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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.

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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.

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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.

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How To Practice Effectively, According To Science

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

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Jay McTighe has a varied career in education. He served as director of the Maryland Assessment Consortium, a collaboration of school districts working to develop and share formative performance assessments and helped lead standards-based reforms at the Maryland State Department of Education. Prior to that, he helped lead Maryland's standards-based reforms, including the development of performance-based statewide assessments.

Well known for his work with thinking skills, McTighe has coordinated statewide efforts to develop instructional strategies, curriculum models, and assessment procedures for improving the quality of student thinking. He has extensive experience as a classroom teacher, resource specialist, program coordinator, and in professional development, as a regular speaker at national, state, and district conferences and workshops.

McTighe is an accomplished author, having coauthored more than a dozen books, including the award-winning and best-selling Understanding by Design® series with Grant Wiggins. He has written more than 50 articles and book chapters and has been published in leading journals, including Educational Leadership (ASCD) and Education Week.
UNDERSTANDING BY DESIGN® and UbD® are registered trademarks of Backward Design, LLC used under license.

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Upgrade Your Teaching: Understanding by Design Meets Neuroscience

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How can educators leverage neuroscience research about how the human brain learns? How can we use this information to improve curriculum, instruction, and assessment so our students achieve deep learn

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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.

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Can millennials pay attention to classwork while texting, tweeting and being on Facebook?

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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?

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how can i get this module for my class on D2L

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how can i get this module for my class on D2L

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Inside Higher Ed | Higher Education News, Events and Jobs

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Attention is how the mind prioritizes. The brain's attention circuits stay busy throughout our waking hours, directing on a millisecond-by-millisecond basis where our limited cognitive resources are going to go, monitoring the information that floods into our senses, and shaping conscious experience. Attention is one of the most mysterious and compelling topics in cognitive science. Years of research on the subject are now paying off handsomely in the form of recent advances in our understanding of how these mechanisms work, on both theoretical and physiological levels. And the more we learn, the more we realize that these findings aren't just important for theory-building -- they offer myriad practical applications that can help people function more effectively across all aspects of life. Teaching and learning is one area where attention research is especially useful for helping us get better at what we do.

In my book Minds Online: Teaching Effectively with Technology, I foreground attention as the starting point for everything designers of college-level online learning experiences should know about human cognition. Without attention, much of what we want students to accomplish -- taking in new information, making new connections, acquiring and practicing new skills -- simply doesn't happen. And thus, gaining students' focus is a necessary first step in any well-designed learning activity, whether online or face-to-face.

But how does this principle play out in a contemporary learning environment littered with tempting distractions -- the smartphones that accompany students to class, social networks that let us reach out to friends around the clock, the sites for games, media, and shopping that beckon every time we open our browsers? It's especially concerning given how overly optimistic people tend to be about their ability to juggle different tasks. As psychologists Christopher Chabris and Daniel Simon eloquently explain in The Invisible Gorilla: And Other Ways Our Intuitions Deceive Us, human beings are notoriously bad at knowing what we can handle, attention-wise. Essentially, we lie to ourselves about what we notice and what we know, believing that we take in much more that we actually do.

For our students, this adds up to a serious drain on learning. And as learning environments become more complex, it is a drain they can't afford. Consider, for example, some forms of blended learning in which students master foundational knowledge outside of class, usually through online work, then spend class time on focused application and interaction with instructors and classmates. A tightly scheduled and synchronized system like this can work beautifully, but doesn't allow much margin of error for wasted time and scattered focus.

So what can we do about this situation? One strategy is to educate students about the limits of attention and just how much they miss when they choose to multitask. This, however, is easier said than done. Incorporating a learning module on attention is straightforward enough, but what would it take for such a module to be effective? First, it would need to be brief and to the point, reinforcing just a few crucial take-home messages without a great deal of history, theory or other background more appropriate to a full-length course in cognition. At the same time, quality control would be a major concern, especially for the module to be usable by an instructor without academic training in cognitive psychology. Just Googling for materials on attention brings up at least as much pseudoscience as reputable work, and without this solid scientific grounding, a module on the dangers of multitasking could easily devolve into a "Reefer Madness"-style experience, more laughable than persuasive.

