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How Can We Amplify Student Learning? The ANSWER from Cognitive Psychology

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How Can We Amplify Student Learning? The ANSWER from Cognitive Psychology

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Faculty Focus | Higher Ed Teaching & Learning

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In the early 2000s, anyone learning about pedagogy might have encountered "learning styles," a collection of theories that assert people learn differently, coupled with the advice to teach in ways that include visual, auditory, and/or kinesthetic learning.

We know now from rigorous testing in cognitive psychology that learning styles are really learning preferences that do not correlate with achievement (An et al., 2017). It turns out that learning happens similarly in fully-cognitive functioning learners, and it all has to do with brain processes that enable long-term memory. Books about study techniques built around learning science principles have proliferated in recent years (Carey; Sousa; Brown), with some now also tackling the strategies teachers can employ to encourage students to study more effectively (Zakrajsec; Willingham).

While cognitive science literature is exciting, it lacks a unifying structure to enhance practitioners' recall and application of the findings. To assist time-strapped instructional faculty and staff, we offer a consolidated summary of key cognitive science principles, in the form of an easy-to-remember acronym: ANSWER.

Attention: Learning requires memory, and memory requires focused attention. Multitasking is a myth, and even the more scientifically-accurate term "task-switching" yields errors compared to focused attention. The brain is quite adept at filtering out dozens of simultaneous stimuli, as it does every second of wakefulness. Attention is a required ingredient for learning. This has ramifications for syllabus policies on the use of electronic devices for note-taking, which have been shown to be irresistible and therefore lead to distraction and lower scores (Ravizza, Uitvlugt, and Fenn). Even when students are not distracted, laptops are used primarily for dictation, which does little for long-term memory; writing by hand does more to stimulate attention and build neural networks than typing (Mueller and Oppenheimer).

Novelty: The brain craves novelty. We scan the environment for anything new (and potentially dangerous). While an evolutionary advantage in a natural setting that might include predators, it also means that an overly-safe environment is one that the brain considers dull and unworthy of complete attention. By building variety into lesson plans, activities, and opportunities for practice, instructors amplify potential learning for their students. Further, the use of metaphors in teaching enhances transfer, hemispheric integration, and retention, so using picture prompts and images can further solidify student learning (Sousa).

Spacing: Sometimes called "distributed practice," the spacing effect refers to the jump in performance when students study a subject and then practice with gaps of time, ideally over one or more nights (sleep helps with memory consolidation), as compared to studying all at once, as if cramming the night before a test. Cramming, or massed practice, is successful for temporary test performance, since information is loaded into working memory. But the practices that work well for short-term memory do not work well for long-term memory. The spacing effect is particularly effective when combined with interleaving, the intentional practice of mixing in older learning tasks/skills with the new ones (Roedeiger, et al.). An ideal example of this would be regular quizzes in the semester that are cumulative (think "tiny final exams").

Why: Seasoned instructors frequently share context and meaning with students at the beginning of new unit or project, which leads to greater retention and mastery. Memory is associative; when new memories are formed, neurons wire together (and later fire together), so the context can lead to the information, and vice versa. A teaching strategy of comprised of questions to guide lesson plans (perhaps even beginning with mystery) can pique student interest and learning potential. If you use PowerPoint, Haiku Deck, or Prezi, do your slides consist primarily of answers or questions? Mixing these up (or intentionally beginning class with open-ended questions) allows students to connect with material and "start with why."

Emotions: Short-term memories are stored in the hippocampus, a portion of the brain associated with emotions; the same area where we consolidate short-term into long-term memories overnight. It's little wonder that students who dislike an academic subject have difficulty learning it! As instructors, we create the conditions in which students will motivate themselves (Ryan & Deci, 2000) by infusing our interactions with the positive emptions of curiosity, discovery, and fun. Simple gamification (quizzes with immediate feedback, for instance) can help.

Repetition: The creation of a new memory really means the formation of synapses across neurons and new neural pathways. These pathways and bridges degrade over time unless the synapse fires again. Consider the days before smartphones, when the way to remember a phone number was to repeat it several times mentally. Repetition, in all its forms, enables more effective recall later. This is why quizzing, practice testing, flashcards, and instructor-driven questioning and challenges are so effective.

