001; Rose, Cundick, & Higbee, 1983). Moreover, rehearsal is easier to learn and less demanding than other strategies (Turley-Ames & Whitfield, 2003).

Long-term memory

When working-memory is stored, it becomes long-term memory. Long-term memory is the depository of memories throughout the brain that results from the ongoing chemical processes that changes neuronal connections. The formation of long-term memories takes place over the span of days, weeks and in some cases years. As the memories are consolidated, neuron connections become more and more efficient, and in the process, connections that are no longer useful are discarded from lack of use.

Although the capacity of our long-term memory is apparently limitless (as far as we know, no one has ever stored all that the brain is capable of storing), working memory can typically hold only seven items (plus or minus 2) at any given time, and these items "decay" rapidly (Miller, 1956; Baddeley, 2002).

Research on the brains of rats has shown that relatively short periods of practice can enhance the plasticity of the brain and actually change its structure (Rioult-Pedotti, Friedman, Hess, & Donoghue, 1998). Brain imaging has shown that even a brief lesson on new words changes brain circuits (Allami, Brovelli, Hamzaoui, Regragui, Paulignan, & Boussaoud, 2014; Abdullaev & Posner, 1998; Raichle et al., 1994) and retrieval (Habib, Nyberg, & Tulving, 2003).

Experts and novices differ in the amount and structure of information stored in their long-term memories. These cognitive differences occur in large part because of differences in the amount of deliberate practice in which each has engaged (Cantor & Engle, 1993).

Extensive and deliberate practice makes it possible for students to access and apply increasingly complex information without explicitly thinking about it. In other words, it increases automaticity (see earlier discussion of automaticity) (Anderson, 2008; Case, 1985, 1991). Automaticity leaves students' working memories free to process new information (Kotovsky, Hayes, & Simon, 1985). Since working memory can be overloaded at any time, 'savings' from automaticity become very important. When there is too much information in our working memory it will fail, and the chemical processes that transfer information to our long-term memories also fail. Long-term learning is enhanced by a distribution process in which information is repeated, allowing time with time in between practice sessions, rather than crammed practice.

Reviews and tests are forms of practice that can improve learning. Tests (or quizzes) that are given immediately after a learning exercise give children opportunities to practice. Because learning is recent, students tend to do well on these tests. However, their success does not ensure long-term retention. Teachers can provide time during class to give students additional practice in taking tests. Some tests, such as tests with open-ended answers have been shown to enhance learning because they involve students in the "retrieval" of information from long-term memory. Tests are more effective when they are given at spaced intervals and when they are given frequently (Cull, 2000; Dempster; 1991; Rodriguez, Michael, 2004;Roediger & Karpicke, 2006).

Chunking information, or combining small bits together in short-term memory, is another strategy that students can use to increase their STM holding capacity. Although chunking gives a student more capacity in their STM, its usefulness depends on how much knowledge a person already has. The more knowledge one has on a topic, the more likely that one can "chunk" incoming information into larger and more meaningful chunks. This is why knowledge itself adds to one's ability to solve complex problems. Children who use chunking are more likely to be strategic about their learning. Teachers can help children become more strategic by explicitly teaching them strategies like chunking.

Example of chunking information

The following digits can be seen as a random list of numbers: 14921776. Random or meaningless information taxes the limited capacity of short-term memory (STM). However, if a student "chunks" the information into two dates (1492: Columbus discovered America; and 1776: the year the Declaration of Independence was signed) it is learned as 1492 1776. This leaves room in the short-term memory for more information.

Chunking allows several units of information to be compressed into a single meaningful unit or chunk (e.g., whereas a random number string above represents 8 discrete units to be stored in short-term memory (near its maximum capacity), the two meaningful dates represent only two chunks of information to be stored. This leaves space in the STM for more information to be held. And when more information is held in STM, there is more information available for transfer to long-term memory where it can be permanently stored (Gobet et al., 2001).

Chunking can develop experts' schema. Information stored in the brain in larger chunks of integrated concepts are known as "schemas." For example, a novice chess player who does not yet have complex schemas for chess playing has to devote his or her limited working memory to processing large amounts of information while playing (Anderson, 1996).

An expert, on the other hand, can easily access schemas from long-term memory (deGroot, 1966; Cantor & Engle, 1993). With practice, a novice player can construct chess-playing schemas and therefore increase the amount of information stored in long-term memory. In this way, practice accessing and applying knowledge helps one to transfer that knowledge into a "permastore" of long-term memory so that he or she can more efficiently utilize space available in the working memory (Elo, 1978; Kotovsky & Fallside, 1989).

Theories explaining expert performance

1. Many researchers (e.g., Ericsson et al., 1993; Baddeley, 2002) argue that differences in the amount of practice account for the majority of performance differences between individuals, resulting from differences in the amount and structure of knowledge stored in long-term memory.

2. Other researchers emphasize innate, genetic differences or talent as the main factor accounting for differences between expert and novice performance (Mosing, et.al., 2014; Plomin, DeFries, McClearn, & Rutter, 1997).

3. More recently, researchers have emphasized an interaction between innate and behavioral factors in accounting for differences in performance levels (Gobet & Campitelli, 2007).

Overall, the research supports the view that deliberate practice plays a role in performance differences and can reduce performance differences between individuals who are thought to possess talent and those who do not (Chase & Ericsson, 1981). See Gobet and Campitelli (2007), Mosing, et.al., (2014) and Macnamara, et.al., (2014) for a comprehensive review of this debate.

What can a teacher do to maximize the positive effect of practice?

When teachers assign students to complete practice problems that are structurally similar but different in surface features, it helps them discriminate between relevant and irrelevant information in a given problem. This outcome makes it more likely that students will be able to transfer knowledge gained from practice to new and more complex problems (Paas, 1992). As with all scaffolds, they should be diminished gradually as learners become increasingly more independent.

Students' problem-solving skills also increase when teachers distribute practice over time rather than "cramming" practice into short periods (Bahrick & Hall, 2005). Assignments involving practice are more effective when they are shorter, more frequent and distributed over longer periods of time (Cooper, 2007; Cooper, Robinson, & Patall, 2006; Epstein & Van Voorhis, 2010). This distributive effect is particularly important because it also makes it more likely that students will recall information over longer periods of time. Therefore, distributed practice helps students transfer information into their long-term memory.

Teachers should also have students begin homework during class. By doing so, teachers can monitor students to ensure they understand and can solve practice problems correctly before they practice independently. If teachers are unable to monitor this initial practice, they should explain to their students where they can obtain the information (textbooks, web sites, handouts, etc.) they need to complete the assigned practice problems correctly.

Reviews and tests are a form of practice that can improve learning. Tests provide opportunities for practice that enhance learning. Open-ended test questions also provide practice in retrieving information. Both reviews and tests are most effective when they are well spaced and frequent (Dempster, 1991).

Teachers can train students to reflect on their thinking when solving problems by providing them with lists of questions. This kind of "strategy instruction" helps students to construct schemas more efficiently by facilitating a metacognitive awareness of the problem-solving process. That is, students learn more about how they learn and this helps them with new learning.

Teachers can increase students' abilities to transfer existing problem-solving knowledge to new problems when they prompt students to deliberately reflect on problem-solving strategies they have used before. (Renkl, Stark, Gruber, & Mandl, 1998; Rosenshine & Meister, 1992; Stark, Mandl, Gruber, & Renkl., 2002).

Is homework always effective practice?

There is no question that homework can provide students with opportunities for practice but there are more and less effective homework assignments. Research on homework (Cooper, 2001, 2006; Epstein & Van Voorhis, 2010) suggests that the relationship between time spent on homework and students' academic achievement varies with grade level. When parental involvement is well structured it can also enhance the effectiveness of homework on learning (Epstein & Van Voorhis, 2010; Marzano & Pickering, 2007).

How much time should be spent on homework?

Although high school students appear to benefit from at least two hours of homework per night, there is little or no relationship between time spent on homework and academic achievement for young (grades 1-3) students (Marzano, & Pickering, 2007). Younger students may benefit more from supervised in-school practice than from homework. Middle school students may benefit from one to two hours of homework per night (Cooper, 2007).

Will practice activities negatively affect students' motivation? Aren't practice activities the same as "drill and kill" instruction?

Although deliberate practice is often confused with rote learning, researchers emphasize that there is a difference between mere repetition and deliberate practice. For practice to be effective, appropriate instruction, guided practice, as well as descriptive and timely feedback must all be present.

Does practice with "authentic" problems increase learning?

Due to their relevance, "authentic" problems or "real-life" problems may motivate students. However, the positive effect of practice is only realized when teachers provide instructional supports that address the limitations of students' working memories (Anderson, Reder, & Simon, 1996, 2000; Sweller, van Merrienboer, & Paas, 1998; van Merrienboer, Kirschner, & Kester, 2003). If there is cognitive overload and the working memory is taxed beyond its capacity, students will lose motivation even if a problem is highly relevant to them.

Although "authentic" practice problems sound like they would motivate students with their real-world context; they may also include too many variables at the same time. Students' working memories are thus required to manage too many bits of information, and many of these bits may not be directly involved with the construction of the desired schema (Sweller & Chandler, 1994).

Is there such a thing as too much practice?