Keeping these caveats firmly in mind, I've worked with my instructional designer colleague John Doherty to create a free-standing, one-shot online learning module called Attention Matters that instructors can drop into existing courses as an extra credit or required assignment. Besides being scrupulous about the science, John and I prioritized interactivity and use of the multimedia capabilities of online learning -- enabling us to show students, not just tell them, what distraction can do to performance in different contexts. Too many online learning activities consist essentially of glorified PowerPoint slides, so although there is a certain amount of text within our module, we put most of the emphasis on media, demonstrations, self-assessment and discussion.

As an example, we used a demonstration we called the "Selective Reading Challenge" to show students how attention mechanisms constantly filter incoming information, and also, how little we remember of information we don't attend to. The demonstration consists of a page of text, alternating lines of bold and regular typefaces. Students are instructed to pay attention to only the bold lines, ignoring everything else, then proceed immediately to the next page. In the "to be ignored" text, we hide a few stimuli that may break through to awareness -- a couple of common names (Michael, Emily, Stephen, Christina), that if they belong to you, will probably pop out, as well as a few attention-grabbing emotional terms (911, murder). After completing the "selective reading," students are invited to go back review the entire page of text -- bold and regular -- to see what they missed, and what they (likely) don't remember at all even though it was well within the field of vision.

Other demonstrations illustrate the dramatic slowdown in processing that takes place when we multitask among competing activities. We present an online version of the classic "Stroop effect" to illustrate how distraction -- even from other mental processes going on at the same time -- can make a simple activity slow and inaccurate. The task involves naming the colors of a sequence of multicolored words -- not a difficult task, except when the words are themselves color names. red, green, blue, and so on - that contradict the colors they are printed in. Lastly, we pulled in several video clips from around the Web to drive home the multitasking point. One shows a prank "driving test" in which unsuspecting students were told to text while navigating a practice course, with predictably disastrous results. Another classic clip called "The Amazing Color Changing Card Trick," created by psychologist Richard Wiseman, dramatically illustrates how attending to one part of a scene causes us to miss major developments going on in practically the same location.

These videos, activities and demonstrations form the anchor for brief, impactful student learning activities throughout the module. Students respond to discussion prompts asking them whether the demonstrations worked on them as predicted, and what they may mean for everyday attention. They also complete self-quizzes with feedback that target the different learning outcomes for each part of the module. At the end, they revisit what they have learned in a brief self-reflection and survey on attitudes and beliefs about attention and its importance for learning.

Attention Matters is an exciting project, offering us the opportunity to apply cognitive science in a novel and - we hope - useful way. The project also has a research component, through which we will be gathering data on student attitudes and beliefs about their own attentional capabilities, as well as on the frequency of different multitasking behaviors in their own lives.

There's another important side to Attention Matters, and that has to do with the collaboration between an instructional design expert and a Subject Matter Expert, or SME. Much has been written about the virtues of instructional design experts' pairing up with SMEs, and yet, such collaborations remain fairly rare within higher education. We hope that this project demonstrates the real benefits to be gained - perhaps motivating others to take the plunge.

It's still too early to know what the long-term impacts of Attention Matters are going to be, or to predict exactly what we might discover about student attitudes and behaviors around multitasking. But I do foresee that as seismic change continues to occur in higher education, we will see more educators entering similar new territory - collaboratively creating focused, technologically delivered learning modules that live outside of traditional courses and use learning theory and cognitive science as the basis for design. And in our case, we may be able to add to our arsenal of strategies for getting students to become better stewards of their own attention.