A balanced approach to course design, assessment strategies, and lesson planning that incorporates the principles of ANSWER will enhance student engagement and help them focus on long-term learning. In practice, this results in chunked content experiences, varied formative assessment opportunities to practice learning, and a rigorous assessment structure that keeps students accountable on a cumulative basis. We'd love to hear other cognitive science-informed teaching strategies you've used in your courses in the comments.

References

An, Donggun, and Martha Carr. "Learning styles theory fails to explain learning and achievement: Recommendations for alternative approaches." Personality and Individual Differences 116 (2017): 410-416.

Bransford, John D., Ann L. Brown and Rodney R. Cocking. How People Learn: Brain, Mind, Experience and School. Washington D.C.: National Academy Press, 2000.

Brown, Peter, Roediger, Henry, and McDaniel, Mark. Make it Stick: The Science of Successful Learning. Cambridge, Harvard University Press, 2014.

Doyle, Terry, and Zakrajsek, Todd. The New Science of Learning. Sterling: Stylus, 2013.

Dunlosky, John, Rawson, Katherine, Marsh, Elizabeth, Nathan, Mitchell, and Willingham, Daniel. "Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology." Psychological Science in the Public Interest 12, no. 1 (2013): 4-58.

Mueller, Pam, and Oppenheimer, Daniel. "The Pen is Mightier Than the Keyboard: Advantages of Longhand Over Laptop Note Taking." Psychological Science. April 23, 2014. DOI: 10.11777/0956797614524581

Ravizza, Susan, Uitvlugt, Mitchell, and Fenn, Kimberly. "Logged in and Zoned Out: How Laptop Internet Use Relates to Classroom Learning." Psychological Science. December 20, 2016. DOI: 10.11777/0956797616677314

Rohrer, Doug. "Interleaving helps students distinguish among similar concepts." Educational Psychology Review 24 (2012): 355-367.

Ryan, Richard, and Deci, Edward. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American psychologist, 55, no.1 (2000

Sousa, David. How the brain learns. 4 th Ed. Thousand Oaks: Corwin Press, 2011.

Willingham, Daniel. Why don't students like school? San Francisco, Jossey-Bass, 2009.
Kevin Yee is the assistant dean of undergraduate studies at the University of South Florida, where he also serves as director of the Diane E. Boyd is the director of the Biggio Center for the Enhancement of Teaching and Learning at Auburn University. Academy for Teaching and Learning Excellence.

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How Can We Amplify Student Learning? The ANSWER from Cognitive Psychology

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In the early 2000s, anyone learning about pedagogy might have encountered "learning styles," a collection of theories that assert people learn differently, coupled with the advice to teach in ways that include visual, auditory, and/or kinesthetic learning. We know now from rigorous testing in cognitive psychology that learning styles are really learning preferences that do not correlate with achievement (An et al., 2017).

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A Brief History of the Science of Learning

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A Brief History of the Science of Learning: Part 2 (1970s-present) | Tokuhama-Espinosa | New Horizons for Learning

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A Brief History of the Science of Learning: Part 2 (1970s-present)

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How the brain processes information memory retention and learning

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How the brain processes information memory retention and learning(tracey tokuhama espinosa)

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Issuu is a digital publishing platform that makes it simple to publish magazines, catalogs, newspapers, books, and more online. Easily share your publications and get them in front of Issuu's millions of monthly readers.

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Research-Based Strategies to Ignite Student Learning

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by Judy Willis

The past two decades have provided extraordinary progress in our understanding of the nature of learning. Never before have neuroscience and classroom instruction been so closely linked. Because advances in technology enable us to view the working brain as it learns, educators can now find evidence-based neuroimaging and brain-mapping studies to determine the most effective ways to teach.

Brain Plasticity and Pruning

Learning causes growth of brain cells. For a long time, scientists held a misconception about brain growth: they believed it stopped at birth and was followed by a lifetime of brain cell death. Now we know that although most of the neurons where information is stored are present at birth, there is lifelong growth of the support and connecting cells that enrich the communication between neurons. These dendrites sprout from the arms (axons) or the cell body of the neuron.