Merely repeating a task will not automatically improve performance. Deliberate practice is most effective when it involves intense concentration, rehearsal and reflection. For that reason, students are more likely to benefit from frequent, short practice sessions than from long "cramming" sessions. Teachers can foster this meta-cognitive learning process by providing students with frequent opportunities to discuss their problem-solving strategies (National Research Council, 2005).

Even in early grades when students are acquiring foundational knowledge, practice should not be confused with rote learning. For example, phonics instruction is most effective when it is practiced alongside more complex skills like identifying main ideas in stories (National Institute of Child Health and Human Development, 2000).

Does practice work for all academic subjects?

Practice is correlated with student achievement across all developmental levels and across all subjects. NICHD's (2000) analysis of strategies for reading instruction suggests that several kinds of practice activities are beneficial to students. Phonemic awareness practice, phonics practice and read-aloud practice all showed significant positive effects on student achievement in the early grades. Teachers should always keep long-term goals in mind when they are designing practice activities. The ultimate purpose of phonics instruction is not for students to identify phonemes, but rather, to improve their reading comprehension. The goal of practice is to transfer acquired skills to new and more complex problems. Therefore, practice activities should always be designed with that transfer process in mind.

Studies in mathematics education show that practice is effective when teachers design appropriate practice problems, distribute them over time, and provide students with sufficient feedback. Practice is ineffective when it is not appropriately designed, not well distributed, and when adequate feedback is not provided.

Deliberate practice is also effective in learning complex skills from musical fluency to athletic expertise.

When does the strategy work?

All students benefit from well-designed, developmentally-appropriate deliberate practice activities. A meta-analysis (Macnamara, Hambrick, & Oswald, 2014) showed that the effects of deliberate practice are robust for games, music and sports, and modestly effective in education.

Deliberate practice can also provide a bridge over the gaps that exist between different achievement levels. Achievement gaps often exist because of unequal opportunities for students to engage in appropriate deliberate practice rather than unequal learning abilities. As children grow older, they become better able to benefit from instruction on appropriate strategies like rehearsal, reflection and "chunking" information.

Special populations benefit from practice activities that are designed to meet their needs (Chapman, & Mudar, 2014; Nunes, Barros, Evans, & Burman, 2014; Rose, Cundick, & Higbee, 1983). For example, research on children with language processing problems suggests that their difficulties are due to sensory perception rather than an inability to learn. One reason that language-learning impaired students have difficulty learning to read is that their phonemic recognition and spatial discrimination perceptions are impaired. Appropriate practice activities have been shown to help these students compensate for their difficulties (Merzenich et al., 1996). Cooper's (2001) examination of homework practice suggests that students with learning disabilities benefit most from short, skill-reinforcing activities that are carefully monitored (see also Marzano & Pickering, 2007).

Description of research on the use of practice activities with children with learning disabilities

An extensive meta-analysis of interventions for students with learning disabilities found that practice-drill-review instructional strategies were generally effective across academic subjects (Swanson, Hoskyn, & Lee, 1999). Another meta-analysis of inclusion settings found that time-on-task correlated with student achievement across subject areas (Brophy & Good, 1986). Therefore, practice activities appear to be a key factor in student achievement across grade levels, skill levels and academic domains.

In summary, well-designed practice activities result from careful planning where teachers:

Model problem-solving processes.

Design partially-completed examples on which students can practice.

Sequence activities logically.

Space practice activities appropriately.

Monitor student practice providing guidance and feedback.

Is practice effective across the age span?

Children grow more strategic as they get older. Younger children are less strategic - are less likely to rehearse, practice, or chunk spontaneously or to know how to do these things well. They are also less likely to monitor their own knowledge or to use metacognitive strategies. Younger children are less likely than older children to know what they need to rehearse or practice more. Therefore, teachers of younger children should introduce them to strategies such as rehearsal and practice, and in this way can help students improve their learning.

Deliberate practice is effective across all school age levels. Fundamental practice skills are more appropriate for earlier grades than it is for later grades. Teachers can focus younger students on the skills they will need later when they tackle more complex tasks. For example, phonemic awareness instruction is more effective for preschool students than for older elementary school students (NICHD, 2000), but it remains a skill that is very useful in later grades.

Teachers should design developmentally appropriate practice problems for students. Students' memories and attention spans develop with age (Gomez-Perez & Ostrosky-Solis, 2006; Lechuga, Moreno, Pelegrina, Gomez-Ariza, & Bajo, 2006). In general, older students have greater attention spans and greater memory capacity than younger students. This may account for developmental differences seen in the benefits of homework (Cooper, 2001; Muhlenbrook, Cooper, Nye, & Lindsay, 1999) and age differences in the amount of practice that learners engage in outside the classroom (Ericsson et al., 1993). Teachers should plan the type and amount of practice students are expected to do with these developmental differences in mind.

Research on expert performance shows that experts increase the amount of deliberate practice they engage in over time. For example, research by Ericsson and colleagues (1993) on expert violinists revealed that in early childhood they practiced no more than five hours per week. However, by their early twenties, they practiced around thirty hours per week. Because deliberate practice is so taxing, it should be balanced with sufficient periods of rest. Younger learners tire more quickly and lose their motivation to persist if they are not allowed sufficient rest (Ericsson et al., 1993; NICHD, 2000).

Elementary

Early elementary students benefit little or not at all from homework (Campitelli & Gobet, 2011; Cooper, 2001; Halford, Maybery, & Bain, 1986).

Expert violinists practiced fewer than 5 hours per week at the early childhood stage (Ericsson et al., 1993; Macnamara et al., 2014).

Research supports the idea that practice can help elementary students overcome processing deficits (Merzenich et al., 1996).

Practice with phonemic awareness has been shown to have a positive effect on reading outcomes in elementary readers through 6th grade. Effects were not as strong for disabled readers as they were for at-risk and normally progressing readers. The effects of phonemic-awareness instruction were strongest when it was provided in earlier grades (especially pre-K and kindergarten), in small group settings, in shorter training programs and to English-speaking students (NICHD, 2000).

Research suggests that systematic phonics instruction helps students learning to read. The effects of systematic phonics instruction were greater when it was provided in earlier grades (especially kindergarten and 1st grade) (Dahlin, 2011; Gersten, Fuchs, Williams, & Baker, 2001; NICHD, 2000).

A meta-analysis of intervention strategies for students with learning disabilities found that phonics instruction positively affects development of vocabulary, although the results on comprehension were unclear (Swanson et al., 1999). (The mean age for the study participants was 11; 78% of the studies targeted 9-14 year age range.).

Research suggests that repeated and guided-repeated oral reading strategies have a positive effect on reading performance through grade four, especially for non-impaired readers (Dahlin, 2011; Gersten, et al., 2001; Rose et al., 1983).

Swanson et al.'s (1999) meta-analysis suggests that "the teaching of whole language without due attention to decoding places LD children at greater risk than the use of more traditional programs" (p. 254).

Vocabulary instruction (both explicit and implicit) has a positive effect on vocabulary acquisition. Research indicates that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that reading comprehension strategy instruction (e.g., cognitive and meta-cognitive strategies) has a positive effect on reading comprehension and memory in grades 3-6. The effects were greater when strategy instruction was more intensive and when students were instructed in multiple strategies (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

Middle School

Middle school students may benefit from one to two hours of homework per night (Cooper, 2001; Campitelli & Gobet, 2011).

Research suggests that partial-task practice problems are more effective than whole-task practice problems for some 13 year-old math students. Partial-task practice lowered the processing demands on working memory for all students, but it only increased learning for students with low prior knowledge. Students with high prior knowledge benefited more from whole-task practice (Ayres, 2006).

Research suggests that when modeling problem-solving strategies, the use of worked examples is beneficial for middle school students' writing performance. As with Ayres' (2006) study, however, the positive effects were limited to low-performing students. The results suggested that "low-level" writers benefited from worked-example practice problems, while "high-level" writers benefited from "goal-free" practice problems.

Research suggests that the use of repeated and guided-repeated oral reading strategies positively affect students' reading performance. This is especially true for students with reading problems (NICHD, 2000).

Programs aimed at encouraging students to read more (e.g., self-selected, silent reading) yielded no significant positive effects on reading achievement (NICHD, 2000).

Swanson et al.'s (1999) meta-analysis suggests that "the teaching of whole language without due attention to decoding places LD children at greater risk than the use of more traditional programs" (p. 254).

Results that support the positive effects of vocabulary instruction (both explicit and implicit) on vocabulary acquisition indicate that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that reading-comprehension-strategy instruction (e.g., cognitive and meta-cognitive strategies) has a positive effect on reading comprehension and memory in grades 3-6. The effects were greater when strategy instruction was more intensive and when students were instructed on multiple strategies (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

High School

High school students appear to benefit from at least two hours of homework per night, (Campitelli & Gobet, 2011; Cooper, 2001).

Students may benefit from more practice with the transfer of component skills than from practicing whole-task transfer (Pollock, Chandler, & Sweller, 2002). Examples worked out in advance for students were more effective for algebra problem solving transfer than were conventional problems for 9th and 11th grade students (Sweller & Cooper, 1985).

Repeated and guided-repeated oral reading strategies positively affect reading performance. This is especially true for high school students with reading problems (NICHD, 2000).

Programs aimed at encouraging students to read more (e.g., self-selected, silent reading) yielded no significant positive effects on reading achievement (NICHD, 2000).