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Essay calls for professors to start teaching students about distraction and attention

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It's time for professors to move beyond complaining about how students are distracted by social media, writes Michelle Miller. Faculty members need to teach about why attention matters.

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RED, you should say "Blue."
As soon as the words appear on your screen, read the list as fast as you can. When you have finished, click on the "Finish" button. The time it took you to read all of the words will be shown. If you want to try the same set of words, click on the "reload" button of your browser. If you want to continue with the experiment, click on "Continue Experiment."

Go to the first test.

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RED, you should say "Blue."As soon as the words appear on your screen, read the list as fast as you can. When you have finished, click on the "Finish" button. The time it took you to read all of the words will be shown.

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"Critical thinking instruction must also address student dispositions. It is not enough to teach college students the skills of critical thinking if they are not inclined to use them. Critical thinking is more than the successful use of the right skill in an appropriate context. It is also an attitude or disposition to recognize when a skill is needed and the willingness to exert the mental effort needed to apply it."

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Adam Grant: The surprising habits of original thinkers

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How do creative people come up with great ideas? Organizational psychologist Adam Grant studies "originals": thinkers who dream up new ideas and take action to put them into the world. In this talk, learn three unexpected habits of originals -- including embracing failure.

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Retrieval practice is a mental struggle ( a "desirable difficulty" for long-term learning), which means it can also be frustrating. Contrary to what your students might feel, there is always something they can retrieve. Here are 4 steps you can take to scaffold an in-class retrieval practice activity:

1. Remind students that we all need time to think. A reminder for you and your students: the mental struggle during retrieval practice is good for learning, whereas easy learning is easy forgetting. Telling students to "try harder" isn't going to help. Validate that retrieval is hard, remind them that taking a "mental moment" will boost their long-term learning, and don't skip the think step during think-pair-share.

2. Encourage students to sit with the struggle a little longer. We have the natural temptation to jump in and help students as soon as they struggle, but this is a disservice to them and their learning. Instead, give students a clear instruction to try for another minute, and use a clock or timer to make sure you give them the full minute. (I'm a fan of radial timers .)

3. Emphasize that silence is golden. It'll feel awkward for you and your students to sit in complete silence during step #2. We have an ingrained belief that students must be talking in order to be engaged. Quite the contrary! We think best and engage in learning when there aren't distractions (some of my students close their eyes to help them think). Plus, once your students experience a minute of silent retrieval practice, you'll be surprised by how quickly they get used to it and then ask for more silent time to retrieve.

4. Give your students a retrieval cue. A retrieval cue isn't necessarily a hint, but a reminder that might lead to that "ah ha!" feeling when something comes to mind. For example, I asked my students to retrieve what they learned when we discussed implicit bias a few weeks ago. If they draw a blank, a retrieval cue I provide is "reliability and validity." That "cues" their memory without giving them a direct hint (we discussed the implicit association test). In the same way, if you ask students to retrieve what they learned in class and they can't remember, give them a one-word or two-word cue. Avoid the temptation to give students the answer.

What should you do when some students retrieve more quickly than other students? Ask them to retrieve more! If you had your students retrieve , ask the students who finished first to add one or more new things to their list.

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What should you do when your students can't retrieve anything? - Retrieval Practice

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Do your students' minds go blank during an in-class retrieval practice activity? Here are 4 steps you can take to help your students retrieve something.