Dendrites increase in size and number in response to learned skills, experience, and information. New dendrites grow as branches from frequently activated neurons. This growth is stimulated by proteins called neurotrophins. Nerve growth factor is one of these neurotrophins. Although the brain measurements of neurotrophins are highest during childhood (when the brain's connecting cells are undergoing their greatest growth and development), as students continue to learn, neurotrophin activity is elevated in the brain regions responsible for new learning (Kang, Shelton, Welcher, & Schuman, 1997).

Once these dendrites are formed, the brain's plasticity allows it to reshape and reorganize the networks of dendrite-neuron connections in response to increased or decreased use of these pathways (Giedd et al., 1999).

Examples of brain plasticity have been noted when people repeatedly practice activities controlled by parts of their visual, motor, sensory, or coordination systems for specialized learned activities. Blind people who read Braille have significantly larger somatosensory cortexes, where the sense of touch in their right fingers is processed. Similarly, violin players who use the fingers of their left hands to do the complicated movements along the strings have larger somatosensory regions in the area of their parietal lobe associated with the fingers of the left hand.

A 2004 report in Nature found that people who learned how to juggle increased the amount of gray matter in their occipital lobes (visual memory areas). When they stopped practicing the juggling, the new gray matter vanished. A similar structural change appears to occur in people who learn-and then don't practice-a second language. The decrease in connecting dendrites and other supporting brain connecting cells that are not used is called pruning. The loss of native language ability, juggling skills, or learned academic material that is not practiced is the flip side of the brain's growth response to learning. It is the "use it or lose it" phenomenon. The process is called "pruning" because the brain pathways and connections that are used regularly are maintained and "hard-wired," while others are eliminated, or pruned.

Pruning. Just as hedges are pruned to cut off errant shoots that don't communicate with many neighboring leaves, the brain prunes its own inactive cells. By the time we enter adolescence, our brain has chosen most of the final neurons it will keep throughout our adult life based on which cells are used and which are not.

Neurons are pruned when they are not used. Active cells require blood to bring nourishment and clear away waste, but cells that are inactive don't send messages to the circulatory system to send blood. (The brain cells receive circulation not from blood, as seen in the rest of the body, but rather from a colorless, filtered form of blood called cerebral spinal fluid.) This reduced blood flow means that calcium ions accumulate around the cell and are not washed away. This build-up of calcium ions triggers the secretion of the enzyme calpain, which causes cells to self-destruct.

The more ways something is learned, the more memory pathways are built. This brain research discovery is part of the reason for the current notion that stimulating the growth of more dendrites and synaptic connections is one of the best things teachers can learn to do for the brains of their students.

When children are between the ages of 6 and 12, their neurons grow more and more synapses that serve as new pathways for nerve signals. This thickening of gray matter (the branching dendrites of the neurons and the synaptic connections they form) is accompanied by thickening in the brain's white matter (fatty myelin sheaths that insulate the axons carrying information away from the neuron and making the nerve-signal transmissions faster and more efficient). As the brain becomes more efficient, the less-used circuits are pruned away, but the most frequently used connections become thicker, with more myelin coating making them more efficient (Guild, 2004).

Helping Students Grow More Brain Connections

In the classroom, the more ways the material to be learned is introduced to the brain and reviewed, the more dendritic pathways of access will be created. There will be more synaptic cell-to-cell bridges, and these pathways will be used more often, become stronger, and remain safe from pruning.

For example, offering the information visually will set up a connection with the occipital lobes (the posterior lobes of the brain that process optical input). Subsequently or simultaneously having students hear the information will hook up a dendritic circuit with the temporal lobes (the lobes on the sides of the brain that process auditory input and play an important role in the regulation of emotion and memory processing). This duplication results in greater opportunity for future cues to prompt the brain access to this stored information.

Multiple stimulations mean better memory. The more regions of the brain that store data about a subject, the more interconnection there is. This redundancy means students will have more opportunities to pull up all those related bits of data from their multiple storage areas in response to a single cue. This cross-referencing of data strengthens the data into something we've learned rather than just memorized.