Although research supports a positive effect of vocabulary instruction (both explicit and implicit) on vocabulary acquisition in grades 9-11, few studies have been conducted at that level. Results that do exist suggest that students should be exposed to vocabulary repeatedly and in multiple contexts (NICHD, 2000).

Research suggests that "drill-repetition-practice" instructional strategies are beneficial to students with learning disabilities across all age groups and across all subjects (Swanson et al., 1999).

Where can teachers get more information?

Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51(4), 355-368. http://dx.doi.org/10.1037/0003-066X.51.4.355

Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school. Washington, D.C.: National Academy Press. ISBN 0-309-07036-8

Carver, S. M. & Klahr, D. (Eds.). (2001). Cognition and instruction: Twenty-five years of progress. Mahwah, NJ: Erlbaum.

# data[].attributes.attachment_link.title
Practice for knowledge acquisition (not drill and kill)

# data[].attributes.attachment_link.description
Researchers who have investigated expert and novice performance have uncovered important distinctions between deliberate practice and other activities, such as work, play and rote repetition.

# data[].attributes.attachment_link.readable_text
In simple terms, metacognition is thinking about one's thinking. In an educational context, it is students' awareness and understanding of their own strengths and weaknesses as learners and their ability to adapt accordingly to be more successful learners. Metacognition involves active control over the cognitive processes engaged in learning. Novices tend to think more like experts when they recognize their strengths and weaknesses as learners. Self-monitoring and self-regulation, important metacognitive processes, lead to better goal-setting, planning, implementation of plans, monitoring of progress toward goals and, generally, better adaptation of learning strategies. Metacognitive practices increase students' ability to determine how to expand their knowledge and transfer that knowledge to new contexts. Recent studies show that these practices can be taught and learned. Students should understand that their ability to be self-regulated learners can improve with practice. Metacongnition is applicable to a single class session, a homework assignment, an exam, or an entire course.

# data[].attributes.attachment_link.title
L2L Strategy - Metacognition | Arizona Site

# data[].attributes.attachment_link.description
In simple terms, metacognition is thinking about one's thinking. In an educational context, it is students' awareness and understanding of their own strengths and weaknesses as learners and their ability to adapt accordingly to be more successful learners. Metacognition involves active control over the cognitive processes engaged in learning.

# data[].attributes.attachment_link.title
Day 6: Supporting Real-World Transfer Through Innovative Engagement, Practice & Feedback (Neuro 1)

# data[].attributes.attachment_link.readable_text
Retrieval practice is a simple research-based teaching strategy that dramatically raises students' grades. When students retrieve and bring information to mind, this mental challenge produces durable long-term learning. Easy learning leads to easy forgetting. Stop cramming, reviewing, and re-teaching. Instead, simply ask students what they remember. No prep, no grading, just powerful teaching.

The science of learning exists. It's time to unleash it.

# data[].attributes.attachment_link.title
Retrieval Practice: Unleash the Science of Learning

# data[].attributes.attachment_link.description
Harness powerful teaching strategies, unleash the science of learning, and transform your classroom with resources by cognitive scientists.

# data[].attributes.attachment_link.readable_text
To interleave while studying, students should choose several topics and spread them throughout their study sessions. The topics can be from the same or different subjects, but some experts believe that this strategy is most beneficial when the subjects are related in some way. For example, during a study session, a student could devote some time to math, some time to chemistry, some time to biology and then cycle back through the topics, possibly studying the topics in a different order and using different study strategies. Changing things up forces students to retrieve information and make new connections between the topics: for example, how is this topic in biology related to what was just studied in chemistry? It is important to devote enough time to each topic to ensure that a deeper understanding is achieved each time the topic is studied. Learners should be careful not to use interleaving as an excuse to switch to another subject when the current subject becomes too challenging. Instead, they should persist in one subject until they have a sense of accomplishment before moving on to another subject.

# data[].attributes.attachment_link.title
L2L Strategy - Interleaving | Arizona Site

# data[].attributes.attachment_link.description
To interleave while studying, students should choose several topics and spread them throughout their study sessions. The topics can be from the same or different subjects, but some experts believe that this strategy is most beneficial when the subjects are related in some way.

# data[].attributes.attachment_link.readable_text
This section provides an overview of how to tailor your writing based on the type of assignment you are required to write.

Discover the basic structure of all essays and see what a good essay introduction and conclusion look like.

Learn how to create effective content and deliver your message in a way that engages your audience.

# data[].attributes.attachment_link.description
This section provides an overview of how to tailor your writing based on the type of assignment you are required to write.

# data[].attributes.attachment_link.readable_text
How well do students learn when a lesson is mainly in PowerPoint? Henrik Berger Jørgensen, CC BY-NC-ND

For a brief period in the history of teaching, using PowerPoint automatically qualified you as a tech-savvy professor - an innovator who wouldn't settle for the usual combination of staticky black-and-white overhead films and hand-scrawled chalkboard notes.

Now, it's hard to believe that PowerPoint was once considered innovative by anyone. Popular criticism includes everything from tongue-in-cheek comments about death by PowerPoint to serious claims that it fundamentally degrades how we think and communicate.

But much of today's college instruction isn't in face-to-face classrooms, a setting in which PowerPoint was traditionally used. It's in the burgeoning field of online learning.

So if more learning is moving online, does that mean that teaching with PowerPoint is becoming a thing of the past?

Surprisingly, the answer is no.

Passive learning through PowerPoint?

Even though there's little research that directly addresses whether PowerPoint affects learning in college students, critics have questioned its value in educational settings.

Some ask whether PowerPoint might indirectly undermine the quality of teaching by reinforcing a passive learning approach.

We know that lecturing is less effective than alternative methods. It therefore makes sense for teachers in face-to-face classrooms to question how much of their class time ought to be spent on slideshows.

But the fact is "slideshows" remain a popular method for presenting content in today's online courses.

Technically, these are often not PowerPoints, but decks generated using other types of specialized programs.

And they may differ from standard in-class PowerPoint presentations in important ways.

For example, taking advantage of the increased flexibility of the online environment, they give students more control over how quickly to go through the material and when to backtrack. They can also have more interactive features, such as quizzes, that ask students to apply material while they are learning it.

Even so, the basic - and flawed - idea is the same: put the material in front of students, and learning will happen.

What's wrong with slideshows in online courses

As a psychologist specializing in teaching techniques and course design, when I talk to faculty about teaching effectively with technology, I sometimes tell them to follow the ABS principle: anything but slideshows.

I'm only half-kidding with that blanket statement.

After all, we learn with the same brains in online environments as we do face-to-face; the principles of learning don't change just because the medium changes. And today's learning theorists agree: active involvement trumps passive viewing.

Students need to grapple with challenging problems, practice skills, discuss and defend viewpoints. But for this kind of active learning to happen, instructors need to ensure they do not rely too heavily on slides.

There are alternatives: simulations, problem-based learning, even educational games are all proven methods for drawing students in. They also transplant well into online learning.

Using slideshows the right way

So do slideshows have any place in a well-designed online course? Possibly.

They can be used strategically for things they are best at: giving students an overview of new material, or providing a refresher on concepts students will need for an upcoming activity.

Slides are also great for for integrating visual illustrations. This is important because visuals - diagrams, figures, photos and the like - have a powerful impact on learning.

Visual information is almost always more memorable than sound, text or other modalities.

This isn't because of the now-debunked idea that some people are "visual learners," but more likely stems from how the brain codes images. There are separate systems for representing verbal and visual information in the brain. When we save information in both places, it is easier to recall.

Teachers don't have to stick with static images, either. Even basic animations can illuminate conceptual relationships - such as cause and effect, or the unfolding of a process over time - in ways that text can't.

Furthermore, as University of California, Santa Barbara researcher Richard Mayer has discovered, visuals and the spoken word pair up in powerful ways, so that audio plus visuals produce better learning than either alone.

Research also tells teachers some things not to do with visuals. Instructors should avoid purely decorative graphics, as these can actually hamper learning.

They should also eschew reading text verbatim, instead using a conversational, natural speaking style for voiceovers and verbal explanations.

What this means in the larger context of online learning

In sum, slideshows can be a useful part of online instruction, when used for the right things and designed in the right way. But they shouldn't be the main, or the only, method of instruction - any more than lectures should dominate face-to-face classes.

But it's not just instructors who need to hear this message.

Publishing and educational technology companies, who provide many of the tools that educators rely on, can do more to develop products that push beyond familiar formulas and draw on the latest learning science.

We need tools that make it easy to create assignments that ask students to apply what they have learned, in scenarios that are as realistic and challenging as possible.

These learning tools also need to be adaptive, adjusting the material and pace to the individual learner. This kind of educational technology does exist, but far more can be done to expand the available options.

Teaching in the age of technology comes with its own set of opportunities as well as challenges. And online education presents educators and tech developers with a rare opportunity to fundamentally rethink what we do.

Will we use it to explore new avenues for learning, or will we fall back on the the same old techniques that don't work well in face-to-face classrooms?

# data[].attributes.attachment_link.title
Learning from PowerPoint: is it time for teachers to move on?

# data[].attributes.attachment_link.description
Slideshows, when designed right, can be a useful part of online instruction. But they shouldn't be the main, or the only, method of instruction.

# data[].attributes.attachment_link.provider_name
Struggling to Learn a New Language? Blame It on Your Stable Brain | UC San Francisco

# data[].attributes.attachment_link.readable_text
A study in patients with epilepsy is helping researchers understand how the brain manages the task of learning a new language while retaining our mother tongue. The study, by neuroscientists at UC San Francisco, sheds light on the age-old question of why it's so difficult to learn a second language as an adult.