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The movie "Inside Out" (2015) takes us inside the mind of its young protagonist, an 11-year-old girl named Riley, and depicts memory in a way that is sure to resonate with many people. In Riley's mind, her memories are objects - globes colored with emotions - that are stored in a mental space, just as physical objects are stored in a physical space. When Riley experiences an event and creates a new memory, a new globe is produced in her mind, rolling down a ramp like a ball returning in a bowling alley. When Riley re-experiences a past event, a globe is placed in a projector and events are replayed, projected on a screen in her mind. Cognitive psychologists refer to the mental processes involved in the creation of new memories and the recovery of past memories as encoding and retrieval, respectively. The depiction of the mind in "Inside Out" follows centuries of thought on how mind and memory work. Throughout history, scholars have used a common metaphor to talk about memory: The mind is a vast storehouse or space; memories are objects stored in that space; and retrieving a memory is akin to searching for and finding an object in a physical space (Roediger, 1980). To learn something new, according to this view, the challenge lies in getting knowledge "in" one's mental space. Getting it back "out" when needed is important, too, but learning is usually identified with the encoding of new knowledge in memory. Retrieval is assumed to be neutral for learning; retrieval is needed to assess what a person has learned, but retrieval processes themselves are not thought to produce learning. Recent advances in the science of learning and memory have challenged common assumptions about how learning happens. Specifically, recent work has shown that retrieval is critical for robust, durable, long-term learning. Every time a memory is retrieved, that memory becomes more accessible in the future. Retrieval also helps people create coherent and integrated mental representations of complex concepts, the kind of deep learning necessary to solve new problems and draw new inferences. Perhaps most surprisingly, practicing retrieval has been shown to produce more learning than engaging in other effective encoding techniques (Karpicke & Blunt, 2011). This approach, which recognizes the central role of retrieval processes in learning and aims to develop new learning strategies based on retrieval practice, is referred to as retrieval-based learning.
Retrieval Creates Learning:
Research dating back a century has shown that retrieval contributes to learning (for a historical review, see Roediger & Karpicke, 2006a), but the past decade has seen a renewed, intense focus on exploring the benefits of retrieval for learning. This recent research has established that repeated retrieval enhances learning with a wide range of materials, in a variety of settings and contexts, and with learners ranging from preschool ages into later adulthood (Balota, Duchek, Sergent-Marshall & Roediger, 2006; Fritz, Morris, Nolan & Singleton, 2007). A word-learning experiment illustrates some key points about retrieval-based learning. In the experiment (Karpicke & Bauernschmidt, 2011), students learned a list of foreign language words (e.g., Swahili vocabulary words like "mashua - boat") across cycles of study and recall trials. In study trials, the students saw a vocabulary word and its translation on the computer screen, and in recall trials, they saw a vocabulary word and had to recall and type its translation. The students studied a list of vocabulary words, then attempted to retrieve the whole list, studied it again, retrieved it again, and so on across alternating study and retrieval practice blocks. There were several different conditions in the experiment. In one condition, students simply studied the words once, without trying to recall them at all. In a second condition, students continued studying and recalling the words until they had recalled all of them once. After a word was successfully retrieved once, it was "dropped" from further practice - the students did not see it again in the learning session. Other conditions in the experiment examined the effects of repeated retrieval practice. Once a word was recalled, the computer program required the students to practice retrieving the items three more times. One repeated retrieval condition had the three recall trials happen immediately, three times in a row. This condition, referred to as massed retrieval practice, is akin to repeating a new piece of information over and over in your head right after you experience it. Finally, in the last condition highlighted here, the students also practiced retrieving the words three times, but the repeated retrievals were spaced throughout the learning session. For instance, once a student correctly recalled the translation for mashua, the program moved on to other vocabulary words, but prompts to practice retrieval of the translation for mashua would pop up later on in the program. In this way, the retrieval opportunities were spaced throughout the learning session. The key question in this research was, how well would students remember the vocabulary word translations in the long term? Figure 1 shows the proportion of translations that students remembered one week after the initial learning session. Merely studying the words once without ever recalling them produced extremely poor performance (average recall was 1 percent, barely visible on the figure). Practicing until each translation was recalled once was much better. But what about the effects of repeated retrieval practice? Massed retrieval - repeating the translations three times immediately - produced no additional gain in learning. Repeated retrieval enhanced learning only when the repetitions were spaced, and indeed, the effects of repeated spaced retrieval were very large. In a single experiment, simple changes that incorporated spaced retrieval practice took performance from nearly total forgetting to extremely good retention (about 80 percent correct) one week after an initial learning experience (see also Karpicke & Roediger, 2008; Pyc & Rawson, 2010).