For example, when we learn about our cars, we store the information in brain association areas under multiple categories that relate to the context with which new information about cars is learned. When we see a car, it goes into the visual image cortex. When we see the word C-A-R spelled out, that information goes into a language-association region. After learning about the internal combustion engine, the association is made with "jet and rocket engines are also powered by internal combustion." Later we build associational memories with the cars we've grown up with.

Because the information about cars is stored in multiple brain areas, and cross-referencing occurs among these areas when we think about cars, connecting networks of dendrites sprout among these memory storage areas. This circuitry permits multiple cues or stimuli to call forth all our car knowledge instantaneously. Just seeing the word "car" will put our recall systems online to provide all the stored data we have connected pertaining to cars. We may not need all that information, but because the associations activate these circuits, any of the stored information that we do need will be rapidly and efficiently accessible.

That is the reason for teaching important material through multiple learning pathways such as several senses (hearing, seeing, touching) as well as through several subjects (cross-curricular topics).

From enriched cages to enriched classrooms and curriculum. Even before plasticity was fully understood, neuroimaging laboratory research demonstrated how growing brains are physically shaped by experience. The brain sizes and weights of rats reared in standard cages were compared with those that lived in enriched cages (where the rats had more objects that they could manipulate). The rats reared in enriched environments had brains that were larger and heavier. Their dendrites, neural pathways, and connections were much longer and more complex, and the pathways branched out to more areas of their brains.

Chimpanzees living in enriched environments with stable social communities showed an increase in dendrite sprouting and synaptic connections in proportion to their increased ability to perform complex memory tasks, such as learning their way around a new maze. They also appeared to interact more positively with members of their group and to work more tenaciously on tasks and problems.

If a few pieces of metal in a rat cage and a stable community of chimps can do all that, think what educators can do in classrooms and with curriculum. In addition, building a supportive social classroom community, with enriched input from the environment, will result in more brain pathways and greater speed and efficiency of brain signals.

Educators as Memory Enhancers, Not Just Information Dispensers

There are many classifications of the types of memory, and the one presented here is a composite of several existing ones. From the most basic awareness of our environment, our memory skills progress to rote memory, working (short-term) memory, patterning and connections to relational memory, and ultimately, long-term memory storage.

Rote memory is unfortunately the most commonly required memory task for students in primary and secondary school. This type of learning involves "memorizing," and soon forgetting, facts that are often of little primary interest or emotional value to the student, such as a list of vocabulary words. Facts that are memorized by rehearsing over and over often don't have obvious or engaging patterns or connections. With nothing to give them context or relationship to each other or to the students' lives, these facts are stored in remoter areas of the brain. These isolated bits are more difficult to locate later because there are few nerve pathways leading to these remote storage systems.

Brain-based strategies can be used to reduce the amount of rote memorization required, and what remains can be less tedious because these strategies help students access and use more effective types of memory storage and retrieval.

The goal of research-based education is to structure lessons to ultimately rely less on inefficient and tedious rote memory. Helping students access and use more effective types of memory storage and retrieval will literally change their brains.

Working memory, or short-term memory, involves the ability to hold and manipulate information for use in the immediate future. Information is held in working memory for only about 20 minutes. The challenge students face is to move information from their working memories into their long-term memories. If they don't do this in about 20 minutes, that information can be lost. (Think about the last time someone gave you driving directions that seemed so clear when you heard them, but were lost to you once you made the second right turn.) To keep this newly learned material from slipping away, it needs to enter the network of the brain's wiring. Students can retain the new information by activating their previously learned knowledge that relates to the new material. This prior knowledge exists in stored loops of brain cell connections (circuits of neurons connected by branching axons and dendrites that carry the information as electrochemical signals). Effective teaching uses strategies to help students recognize patterns and then make the connections required to process the new working memories so they can travel into the brain's long-term storage areas.

Recall the first few times you learned and practiced a new computer process, such as making a Web page or using e-mail. At first you may have followed step-by-step written or verbal instructions. You possibly needed to rely on those instructions multiple times as you repeated the task, until one day, the process became automatic and you could even carry on a conversation while doing the job. That working memory was embedded by repetition into long-term memory, but it still needed periodic repetition for it to remain in your active memory bank and not gradually fade from disuse. Even if it did fade when you were away from your computer during summer vacation, however, the neuronal circuit or brain cell network that was created was still physically present in your brain, just like that hiking trail under the winter's snow. It was just in storage, like data taken off your computer desktop and put into the hard drive, and it took less time to refresh it than it did to learn it the first time.