The somewhat surprising results gave the team a window into how the brain navigates the tradeoff between neuroplasticity - the ability to grow new connections between neurons when learning new things - and stability, which allows us to maintain the integrated networks of things we've already learned. The findings appear in the Aug. 30 issue of Proceedings of the National Academy of Sciences.

"When learning a new language, our brains are somehow accommodating both of these forces as they're competing against each other," said Matt Leonard, PhD, assistant professor of neurological surgery and a member of the UCSF Weill Institute for Neurosciences.

By using electrodes on the surface of the brain to follow high-resolution neural signals, the team found that clusters of neurons scattered throughout the speech cortex appear to fine-tune themselves as a listener gains familiarity with foreign sounds.

"These are our first insights into what's changing in the brain between first hearing the sounds of a foreign language and being able to recognize them," said Leonard, who is a principal investigator on the study.

"That in-between stage is a crucial step in language learning but has been difficult to tackle, because the process is dynamic and unique to the individual," he said. "With this study, we were able to see what's actually happening in the brain regions involved in differentiating sounds during this initial phase of learning."

Shift as Foreign Sounds Become Familiar

Learning the sounds of a new language is the first step in learning to use that language, said Leonard. So for this study, Leonard and lead author and postdoctoral scholar Han Yi, PhD, investigated how the activity in the dispersed brain regions associated with language shifted as the listener became more familiar with the foreign sounds.

The team worked with 10 patient volunteers, aged 19 to 59, whose native language is English, and asked them to recognize speech sounds in Mandarin. Mandarin is a tonal language in which the meaning of the word relies not only on the vowel and consonant sounds but also on subtle changes in the pitch of the voice, known as tones. Speakers of non-tonal languages like English often find it very challenging to discern these unfamiliar sounds.

Each of the volunteers had previously had brain surgery, during which electrodes were implanted in their brains to locate the source of their seizures. The study included seven patients at the UCSF Epilepsy Center, and three in the Epilepsy Center at the University of Iowa Hospitals and Clinics. The volunteers agreed to allow Leonard and his team to gather data from high-density, 256-channel electrodes placed on the surface of the brain regions that process speech sounds.

Over the course of the next few days, Leonard and Yi worked with the volunteers individually, playing recordings of several native Mandarin speakers of different ages, both male and female, pronouncing syllables like "ma" and "di" using each of the four tones. After each sound the patient indicated whether they thought the tone was going up, down, up and then down, or staying flat, and received feedback on whether they were correct. Patients repeated this task about 200 times, over several five- to 10-minute sessions.

After that brief amount of time, Leonard said, people had gotten through the initial learning phase and had become somewhat adept at categorizing the sounds.

"We also saw a lot of variability," he added. "Some people will get a bunch of trials right and then they'll start getting them wrong and then they'll get it right again in this kind of up-and-down that seems to be part of the learning process."

Fine-Tuning Neural 'Knobs'

When Leonard and Yi looked at the neural signals generated by the language learners, they saw a pattern that both surprised them and explained the performance curve they'd observed.

Data from other published studies suggested that activity across the speech cortex might increase as a person becomes more familiar with the language. What the researchers discovered instead was a spectrum of changes distributed throughout that speech cortex; with activity increasing in some areas but decreasing in others, maintaining a careful balance.

Those changes might be related to a brain area becoming tuned in to a particular tone, said Yi.

"We could see some groups of cells would respond more to the falling tone, and just keep ramping up their response, while right next to it another group of cells would increasingly engage when the person heard the dipping tone," Yi said. "It's as if these small clumps of neurons took on different roles."

In addition, which brain regions were more activated by which tone varied across individuals.

"It's more like each person's brain has a unique set of knobs that are getting fine-tuned while they're becoming familiar with these sounds," Leonard said.

Leonard and Yi think this may explain why some people pick up the sounds much more easily than others, as each unique brain strikes its own balance between maintaining the stability of the native language while calling on the plasticity required to learn a new one.

"The volunteers were able to learn the tones in Mandarin without affecting their ability to perceive pitch in English or in music," said Leonard. "These little neural knobs were all communicating with each other to reach the point where they can do the task correctly by working together."

Co-authors include William L. Schuerman, PhD, and Edward F. Chang, MD, of UCSF. Additional authors can be found in the paper. The work was supported by grants from DARPA (N66001-17-2-4008) and NIH (R01-DC012379, R01-DC0155004), as well as philanthropic foundations.
The University of California, San Francisco (UCSF) is exclusively focused on the health sciences and is dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. UCSF Health, which serves as UCSF's primary academic medical center, includes top-ranked specialty hospitals and other clinical programs, and has affiliations throughout the Bay Area.

# data[].attributes.attachment_link.title
Struggling to Learn a New Language? Blame It on Your Stable Brain

# data[].attributes.attachment_link.description
A study in patients with epilepsy is helping researchers understand how the brain manages the task of learning a new language while retaining our mother tongue. The study, by neuroscientists at UC San Francisco, sheds light on the age-old question of why it's so difficult to learn a second language as an adult.

# data[].attributes.attachment_link.readable_text
The UDL Guidelines are a tool used in the implementation of Universal Design for Learning, a framework to improve and optimize teaching and learning for all people based on scientific insights into how humans learn. Learn more about the Universal Design for Learning framework from CAST. The UDL Guidelines can be used by educators, curriculum developers, researchers, parents, and anyone else who wants to implement the UDL framework in a learning environment. These guidelines offer a set of concrete suggestions that can be applied to any discipline or domain to ensure that all learners can access and participate in meaningful, challenging learning opportunities.

Reenvisioning the UDL Guidelines

Because the UDL Guidelines are meant to be informed by feedback from the field as well as new research, they have been updated several times in the past. We are in the process of updating the Guidelines once again in our UDL Rising to Equity initiative.

This update will focus specifically on addressing systemic barriers that result in inequitable learning opportunities and outcomes. CAST aims to develop a transparent, inclusive, and community-driven process. If you are interested in collaborating and staying updated on our progress, we invite you to complete a brief survey.

# data[].attributes.attachment_link.description
The UDL Guidelines are a tool used in the implementation of Universal Design for Learning, a framework to improve and optimize teaching and learning for all people based on scientific insights into how humans learn. Learn more about the Universal Design for Learning framework from CAST. The UDL Guidelines can be used by educators, curriculum developers, researchers, parents, and anyone else who wants to implement the UDL framework in a learning environment. These guidelines offer a set of concrete suggestions that can be applied to any discipline or domain to ensure that all learners can access and participate in meaningful, challenging learning opportunities.

# data[].attributes.attachment_link.readable_text
Neuroplasticity is the brain's capacity to continue growing and evolving in response to life experiences. Plasticity is the capacity to be shaped, molded, or altered; neuroplasticity, then, is the ability for the brain to adapt or change over time, by creating new neurons and building new networks.

Historically, scientists believed that the brain stopped growing after childhood. But current research shows that the brain is able to continue growing and changing throughout the lifespan, refining its architecture or shifting functions to different regions of the brain.

The importance of neuroplasticity can't be overstated: It means that it is possible to change dysfunctional patterns of thinking and behaving and to develop new mindsets, new memories, new skills, and new abilities.

# data[].attributes.attachment_link.description
Neuroplasticity is the brain's capacity to continue growing and evolving in response to life experiences. Plasticity is the capacity to be shaped, molded, or altered; neuroplasticity, then, is the ability for the brain to adapt or change over time, by creating new neurons and building new networks.

# data[].attributes.attachment_link.title
Interactive Brain | How the brain works & the impact of injury

# data[].attributes.attachment_link.description
Take an interactive journey to see how the brain works and what impact an injury can have

# data[].attributes.attachment_link.readable_text
K atie Novak explains why the implementation of universal design for learning (UDL) is best practice to increase engagement in all students

In 1922, my grandmother moved from Trois-Rivières, a city in Quebec, Canada, at the age of eleven. Speaking only French, and traveling with her older sister, she was determined to learn English once she arrived. Each day, after she finished her official au pair duties, she walked to the local market to teach herself English. Her textbooks? The handwritten signs posted above the food and day-old newspapers. Her teachers? The store owner and passersby completing their nightly shopping.

Before she died, she bragged that she was fluent in groceries long before she mastered conversational English. Her strategy was simple, she said. She befriended the store owner, who gave her the permission she needed to amble around the store, picking up fruits, vegetables, boxes of cereal, and newspapers. And if the signs did not exist?

She would pick up a shiny apple or a handful of walnuts and ask anyone who would listen, " Qu'est-ce que c'est? " She recalls the kindness of her strangers, always patient as they helped build her comprehension and provided her with feedback.

Without any formal education beyond third grade, Mémère became fluent in English because of her daily market visits. Knowing now what I know about education, it is clear that Mémère's "teachers" exemplified the principles of universal design for learning (UDL), a framework that provides options to ensure that all students have the opportunity to experience growth and success. Mémère got not just one way but a whole basket of tips and assistance to learn English.

The Building Blocks of UDL

The Every Student Succeeds Act (ESSA) urges states to adopt UDL in a number of areas. For example, it says assessments should be designed using the principles of UDL. It also requires schools to use the principles of UDL to support the learning needs of all students, including English learners (ESSA, 2015, Section 4104).