Figure 1. Data from Karpicke & Bauernschmidt (2011).

Retrieval Practice is Underappreciated as a Learning Strategy:
If retrieval practice is such a potent learning strategy, one would hope that many learners would practice retrieval to learn many different things in many situations. However, as noted earlier, retrieval is not typically considered an important part of the learning process, and unfortunately, many learners do not practice retrieval as often or as effectively as they could. An emphasis on getting knowledge in memory shows up on surveys of students' learning strategies. In one survey (Karpicke, Butler & Roediger, 2009), college students were asked to list the strategies they use while studying and to rank-order the strategies. The results, shown in Figure 2, indicate that students' most frequent study strategy, by far, is repetitive reading of notes or textbooks. Active retrieval practice lagged far behind repetitive reading and other strategies (for a review of several learning strategies, see Dunlosky, Rawson, Marsh, Nathan & Willingham, 2013). A wealth of research has shown that passive repetitive reading produces little or no benefit for learning (Callender & McDaniel, 2009). Yet not only was repetitive reading the most frequently listed strategy, it was also the strategy most often listed as students' number one choice, by a large margin.

Figure 2. Student study strategy usage. Survey data from Karpicke, Butler, & Roediger (2009).

Why don't learners use repeated retrieval practice more frequently? Many students view retrieval as a "knowledge check"; they test themselves to see if they know something, rather than out of the belief that practicing retrieval itself will help them learn. This means that many students will use a "one-and-done" strategy: If they can recall something once, they believe they have learned it, so they remove it from further practice. Many students study this way when they regulate their own learning (Karpicke, 2009), even though their long-term learning will not benefit from repeated retrieval practice. Instead, a one-and-done strategy will produce long-term performance similar to the recall-once condition in Figure 1. There is some evidence that instructing learners about the benefits of retrieval leads students to report using retrieval practice more frequently when they study on their own (Einstein, Mullet & Harrison, 2012), but the best ways to influence students to practice retrieval remain to be discovered.
Practicing Retrieval Promotes Meaningful Learning
Perhaps another reason retrieval practice is not used more widely is because repeated retrieval may seem like "rote learning." Rote learning - simple memorization based on repetition - is short-lived, poorly organized and does not support the ability to transfer knowledge, make inferences or solve new problems. The outcome of rote learning is obviously not what students and educators aim for. Meaningful learning is essentially the opposite of rote learning: It is long-lasting and durable, coherent and well organized, and supports transfer, inferencing and problem solving. In fact, the past decade of research on retrieval-based learning has firmly established that retrieval practice promotes meaningful learning. Retrieval-based learning may be a more effective means of achieving meaningful learning than other popular active learning strategies. In one example of this (Karpicke & Blunt, 2011), students studied educational texts about science topics using one of two strategies. In a retrieval practice condition, students read a text, then set it aside and spent time recalling and writing down as much as they could remember from it (Roediger & Karpicke, 2006b). They then reread the text and recalled it a second time. In a second condition, students created concept maps while they read the texts. Concept maps are node-and-link diagrams that require learners to think about the relational and organizational structure of materials (Novak, 2013). The students spent the same amount of time studying in the two conditions; the difference was whether they created concept maps or practiced actively retrieving while learning. Figure 3 shows the results of two different final assessments given one week after the learning session. On one assessment, students answered two types of short-answer questions aimed at measuring meaningful learning: verbatim questions, which assessed concepts stated directly in the texts, and inference questions, which required students to make new connections across concepts. On another assessment, the final assessment involved creating a concept map, because concept mapping is often used as an assessment of the coherence and integration of students' knowledge. On the final verbatim and inference questions and on the final concept map assessment, practicing retrieval during learning produced the best performance, even better than studying the material by making concept maps.