Learning promotes learning. Engaging in the process of learning actually increases one's capacity to learn. Each time a student participates in any endeavor, a certain number of neurons are activated. When the action is repeated, such as when performing a follow-up science lab experiment or rehearsing a song, or when the information is repeated in subsequent curriculum, these same neurons respond again. The more times one repeats an action or recalls the information, the more dendrites sprout to connect new memories to old, and the more efficient the brain becomes in its ability to retrieve that memory or repeat that action.

Eventually, just triggering the beginning of the sequence results in the remaining pieces falling into place. This repetition-based sequencing is how you are able to do many daily activities almost without having to think about them, such as touch-typing or driving a car. The reason for this ability goes back to the construction and strengthening of those memory pathways in the brain.

Very few educators resort to having students learn only by rote memorization or limit instruction to only drill-and-kill worksheets day after day in hopes of imprinting material in students' brains. Teachers know from their own teaching experience how briefly that material remains accessible to students. Many teachers can recall occasions when they accidentally gave students a spelling list or math worksheet they had already completed, and the relatively large number of students who didn't instantly recognize that it was the identical work they did only a few weeks, or even days, before.

Now there are more ways to help students process information from lessons so it travels beyond temporary working memory and into memory storage. These strategies keep students interested in what they are learning. These lessons activate multiple senses and connect new information to multiple brain pathways into the memory storage areas. Successful brain-based teaching builds more connections and stronger circuits. Students will have more roadways to carry new information into their memory storage region and to carry out the stored knowledge when it is needed.

Build stronger memory circuits. Some of the strategies suggested by neuroimaging are ones that have students personalize information to be learned, thereby further activating the areas of the brain that help form memories. Others encourage students to connect with the information with as many senses as possible. They can visualize an electron orbiting the nucleus of an atom, mimic the buzz of electricity as it whizzes by, or feel a tingling associated with the electron's negative charge by rubbing a balloon against their arm and feeling their hair move. If they then draw a sketch of their visualizations and verbally communicate them to partners, or write about them in their own words, multiple brain pathways will be stimulated to enter long-term memory because they have personalized and interacted with the information.

Stimulate Their Senses

The brain may appear to be a tangled bundle of miles of nerve cell connections, but these bundles are in fact organized. From brain mapping we know that predictable tiny regions of the brain are where specific cognitive activities take place. Similarly, imaging has shown us that each of these locations is fed data from brain centers that collect information from the senses and emotions. When students build their working memories through a variety of activities, they are stimulating multiple sensory intake centers in their brains. Their brains develop multiple pathways leading to the same memory storage destination. By stimulating several senses with the information, more brain connections are available when students need to recall that memory later on. This means that the memory can be retrieved by more than one type of cue. If the learned information was taught with visual and auditory associations, it can be recalled by the students using either their sound or visual memory.

My teachers allowed me the exhilaration of my own discovery.

~ Robert Oppenheimer, on how he came to be a nuclear physicist

Surprise

Our brains are structured to remember novel events that are unexpected. Back to basic survival, success is often based on our ability to sense a cause and predict the effect. For example, we get out of the way when we see something being dropped from a roof above us because we predict the possibility of injury from the falling object. Because our brains are encoded to make and respond to predictions, they are particularly stimulated when they predict one effect and experience a different one.

Use surprise to bring students' brains to attention. Consider employing the technique of surprise to light up students' brains and illuminate the pathways to memory storage. Starting a lesson with an unanticipated demonstration or having something new or unusual in a classroom will spark student attention and curiosity. It can be anything from playing a song as they enter to greeting them in a costume. If students sense novel experiences from demonstrations descriptions, anecdotes, or even the enthusiasm in their teacher's voice, they will be more likely to connect with the information that follows.

To take advantage of their engaged state of mind, students should have opportunities to interact with the information they need to learn. The goal is for them to actively discover, interpret, analyze, process, practice, and discuss the information so it will move beyond working memory and be processed in the frontal lobe regions devoted to executive function.