In a recent publication of WIDA Focus On, a series of bulletins on topics of interest to educators of English language learners, it notes, "Accessibility principles, including processes like Universal Design for Learning (CAST, 2008), can help educators rethink how they position language development support within activities." The building blocks of UDL include three core principles, which remind educators to provide options to ensure that all students have equal opportunities to access and engage with rigorous academic curriculum.

Provide Multiple Means of Representation

The first principle of UDL reminds educators to provide multiple means of representation to build knowledge and comprehension in all learners. In the case of my Mémère, she had manipulatives: pungent onions, stalks of celery, and newspapers that stamped her fingers with black ink. But that was not enough for her to develop and use English. In addition, she had options to build background knowledge by accessing visual support through pictures and words and accessing auditory support through conversations with individuals who encouraged her language expression.

She also had access to her native language, as the storeowner spoke French. We can foster multiple means of representation in the classroom by providing all students with access to visual support as well as the option to listen to texts in English via peer reading, audio books, and text-to-speech.

One of my colleagues, ELL teacher Cheney Harper, designed a lesson for her students on the rainforest and took them on a "virtual field trip." At the beginning of the lesson, Cheney welcomed all students at the door, which was decorated with a lush, green poster of the rain forest. She then opened up an "explorer backpack," from which she gave them each rain forest props to begin their rain forest scavenger hunt.

Each student received a scavenger hunt list, and they had to find twelve animals that live in the rain forest by searching around the classroom and in books. In the classroom, she had hidden twelve stuffed animals, each attached to informational text that provided details about the animals. As they found the animals, she identified the names of the animals (i.e., jaguar, caiman, speckled bear) and shared characteristics of the animals.

She then took them on a "rain forest tour" on the iPad so they could build more background knowledge on the rain forest. As they worked, they had access to translation software and dictionaries, so they had access to their native languages. Having access to the multiple means of representation allowed all students to actively participate in the activity, learn academic vocabulary, and engage with peers in a fun, meaningful way.

Provide Multiple Means of Action and Expression

It is not enough to comprehend information if there is no way to express it. Students need numerous methods to express their understanding as they develop into writers and speakers.

When we examine the Common Core State Standards, teaching methods, materials, and assessments are not outlined. This provides us with an opportunity to create multiple pathways to meet the same destination by providing students with options.

This is no accident, as the Common Core endorses UDL as the framework to support all students as they reach for the standards. The standards are only the "what." UDL is the "how."

There are many different paths to reach the same destination. We, as educators, need to embrace the many possible journeys that our students can take in order to arrive at the same place. Traditional assessments are one-size-fits-all and expect the same product from all students (i.e., everyone is expected to write informative text as a five-paragraph essay).

UDL encourages multiple options for expression and multiple scaffolds to help all students reach the goal. Take the anchor standard, "Write informative/explanatory texts to examine and convey complex ideas and information clearly."

Sentence frames, graphic organizers, collaborative work, exemplars, and the use of the WIDA English Language Development Standards provide necessary supports that allow all students to express what they know in inclusive, diverse classrooms while working toward the same standard. Additionally, since students master speaking before writing, educators may provide English learners the option to audio record their learning, supplement with visuals, or use voice-recognition software to scaffold the language process as they continue to develop into writers.

Provide Multiple Means of Engagement

Engagement is at the core of all learning experiences. If we want students to learn, we have to foster both attention and commitment by providing students with authentic, meaningful experiences in learning. All students need access to options that help them connect their own cultural backgrounds to new learning activities, as well as access to their peers to foster collaboration and community. In order to master a skill, one needs practice.

A lot of practice. Peers provide an amazing opportunity for English learners to practice speaking in the classroom. Just as my Mémère befriended countless customers at the market, our students need to interact with their peers.

From "do-nows" to brainstorming sessions to collaborative discussions, authentic opportunities to build language with others are what build a solid foundation to learn academic English. Teachers can observe these collaborative conversations, informally assess students, and give feedback on their language structures and use of vocabulary to provide additional means for action and expression in authentic settings.

These three principles of UDL-provide multiple means of representation, provide multiple means of action and expression, and provide multiple means of engagement-remind all educators to ensure that English language learners always have the option to build background knowledge, interact with information visually and auditorily, access rich scaffolds and supports to help highlight the patterns of language, and have numerous opportunities to express what they know in ways that are authentic and meaningful, all while experiencing the value of collaboration and feedback.

Of course, in the early 1900s, my grandmother had no concept of universal design for learning, nor did her teachers. David Rose, Anne Meyer, and their colleagues at CAST would not articulate the UDL principles until the very end of the century. But something happened in that marketplace which exemplifies what we want teaching and learning to look like today.

Now that we have a framework that is intertwined with our Common Core State Standards, WIDA briefs, and federal legislation, it is time to optimize and scale the framework in all classrooms. Let us make that happen so our students can experience the same magic that my Mémère did, as she learned to appreciate the power of language.

Katie Novak, EdD, is the assistant superintendent of the Groton-Dunstable Regional School District in Massachusetts and a leading expert on universal design for learning implementation. She is the author of four books, including UDL Now! (CAST Professional Publishing, 2016), Universally Designed Leadership (CAST, 2016), and Let Them Thrive (CAST, 2017). Learn more at http://www.katienovakudl.com.

# data[].attributes.attachment_link.title
Why UDL Matters for English Language Learners - Language Magazine

# data[].attributes.attachment_link.description
Katie Novak explains why the implementation of universal design for learning (UDL) is best practice to increase engagement in all students In 1922, my grandmother moved from Trois-Rivières, a city in Quebec, Canada, at the age of eleven. Speaking only French, and traveling with her older sister, she was determined to learn English once she [...]

# data[].attributes.attachment_link.readable_text
Date
Wednesday, May 22, 2019

Presenters
Caroline Torres & Kavita Rao

Description

Designing instruction to meet the needs of language learners, whose primary language is not the language of instruction, can be overwhelming. Language learners come to our classrooms with varied backgrounds, prior experiences, strengths, and needs. Whether one or multiple primary languages are spoken in your classroom, using Universal Design for Learning can help address the variability of all your learners. Join us in this conversation with authors Cary Torres and Kavita Rao where they will share a behind the scenes look at their book, UDL for Language Learners, and you can gain practical tips to design instruction for all learners.

Presentation slides

Digital handout

Access the webinar recording

# data[].attributes.attachment_link.description
Date Wednesday, May 22, 2019 Presenters Caroline Torres & Kavita Rao Designing instruction to meet the needs of language learners, whose primary language is not the language of instruction, can be overwhelming. Language learners come to our classrooms with varied backgrounds, prior experiences, strengths, and needs.

# data[].attributes.attachment_link.readable_text
The NFLRC is pleased to release its new 7-episode podcast series on Universal Design for Learning (UDL) in World Languages for 2022.

All interviews are hosted by Nicole Naditz (2015 ACTFL National Language Teacher of the Year). The NFLRC contributed its expertise in instructional design and technology and provided logistical support. Each episode features interviews with world language professionals who share their insights and experience in relation to UDL for the world language classroom.

Resources and references for each podcast interview can be found below. Enjoy!

The entire podcast playlist can be accessed from our NFLRC Soundcloud channel.

Available May 10, 2022

Available May 11, 2022

Available May 12, 2022
Episode 3 resources
Available May 13, 2022

Available May 14, 2022
Episode 5 resources
Available May 15, 2022
Episode 6 resources
Available May 16, 2022
Episode 7 resources
Resources

For Episode 1

For Episode 2

For Episode 3
Accessibility Universal Design for Learning
For Episode 4

Spathis, Elena (2019) " Station Rotation in World Language Classes " Edutopia. Accessed on July 2, 2021

Tovani, Crios (2010) " Minimize Lecture, Maximize Learning: The Workshop Model " , excerpt from So What Do They Really Know? at Education World, Accessed on July 2, 2021.

For Episode 5

1. Chapter 2 of the California World Languages Framework

2. Chart: The Difference Between Universal Design for Learning and Traditional Education

3. UDL Guidelines (CAST.org)

4. ACTFL Appendix D (interpretive task template)

For Episode 6

For Episode 7

1. Universal Design for Instruction: A Framework for Anticipating and Responding to Disability and Other Diverse Learning Needs in the College Classroom

2. Project LINC

3. Universal Design and Its Applications in Educational Environments

4. Disability and World Language Learning by Sally Scott and Wade Edwards, 2019

# data[].attributes.attachment_link.title
Universal Design for Learning (UDL) in World Languages

# data[].attributes.attachment_link.description
The NFLRC is pleased to release its new 7-episode podcast series on Universal Design for Learning (UDL) in World Languages for 2022. All interviews are hosted by Nicole Naditz (2015 ACTFL National Language Teacher of the Year). The NFLRC contributed its expertise in instructional design and technology and provided logistical support.

# data[].attributes.attachment_link.readable_text
The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

doi: 10.1016/j.cortex.2014.05.001.

Affiliations

¹ Center for Brain, Behavior, and Cognition, Center for Language Science, Department of Psychology, Pennsylvania State University, United States. Electronic address: pul8@psu.edu.

² Center for Brain, Behavior, and Cognition, Center for Language Science, Department of Psychology, Pennsylvania State University, United States.

doi: 10.1016/j.cortex.2014.05.001.