Figure 3. Data adapted from Karpicke & Blunt (2011) (from Figure 2, panels A and C).

Several additional studies have established that retrieval practice promotes meaningful learning. Retrieval practice enhances the learning of educationally relevant materials, including educational texts, multimedia presentations, material explained in classroom lectures and a variety of other complex concepts (Jensen, McDaniel, Woodard & Kummer, 2014; Johnson & Mayer, 2009; Larsen, Butler, Lawson & Roediger, 2013; Lyle & Crawford, 2011; Roediger, Agarwal, McDaniel & McDermott, 2011). Retrieval practice also supports students in making inferences, solving new problems and transferring knowledge (Butler, 2010; Chan, 2009; Hinze & Wiley, 2011; McDaniel, Howard & Einstein, 2009; Smith & Karpicke, 2014). Retrieval-based learning is an effective method for improving meaningful learning.
Creating Retrieval-based Learning Activities
Perhaps the best aspect of retrieval-based learning is that it is free. Although there are sophisticated tools that can be used to implement retrieval practice, like classroom clicker systems (Roediger et al., 2011) and other computer-based learning systems (Grimaldi & Karpicke, 2014; Lindsey, Shroyer, Pashler, & Mozer, 2014), retrieval practice does not require special equipment or technology. The essence of retrieval-based learning is taking material you are trying to learn, setting it aside, and spending time actively retrieving the information. Existing educational activities can be converted into retrieval-based learning activities. For instance, answering questions and taking quizzes are effective ways to practice retrieval. In some circumstances, students might answer questions on quizzes or practice worksheets by looking up answers in their notes or books, rather than by attempting to retrieve the answers. One study directly compared this type of open-book questioning to closed-book conditions in which students were required to retrieve the answers to questions rather than looking them up (Agarwal, Karpicke, Kang, Roediger & McDermott, 2008). Answering questions in open-book conditions led to more forgetting over one week than did attempting to retrieve the answers, closed-book and then studying the answers. In other words, closed-book quizzes, which required retrieval practice, were more effective than open-book quizzes, which did not require learners to engage in retrieval. Another study (Blunt & Karpicke, 2014) examined the effectiveness of using concept mapping as a retrieval practice activity. In the experiment, students read texts about science topics and then created concept maps either with or without viewing the texts. In other words, some students created maps while studying the texts whereas other students had to engage in retrieval to create their maps. On a short-answer assessment one week after the learning session, students did better when they had learned by creating concept maps without viewing the texts, as a retrieval practice activity, than by creating maps while studying the texts. Thus, educational activities can be enhanced when they involve retrieval-based learning.
Take Home Points About Retrieval-based Learning
This article has made the case for four take-home points about retrieval-based learning:

Retrieval is a learning event. Practicing retrieval is a simple and effective way to enhance long-term, meaningful learning.

Some effective learning strategies, like retrieval practice, are underutilized. Conversely, the most popular learning strategy among college students - repetitive reading - leads to very limited levels of learning.

When practicing retrieval, retrieve more than once and space your retrievals, rather than massing them all together. Self-testing as a knowledge check is a good idea, but don't stop at just one successful retrieval (one-and-done). Two or three additional spaced retrievals will bolster long-term learning.

Retrieval can happen in a variety of ways, and many existing activities may be converted into retrieval-based learning activities. The key ingredient is to spend time actively retrieving when trying to learn something new.

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A powerful way to improve learning and memory

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The movie "Inside Out" (2015) takes us inside the mind of its young protagonist, an 11-year-old girl named Riley, and depicts memory in a way that is sure to resonate with many people. In Riley's mind, her memories are objects - globes colored with emotions - that are stored in a mental space, just as physical objects are stored in a physical space.

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What Is ‘Transfer of Learning’ and How Does It Help Students?

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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.

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L2L Strategy - Metacognition | Arizona Site

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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.

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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.

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Practice for knowledge acquisition (not drill and kill)

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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.