Teachers don't always have to dialogue with individual students to prompt their being "in the moment" with the information, although that certainly worked well for Socrates. Strategies that can achieve these goals include partner discussions and Think-Pair-Share. Students can write dend-writes (a more enticing name for class notes that gives student note-taking more status).

They might add a sketch in their notebooks alongside their comments about the surprise, the new information they learned, and their personal response to it (What did I see/hear/smell? What did I learn? What surprised me? What do I want to know more about? What did this information remind me of?).

New Ways to Use Available Material

When the lesson is a more passive one, such as students reading a section of a textbook in class, teachers can improvise engaging strategies using resources already accessible. Well-crafted textbooks often include comprehension questions at the end of each chapter. However, in the age of interactive computers and video games, the textbook is not likely to grab students' enthusiastic interest without some help from their teacher. Teachers can select some of the text's more thought-provoking questions, the more open-ended questions that prompt connections to previous experiences or learning, and those that encourage students to consider their personal opinions. Instead of assigning the rather tedious, passive homework task of having students read a question, then search the chapter or their notes for "the right answer," teachers can create classroom opportunities to bring these questions to life.

To stimulate more memory circuits, students can use these chapter questions to interview a partner as if for a television news show. They can sketch an abstract representation in response to a concept question (What would the Big Bang or infinity look like?).

It might seem boring or pointless to students if you ask them to check their own notes for accuracy, but with proper teacher modeling to demonstrate respectful and constructive peer editing, students can read the notes of partners and advise them on what they missed. They are also likely to find information in their partner's notes that they will want to add to their own. After any of these activities, partners can "nominate" their classmate's sketch, notes, or interview comments to be shared with the entire class. When teachers have taken steps to engage students' interest long enough for new information to pass from awareness into working memory, students' brains can take over, and these meaningful patterns and memorable connections will penetrate through the brain circuits to relate to and build upon existing stored memory pathways.

Episodic Memory and Experiential Learning

Decades ago, my high school chemistry teacher slowly released hydrogen sulfide (rotten egg smell) from a hidden container he opened just before we entered his classroom. A few minutes after we took our seats and he began his lecture, a foul odor permeated the classroom, grabbing our attention. We groaned, laughed, and looked around for the offending source. To an outside observer entering our class at that time, we would have appeared unfocused and off-task. However, this demonstration literally led me by the nose to follow his description of the diffusion of gases through other gases. It is likely that during that class I created two or three pathways to the information about gas diffusion that I processed through my senses and ultimately stored in my long-term memory. Since then, that knowledge has been available for me to retrieve by thinking of a rotten egg or by remembering the emotional responses as the class reacted to the odor permeating the room. Once I make the connection, I am able to recall the scientific facts linked to his demonstration.

Event memories, such as the one that was stored that day in my chemistry class, are tied to specific emotionally or physically charged events (strong sensory input) because of the emotional intensity of the events to which they are linked. Because the dramatic event powers its way through the neural pathways of the emotionally preactivated limbic system into memory storage, the associated hitch-hiking academic information gets pulled along with it. Recollection of the academic material occurs when the emotionally significant event comes to mind, unconsciously or consciously. To remember the lesson, students can cue up the dramatic event to which it is linked.

Can you recall a time when you smelled the perfume a friend or loved one wore, and you remembered other details about that person? Perhaps upon hearing an old song, you've recalled dancing to it years before? You can probably visualize where you were when you heard the World Trade Center had been hit. When you think of that event, you probably remember other details of your environment at that moment. Similarly, experiential learning that stimulates multiple senses in students, such as hands-on discovery science, is not only the most engaging, but also the most likely to be stored as long-term memories. Because each of the senses has a separate storage area in the brain, multisensory input results in duplicated storage and can be retrieved by a variety of stimuli. With strategies that engage the senses, students "become" the knowledge by interacting with it. As a result, a new memory that might otherwise be forgotten is linked to a sensation, a movement, or an emotion, and therefore it travels into the memory storage along more than one pathway. This redundancy of pathways means greater memory retention and recall.