Affiliations

¹ Center for Brain, Behavior, and Cognition, Center for Language Science, Department of Psychology, Pennsylvania State University, United States. Electronic address: pul8@psu.edu.

² Center for Brain, Behavior, and Cognition, Center for Language Science, Department of Psychology, Pennsylvania State University, United States.

Abstract

The brain has an extraordinary ability to functionally and physically change or reconfigure its structure in response to environmental stimulus, cognitive demand, or behavioral experience. This property, known as neuroplasticity, has been examined extensively in many domains. But how does neuroplasticity occur in the brain as a function of an individual's experience with a second language? It is not until recently that we have gained some understanding of this question by examining the anatomical changes as well as functional neural patterns that are induced by the learning and use of multiple languages. In this article we review emerging evidence regarding how structural neuroplasticity occurs in the brain as a result of one's bilingual experience. Our review aims at identifying the processes and mechanisms that drive experience-dependent anatomical changes, and integrating structural imaging evidence with current knowledge of functional neural plasticity of language and other cognitive skills. The evidence reviewed so far portrays a picture that is highly consistent with structural neuroplasticity observed for other domains: second language experience-induced brain changes, including increased gray matter (GM) density and white matter (WM) integrity, can be found in children, young adults, and the elderly; can occur rapidly with short-term language learning or training; and are sensitive to age, age of acquisition, proficiency or performance level, language-specific characteristics, and individual differences. We conclude with a theoretical perspective on neuroplasticity in language and bilingualism, and point to future directions for research.

Keywords: Bilingualism; DTI; Neuroplasticity; Second language acquisition; VBM.

Similar articles

White matter structure changes as adults learn a second language.

Schlegel AA, Rudelson JJ, Tse PU. Schlegel AA, et al. J Cogn Neurosci. 2012 Aug;24(8):1664-70. doi: 10.1162/jocn_a_00240. Epub 2012 May 9. J Cogn Neurosci. 2012. PMID: 22571459

Structural plasticity in the language system related to increased second language proficiency.

Stein M, Federspiel A, Koenig T, Wirth M, Strik W, Wiest R, Brandeis D, Dierks T. Stein M, et al. Cortex. 2012 Apr;48(4):458-65. doi: 10.1016/j.cortex.2010.10.007. Epub 2010 Oct 28. Cortex. 2012. PMID: 21106192

Early bilingualism, language attainment, and brain development.

Berken JA, Gracco VL, Klein D. Berken JA, et al. Neuropsychologia. 2017 Apr;98:220-227. doi: 10.1016/j.neuropsychologia.2016.08.031. Epub 2016 Sep 1. Neuropsychologia. 2017. PMID: 27593907 Review.

Consequences of multilingualism for neural architecture.

Hayakawa S, Marian V. Hayakawa S, et al. Behav Brain Funct. 2019 Mar 25;15(1):6. doi: 10.1186/s12993-019-0157-z. Behav Brain Funct. 2019. PMID: 30909931 Free PMC article. Review.

Distinct patterns of functional and structural neuroplasticity associated with learning Morse code.

Schmidt-Wilcke T, Rosengarth K, Luerding R, Bogdahn U, Greenlee MW. Schmidt-Wilcke T, et al. Neuroimage. 2010 Jul 1;51(3):1234-41. doi: 10.1016/j.neuroimage.2010.03.042. Epub 2010 Mar 24. Neuroimage. 2010. PMID: 20346399

Cited by

Musical and Multilingual Experience Are Related to Healthy Aging: Better Some Than None But Even Better Together.

Nijmeijer SE, van Tol MJ, Aleman A, Keijzer M. Nijmeijer SE, et al. J Gerontol B Psychol Sci Soc Sci. 2023 Apr 1;78(4):609-619. doi: 10.1093/geronb/gbac185. J Gerontol B Psychol Sci Soc Sci. 2023. PMID: 36454717 Free PMC article.

Person-specific connectivity mapping uncovers differences of bilingual language experience on brain bases of attention in children.

Arredondo MM, Kovelman I, Satterfield T, Hu X, Stojanov L, Beltz AM. Arredondo MM, et al. Brain Lang. 2022 Apr;227:105084. doi: 10.1016/j.bandl.2022.105084. Epub 2022 Feb 14. Brain Lang. 2022. PMID: 35176615 Free PMC article.

# data[].attributes.attachment_link.keywords[]
national center for biotechnology information

# data[].attributes.attachment_link.title
Neuroplasticity as a function of second language learning: anatomical changes in the human brain - PubMed

# data[].attributes.attachment_link.description
The brain has an extraordinary ability to functionally and physically change or reconfigure its structure in response to environmental stimulus, cognitive demand, or behavioral experience. This property, known as neuroplasticity, has been examined extensively in many domains. But how does neuroplast ...

# data[].attributes.attachment_link.title
Improving our neuroplasticity | Dr. Kelly Lambert | TEDxBermuda

# data[].attributes.attachment_link.title
How can stress affect learning?  | Dr. Lara Boyd | TEDxSurrey

# data[].attributes.attachment_link.readable_text
Should mobile devices be encouraged in class? Trinity College, CC BY-NC-ND

It's hard not to notice the connection of today's youth to technology.

Fused to their smartphones around the clock, they prefer screens to paper and text message to speech; they consider leaving voicemail an act of interpersonal aggression.

They seem to focus differently too: skimming and sampling their way through multiple streams of data, they look like they're taking it in all at once.

Some educators call them "digital natives," reflecting the idea that tech is at the core of who they are and how they function.

If living with technology really has rewired this generation for multitasking, what implications does this have for how we educate them? Should we tolerate - or maybe even encourage - mobile devices in class? And should we worry when we see students keeping an eye on social media or other diversions while doing homework?

Why attention matters for learning

As a professor who specializes in course design, I deal with these questions frequently as I help fellow faculty devise better strategies. In this work, I draw on my research background in cognitive psychology, a specialization focusing on mental processes such as reasoning, memory and attention.

Of those processes, attention is one that I tell teachers to be particularly attuned to. Research shows that memory - especially working memory, which holds information we're using in the present moment - is deeply intertwined with attention.

Without sustained focus, we retain surprisingly little, and that window of focus is much narrower than we may realize.

So, are the minds of digital natives - or any heavy tech users - better or worse when it comes to attention? It's a complicated question, partly because attention works in some paradoxical ways.

The function of attention is to prioritize where we put our limited cognitive resources at any given moment. One thing attention does is keep irrelevant information at bay. Like a bouncer at an exclusive nightclub, its job is to ensure that only the most important and relevant elements pass through into conscious awareness.

But at the same time, a well-functioning attention system has to stay open to information that's in the background and could be potentially useful. That mental bouncer has to constantly scan the crowd for anyone who might turn out to be a great addition to the party, pick them out and usher them inside.

What technology does to the ability to pay attention

Technology seems to have a bigger impact on that second side of attention.

Certain kinds of tech use - habitually consuming lots of online media at once, or playing certain kinds of video games - appear to boost the ability to efficiently pick up on peripheral information while keeping up with a main task.

And although long-term studies are lacking, there is a growing body of research on how tech-saturated environments shape the minds and brains of kids.

It's unlikely that video games or online media damage kids' ability to pay attention. But comparative research across high-tech and low-tech societies suggests that information processing is different in kids who grow up working with digital rather than physical tools. Neither group is better or worse across the board, but this research suggests that high-tech kids may be less inclined to learn by watching for extended periods of time.

That said, we should be cautious about concluding that today's students have developed the ability to juggle as much technology as they want. Technology has not reshaped the basic ways in which our brains process information.

As cognitive psychologist Daniel Willingham points out, the impact of things like video games is relatively subtle. All they can do is tinker around the edges of our mental systems, rather than altering them at the core.

As Willingham says, something as fundamental as attention couldn't be deeply reshaped without a major overhaul of the brain - something that would be a function of evolution, not life experiences.

All of this means that college teachers should be skeptical of claims that their game- and tech-obsessed students process information completely differently. Compared to earlier generations, today's students are probably no more able to learn while simultaneously engrossed in Twitter, Facebook and texting.

College students and technology

There are other pitfalls to consider.

Research with young adults in college suggests that they are neither as enthusiastic about technology nor as adept at using it as we may assume. Sometimes, they intentionally opt for lower-tech approaches; in one study of California college students, most said that they preferred paper over a browser for their own studying.

This is something my faculty colleagues commonly observe as well - that although their students may use technology like social media casually throughout the day, it doesn't translate to other tech-based tasks, such as navigating a course's online homework system.

Students also get into trouble if they assume - because of the "digital nativism" idea, or simple lack of self-awareness - that they can master demanding coursework while engaged in digital distractions.

Evidence suggests that multitasking - such as tweeting in class - reduces learning, or at the very least makes it take longer.

Even sitting next to a classmate surfing the web on his or her own laptop hampers learning.

In sum, despite that appearance of being fused to their devices, today's students aren't immune to the distraction those devices cause. And they don't necessarily want technology in every corner of their educational lives.

How college teachers can help

College teachers need to include lots of tech support for online assignments and other kinds of educational technologies, because even students who have grown up with computers still get stuck when using them in new contexts.

Teachers must also avoid the trap of adding tech to a class just because they assume digital native students want it. Educational technology can be highly effective, but only when it is tightly coupled to the teacher's goals.