Hands-on experiential learning activities are by nature multisensory. They actually stimulate two memory systems in separate brain regions that are seen networked together, resulting in powerful cross-referencing on PET scans (Andreason et al., 1999). These activities teach information that is specifically structured into the lesson-factual information such as the process of photosynthesis. That is semantic memory. In addition, there are episodic or event memories stored, such as the sensory input from touching, seeing, measuring, and investigating the plant. Because hands-on activities target both memory systems, there is greater likelihood of retention and less need for inefficient rote memory.

It is not, nor should it be, an educator's role to turn the classroom into a video arcade. We don't want students to be primarily motivated by the external rewards of bells and whistles. An ideal event-memory lesson would be one where students' brains are stimulated by their participation in a challenging and engaging student-centered activity that simultaneously activates multiple sensory systems and executive functions as they strive to make sense of experience. The goal is to provide experiences that enable students to interact with knowledge in ways that arouse their physical senses and positive emotions, or to connect the new information with their past experiences and interests.

Educators can supercharge material to be learned by relating it to students' senses and experiences, and these connections intensify their memory building. This process of connecting new information to related experiences or memories is aptly named relational memory.

Relational Memory-Lighting the Pathways

Learning consists of reinforcing the connections between neurons. Relational memory takes place when students learn something that adds to what they have already mastered; they engage or expand on "maps" already present in the brain. This process engages more executive functions as students' brains scan their stored memory banks seeking relationships that help them put new connections in context.

Patterns are paths for memories to follow. How does relational memory apply to teaching? We already know that rote memory is inefficient, but now there is visible evidence to encourage helping students make connections and see patterns.

Patterning is the process whereby the brain perceives and generates patterns by relating new with previously learned material or chunking material into pattern systems it has used before. Education is about increasing the patterns that students can use, recognize, and communicate. As the ability to see and work with patterns expands, the executive functions are enhanced. Whenever new material is presented in such a way that students see relationships, they generate greater brain cell activity (forming new neural connections) and achieve more successful long-term memory storage and retrieval.

Graphic Organizers

Graphic organizers help students see relationships and pattern new information for memory storage. They are one of the most nourishing of all "dendrite sprout foods" to nurture students' brain growth.

The more educators add the science of teaching to their individual styles and skills, the less students will need to rely on the inefficient and unpleasant process of rote memorization. Graphic organizers are a creative alternative to rote memorization because they enable students to make connections, see patterns, access previously stored related memories, and expand upon existing memory circuitry.

Graphic organizers coincide with the brain's style of patterning. For memory capture to occur, there must first be encoding (the initial processing of the information entering from the senses). If this information is to reach the final stage of enduring memory retention in long-term memory, there must be a process of consolidation and storage, where the otherwise transiently encoded event or information is patterned into a more enduring form (Koutstaal et al., 1997).

Graphic organizers promote this more enduring patterning because material is presented in ways that stimulate students' brains to create meaningful and relevant connections to previously stored memories. They can make associations, discover patterns, sort information, and store the new data as relational memories and then long-term memories (see Figure 1).

Figure 1. Sample Instructions for a Student-Generated Graphic Organizer

1. You will create a graphic organizer with evidence to support the following generalization: Sleeping 8 to 10 hours each night is good for middle school students.

2. First, put the generalization in the center of the graphic organizer page.

3. For each fact that you select to support the generalization, include a visual symbol. It can be a picture you draw, a symbol, or clip art.

4. Use at least three colors.

5. Include at least four supporting facts.

Information taught in patterns can be as simple as presenting material in chunked format. Because the working memory has a capacity for immediate recall limited to from five to nine pieces of unrelated items, if information is separated into chunks, students can remember it more successfully. Just as phone numbers and social security numbers are divided into chunks of three or four, information-from biologic genus-species names to states and capitals-can be chunked into groupings of three or four, ideally with some commonality that relates them.

When graphic organizers help students cluster information, the process enhances the brain's natural tendency to construct meaning by forming patterns. The best graphic organizers engage the students' imaginations and positive emotions in a creative process whereby they recognize, sort, and discover patterns for themselves. In addition, the use of graphic organizers to connect information in meaningful relationships allows students time for reflecting about the information. The result is that they can ultimately go beyond regurgitating rote memorization to the higher cognitive process of using the information in significant ways. The relational memories they store will be available for critical thinking and other executive functions to use for meaningful problem solving.