Even better, teachers can help students understand for themselves how attention works - knowledge that everyone ought to have in today's distracting era. Without vilifying technology, teachers can work to raise students' awareness about how attention impacts learning more than we may realize, no matter what our age.

The effects of technology on cognition are intriguing, but they don't justify teaching millennials as if they were a new species. Teachers need to think twice about tolerating devices in class, except as part of structured activities that link to the lesson at hand.

# data[].attributes.attachment_link.title
Can millennials pay attention to classwork while texting, tweeting and being on Facebook?

# data[].attributes.attachment_link.description
From the look of it, the millennials appear to be very comfortable with technology. But are they as immune to the effects of digital distraction as some might assume - especially in the classroom?

# data[].attributes.attachment_link.readable_text
Examples

In addition to the three core styles, over 71 separate learning-style instruments and theories have been documented in education literature (Coffield et al 2004). 30 popular ones include (Pashler 2008):

· convergers vs. divergers

· verbalizers vs. imagers

· holists vs. serialists

· deep vs. surface learning

· activists vs. reflectors

· pragmatists vs. theorists

· adaptors vs. innovators

· assimilators vs. explorers

· field dependent vs. field independent

· globalists vs. analysts

· assimilators vs. accommodators

· imaginative vs. analytic learners

· non-committers vs. plungers

· common-sense vs. dynamic learners

· concrete vs. abstract learners

· random vs. sequential learners

· initiators vs. reasoners

· intuitionists vs. analysts

· extroverts vs. introverts

· sensing vs. intuition

· thinking vs. feeling

· judging vs. perceiving

· left brainers vs. right brainers

· meaning-directed vs. undirected

· theorists vs. humanitarians

· activists vs. theorists

· pragmatists vs. reflectors

· organizers vs. innovators

· lefts/analytics/inductives/successive processors vs. rights/globals/deductives/simultaneous processors

· executive, hierarchic, conservative vs. legislative, anarchic, liberal

A variety of sites in the consumer industry, including VARK, Learning Styles Online, and Education Planner encourage students and learners to 'find their learning style,' exhibiting a) how wide and popular the notion has become in culture, and b) the ways that online inventory and profiling quiz culture can warp educational research. Instructors might prepare for their students to arrive in class with certain assumptions about their most efficient modes of learning.

Recommendations

Many instructors still gravitate towards the learning-styles framework because of its seeming intuitiveness and resonance with teaching experiences. A broader approach that invites students to reflect on their learning, rather than narrow their style down, has been shown to improve learning outcomes (Ambrose et. al, 2010).

Studying vs. Learning - Instructors can help students understand the difference between studying styles and learning processes. Students will develop their own preferences for reviewing content, but these practices differ from deeper cognitive processes like "chunking," building on prior knowledge, making conceptual connections, and transferring knowledge. Ambrose, et. al (2010) and the National Research Council (2000) offer excellent overviews of these deeper processes, and explain why multiple modes of instruction assist all students.

Students benefit from different kinds of instruction - Because learning requires complex, often uneven developmental steps like building on prior knowledge, forming conceptual structures slowly, and varieties of repetition, students benefit when instruction provides various ways to enter into learning. Alternating modes can serve different students' aptitude, level of self-awareness as a learner, and cultural background. Instructors should imagine students to be neither uniform, nor categorized, in their learning, but instead experiencing similar development through singular personalities and experiences. As such, instructors can incorporate active learning, group work, and inclusive teaching strategies to invite students to engage their full faculties and experience peer learning. Multiple modalities can assist all students regardless of proposed learning style: research shows, for instance, that students learn more deeply from words and visuals than from words alone. Multimedia presentation encourages active cognitive processing, promoting meaningful learning (Mayer 2003).

Students benefit from thinking about how they learn - Research shows that students benefit when given opportunities to reflect on assignments, exams, and activities, and that learning outcomes improve when instructors help students think about how they drew connections, digested content, or arrived at conclusions (Kaplan, et. al, 2013). This process of metacognition helps students think about their thinking, and helps students identify ways to improve their learning and avoid weak habits of thought or study.

Effective instructional methods can vary across disciplines and course content - Proposed learning styles do not always fit disciplinary norms; for example, writing courses benefit from a significant verbal component, geometry courses from a visual component, and lab classes from an experiential component. Instructors can be aware of predominant presentation styles in their discipline, and consider discipline-specific resources to widen their modes of instruction.

References

Ambrose, S., Bridges, M., Lovett, M., DiPietro, M., & Norman, M (2010). How Learning Works: 7 Research - Based Principles for Smart Teaching. San Francisco: Jossey-Bass.

Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. London, UK: Learning and Skills Research Centre.

Kaplan, M., Silver, N., Lavaque-Manty, D., and Meizlish, D., eds. (2013). Using Reflection and Metacognition to Improve Student Learning. Sterling, VA: Stylus.

Kirschner, PA. (2017). Stop propagating the learning styles myth. Computers & Education, 106: 166-171.

Mayer, RE. (2003). The promise of multimedia learning: using the same instructional design methods across different media. Learning and Instruction, 13(2): 125-139.

National Research Council. (2000). How People Learn: Brain, Mind, Experience, and School: Expanded Edition. Washington, DC: The National Academies Press.

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence. Psychological Science in the Public Interest, 9(3), 105-119.

Simmonds, A. (2014). How neuroscience is affecting education: Report of teacher and parent surveys. Wellcome Trust.

# data[].attributes.attachment_link.description
Examples In addition to the three core styles, over 71 separate learning-style instruments and theories have been documented in education literature (Coffield et al 2004). 30 popular ones include (Pashler 2008): · convergers vs. divergers · verbalizers vs. imagers · holists vs. serialists

# data[].attributes.attachment_link.readable_text
Doing several things poorly.

Multitasking refers to either the ability to pay attention to several pieces of information at the same time or the process of performing more than one task at the same time.

Can learners multitask?

In short, no. Multitasking is a misnomer, because what learners actually do is task-switch very quickly between tasks, while focusing their conscious attention on only one task. Depending on the type of tasks attempted and the level of automation of one of the tasks, learners - and faculty - may believe they can multitask.

Working memory has limits to how much information it can process (see Memory and Learning). While working memory creates a bottleneck for learning, there are two mechanisms that free up working memory and allow us to achieve much higher levels of cognition:

Automaticity
Working memory is freed after we have practiced tasks until they become unconscious or automated. Examples include playing music, driving in calm conditions, or chewing gum while walking.

Chunking
Working memory is freed up when individual pieces of information are bound together into a meaningful whole, referred to as a chunk. For example, the concepts of pollution, liberty, or Italian cooking are each single chunks even though they are composed of many smaller concepts. These chunks are then processed as individual pieces of information.

Task switching

When people are able to do multiple tasks at once, this is because at least one of their tasks has been automated, not because people are multitasking. Consider the following tasks:

Washing dishes while listening to music.

Driving in calm conditions while talking to a friend.

Reading a book while watching TV.

The first two examples are often easy to do because at least one of the tasks is carried out unconsciously (listening to music). The tasks in the last example cannot be automated because they require the person to make conscious decisions at unpredictable points. In these instances, if a person is attempting to do both tasks at once they are actually switching back and forth quickly between tasks. In the first two examples, one of the tasks may at some point require decisions and task switching will occur as well. For example, if while driving an accident occurs in front of you, you would be unable to continue your conversation because your working memory will be focused on driving to avoid the accident.

Effects of Task Switching

Task switching is usually an inefficient way to accomplish multiple tasks, and can have negative consequences for both how well the task is done and for the person attempting the task. The following are mainly correlational findings from a broad range of research on the costs of task-switching:

Grades and Studying

Facebook
When studying and using Facebook users report lower GPA; 74.3% said it impacts their grades, yet they still use it anyway (Kirschner & Karpinski, 2010)

Instant Messaging
More than half of respondents report a detrimental effect on schoolwork when also using instant messaging (Junco & Cotton, 2011).

Homework
Students reported that doing homework while trying to multitask took significantly longer; had lower GPA scores; and learned less (Bowman et al., 2010; Rosen et al., 2013; Pool et al., 2000)

Cognitive Challenge
Learners use less demanding & accurate cognitive strategies when trying to multitask (Hoffman et al., 2013; Mueller & Oppenheimer, 2014)

Emotional Well-being

Multitasking is associated with negative well-being, higher depression and anxiety (even after controlling for neuroticism, extroversion, and overall media use), and higher socio-emotional difficulties (Pea et al., 2012; Becker et al., 2013; Cheever et al., 2014; Loh et al., 2014)

Effects on the Brain

Multitasking is associated with smaller gray matter density in anterior cingulate cortex (ACC), which is responsible for managing cognitive control. This makes the learner more susceptible to interference from distractions, and worse at task switching (Loh et al., 2014; Ophir et al., 2009)

Processing Ability While Texting and Driving

Reaction times at 70mph:

15 extra feet to stop when drunk.

30 extra feet to stop when texting (Austin, 2009).

Reaction times overall:

12% worse when drinking.

21% worse when high.

35% worse when texting (Reed & Robins, 2008).

Suggestions for Learning

Because of the variety of negative consequences for both the learner and the quality of learning, students should avoid task-switching when learning and studying.

The Pomodoro Technique is one method for teaching students to focus on individual tasks. Students set a timer for 25 minutes and work only on the assigned task. If they feel distracted by a thought or urge, they write the thought down for later and continue with the main task. They then rest for 5 minutes and repeat. This process promotes self-regulation by requiring students to track how much time they put towards a task and making them aware of how often they become distracted while working

Implications for Teaching

The main implication for teaching is to create experiences where students do not need to task switch. The two main areas are:

Conflicting Content
It is important to deliver content in a way that does not ask students to do multiple tasks. For example, when presenting a PowerPoint slide, students may need to copy information for their exam, while at the same time you want them to listen and consider what you are saying. The Multimedia Learning page presents examples and solutions for situations like this.

Computers in the Classroom
Because computers offer easy distractions to students, faculty should explicitly design a policy on when computer use in their course is appropriate. Faculty can require use only at specific times for class-related work, and should stipulate clear consequences

Austin, M. (2009, June). Texting While Driving: How Dangerous is it? Retrieved August 11, 2016, from http://www.caranddriver.com/features/texting-while-driving-how-dangerous-is-it

Basak, C., & Verhaeghen, P. (2011). Three layers of working memory: Focus-switch costs and retrieval dynamics as revealed by the N-count task. Journal of Cognitive Psychology, 23(2), 204-219. https://doi.org/10.1080/20445911.2011.481621

Becker, M. W., Alzahabi, R., & Hopwood, C. J. (2013). Media Multitasking Is Associated with Symptoms of Depression and Social Anxiety. Cyberpsychology, Behavior, and Social Networking, 16(2), 132-135. https://doi.org/10.1089/cyber.2012.0291

Bleckley, M. K., Durso, F. T., Crutchfield, J. M., Engle, R. W., & Khanna, M. M. (2003). Individual differences in working memory capacity predict visual attention allocation. Psychonomic Bulletin & Review, 10(4), 884-889.

Bowman, L. L., Levine, L. E., Waite, B. M., & Gendron, M. (2010). Can students really multitask? An experimental study of instant messaging while reading. Computers & Education, 54(4), 927-931.

Cheever, N. A., Rosen, L. D., Carrier, L. M., & Chavez, A. (2014). Out of sight is not out of mind: The impact of restricting wireless mobile device use on anxiety levels among low, moderate and high users. Computers in Human Behavior, 37, 290-297. https://doi.org/10.1016/j.chb.2014.05.002

Garavan, H. (1998). Serial attention within working memory. Memory & Cognition, 26(2), 263-276.

Hoffmann, J. A., von Helversen, B., & Rieskamp, J. (2013). Deliberation's Blindsight How Cognitive Load Can Improve Judgments. Psychological Science, 24(6), 869-879.

Junco, R., & Cotten, S. R. (2011). Perceived academic effects of instant messaging use. Computers & Education, 56(2), 370-378. https://doi.org/10.1016/j.compedu.2010.08.020

Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in human behavior, 26(6), 1237-1245.

Loh, K. K., & Kanai, R. (2014). Higher media multi-tasking activity is associated with smaller gray-matter density in the anterior cingulate cortex. Plos one, 9(9), e106698.

Mueller, P. A., & Oppenheimer, D. M. (2014). The Pen Is Mightier Than the Keyboard Advantages of Longhand Over Laptop Note Taking. Psychological Science, 25(6), 1159-1168.

Ophir, E., Nass, C., & Wagner, A. D. (2009). Cognitive control in media multitaskers. Proceedings of the National Academy of Sciences, 106(37), 15583-15587.

Pea, R., Nass, C., Meheula, L., Rance, M., Kumar, A., Bamford, H., ... Zhou, M. (2012). Media use, face-to-face communication, media multitasking, and social well-being among 8- to 12-year-old girls. Developmental Psychology, 48(2), 327-336. https://doi.org/10.1037/a0027030

Pool, M. M., van der Voort, T. H. A., Beentjes, J. W. J., & Koolstra, C. M. (2000). Background television as an inhibitor of performance on easy and difficult homework assignments. Communication Research, 27(3), 293-326.

Reed, N., & Robbins, R. (2008). The Effect Of Text Messaging On Driver Behaviour: A Simulator Study (No. PPR 367). London, England: Transport Research Laboratory.

# data[].attributes.attachment_link.description
Doing several things poorly. Multitasking refers to either the ability to pay attention to several pieces of information at the same time or the process of performing more than one task at the same time. Can learners multitask? In short, no.

# data[].attributes.attachment_link.provider_name
Faculty Focus | Higher Ed Teaching & Learning

# data[].attributes.attachment_link.readable_text
I was wrapping up a presentation on memory and learning when a colleague asked, "How do we help students learn in courses where there's a lot of memorization?" He explained that he taught introductory-level human anatomy, and although the course wasn't all memorization, it did challenge students' capacity to retain dozens of new terms and concepts.

The question itself is tricky because most teaching professionals are heavily invested in the idea that learning isn't about being able to regurgitate facts on an exam. We also worry, and with good reason, that emphasizing rote learning steals time and effort away from the deeper thinking that we want students to do. But in my work I've come to realize that memorization deserves some airtime because it is one important route to building content knowledge and expertise. Furthermore, acquiring content knowledge doesn't have to detract from critical thinking, reasoning, or innovation-rather, it can complement all these. Cognitive scientists are making new discoveries all the time about the connections between memory and processes such as drawing inferences, making predictions, and other skills that make up the ability to think like an expert in a discipline.

So what techniques target this specific teaching and learning challenge? We're all familiar with mnemonics such as the first-letter technique-using a word such as RICE (rest, ice, compression, elevation) or a catchy phrase (Every Good Boy Does Fine) to remember a sequence of information. Mnemonics are one good tool, but what else can we offer?

Learning isn't about being able to regurgitate facts on an exam, but memorization deserves some airtime because it is one important route to building content knowledge and expertise

For starters, we should convey to students (and keep in mind ourselves) that memorization challenges nearly everyone because the mind simply isn't set up to take in reams of disjointed facts. Our memory systems evolved to be picky about what we remember, selecting the information that is most relevant to our goals and discarding the rest. Understanding this helps us and our students have realistic expectations about the level of effort needed to succeed.

It also helps to understand how we create memories for words, because many memorization tasks involve scientific terms, foreign language vocabulary, and the like. How we do this has been hotly debated among researchers, but one view is that we rely on a special piece of mental machinery called the phonological loop that holds speech sounds.

If you've ever muttered a phone number to yourself while you ran around looking for a pencil to write it down with, you've experienced the phonological loop in action. But recycling phone numbers isn't the phonological loop's main reason for existing. Rather, its real job kicks in when we run into a word we haven't heard before. When this happens, the phonological loop grabs onto the sequence of sounds and keeps it fresh while other memory systems set up representations of what the new word means. The catch is that phonological loop capacity varies fairly substantially from individual to individual. This means that words of three, four, or more syllables overwhelm some people's ability to learn new words on the fly.

With these two points in mind-that memory doesn't handle disjointed facts well and new vocabulary hinges on one sometimes-shaky mechanism within memory-here are some ways to help students manage memorization:

Emphasize context and purpose. Ask yourself why students are being asked to memorize these facts in the first place. If students can readily answer that question and if they can picture future situations in which they will use the information, they will be better primed to remember it.

Break down new vocabulary words, especially those that are more than two syllables long. Allow time to rehearse and remember the first couple of syllables before tacking on later ones. Also keep in mind that this process will be easier for some students than others due to wide variation in phonological loop capacity; you may want to design in a "mastery learning" or other individualized approach for vocabulary so that students can move through at their own pace.

Visualize information. For most people, imagery is highly memorable, perhaps because so much of the brain is devoted to visual processing. Memory champions, such as the ones populating the best seller Moonwalking with Einstein, use elaborate visualization strategies to achieve incredible feats of memorization. Similarly, strategies such as the keyword mnemonic work by linking word sounds to images (such as using an image of a cowboy on a horse to remember the Spanish word "caballo," which sounds a bit like "cowboy").

Take advantage of the "Big Three" applied memory principles-testing, spacing, and interleaving. Briefly, these refer to the facts that quizzes are a great way to study and that we do best when we spread out our study sessions and alternate between different topics. Tackling a big memory project such as human anatomy means we need every advantage we can get, and dozens of research studies have supported these three as producing the biggest memory payoff for the time invested.

Avoid the rereading trap. Students tend to fall into passively reviewing material, and in doing so they miss the key advantage of techniques such as testing: retrieval practice. Retrieval practice strengthens memory, but it works only when we actively challenge memory. Flash cards, a favorite student strategy, are fine as long as students use them to actively quiz themselves.

It's okay to expect students to learn the facts and terms needed to become experts in a discipline. With an understanding of memory and some strategies to share, we can make this side of learning productive and maybe even painless-but certainly at least less painful.
Michelle Miller is a professor in the Department of Psychological Sciences at Northern Arizona University.
Reprinted from The Teaching Professor, 28.9 (2014): 3. © Magna Publications. All rights reserved.

# data[].attributes.attachment_link.title
Helping Students Memorize: Tips from Cognitive Science

# data[].attributes.attachment_link.description
Although there is more to learning than regurgitating facts on an exam, memorization is an important route to building content knowledge and expertise.

# data[].attributes.attachment_link.description
The Metacognitive Awareness Inventory (MAI) measures the two main components of metacognition; metacognitive knowledge and metacognitive regulation. In this study, college students took the MAI and their academic achievement for the semester was assessed. The results showed that metacognitive knowledge and regulation was related to their overall GPA and their current semester course grades.