Graphic organizers are intrinsically engaging, as they require students to interpret and interact with the material. When students create their own categories (personal relevance) the connection is increased. If they are provided a framework for their organizers, it is helpful if they understand the logic of the structure they are given.

When students make this connection of new to previously stored memories, they experience the sentiment described in the quote from Doris Lessing, "That is what learning is. You suddenly understand something you've understood all your life, but in a new way."

Maintaining Alertness and Improving Memory Retrieval

Teachers develop the ability to read their students' body language, and this skill can let them know when it is time for brain breaks ("syn-naps") or altering their mode of instruction. Alertness and memory retrieval increase with more varied modes of instruction of the same material, so one-lesson-fits-all formats should be avoided. Differentiated instruction is one way to gear instruction toward a different type of intelligence each time the lesson is retaught. The better textbooks provide suggestions for these alternative teaching approaches.

Flashbulb memories. As described previously, powerful emotional events are also retrieval-building tools. These flashbulb memories, such as the destruction of the Twin Towers or the Challenger or Colombia blowing up, result in powerful association memories such as what we were doing at the time we heard or saw the event.

These vivid, photographic memories of a lesson punctuated with positive visual and emotional content can include student dramatization in a lesson, pantomiming a vocabulary word, acting out a history skit, or role-playing a conversation in a foreign language. (Students will also benefit from the physical movement and change these activities provide). For these purposes I keep a box of costumes, especially hats, in my classroom at the ready for lessons well suited for dramatization.

Along these same lines, students benefit by being personally involved in the subject material with techniques such as hands-on manipulatives, field experience, experimentation, or even whole body movement (total physical response) to potentiate the implantation of the new information into memory and improve retrieval later. Some specific activities include the following:

1. Multiple forms of review, such as concept maps to provide framework for retrieval.

2. Visual imagery: Visualize the historical event using words or pictures on paper.

3. Personal relevance: Tie the information to their lives. Think, write about the connection, and share with a partner.

4. Produce a product or make models.

5. Role-play or pantomime.

Once the information is successfully retrieved, it still needs to be reviewed between four and seven times to ensure retention. Review beyond a single perfect response permits the new neural networks to fire correctly more than once. The more they fire, the easier it is to access and retrieve the information later.

The best learning occurs when students are given opportunities to develop their capacities to think, interpret, and become engaged in subject matter. It therefore behooves educators to become mentors not only of the subject matter taught, but also of the memory and retention process. Brain-based research has yielded the strategies that improve students' receiving, encoding, storing, and retrieving of information, but there is an emotional aspect to consider as well. These next strategies strive to

Keep student anxiety and stress low.

Punctuate lessons with attention-grabbing moments.

Improve student memory and retention by making connections to previously learned material, personal experience, and positive emotional states.

Enrich lessons with multisensory input.

Access multiple intelligence strategies authentically connected to the material.

Punch Up Lessons

When the 6th grade students entered Ms. Patterson's class one late October morning, the room was darkened, with candlelight the only illumination. Desks were pushed to the sides, a few blankets were spread on the floor, and a "director's chair" faced the classroom. Their delight at this haunted setting allayed any fears of their pending oral presentations of scary stories, and because of this novel surprise, they were more attentive than ever before.

One of the reasons the first day of school is exciting for most students is because there is novelty. It can be the new teacher, new classmates, different bulletin board, new textbook, or even a change of view out the classroom window. Enthusiasm is generated when students are presented with novelty and find creative ways to explore or connect with the new material and are inspired by it. If teachers can generate this awe and sense of wonder, students will be pulled into the lesson and want to connect with the information in a meaningful way.

Brains search for meaning to successfully encode new information. Students' attention must be engaged before the new information can be perceived, encoded, and patterned. Novelty, humor, and surprise in lessons expedite students' attentive focus, and the use of these strategies results in more successful encoding of data into the memory circuits (Koutstaal et al., 1997).

Interactive strategies that incorporate novelty and engage attention can include quiz show formats. New and changing match-game puzzles at workstations with colored stickers or humorous sketches will engage students' attention. Then students can perform the patterning task of connecting one fact to another. This match-game process can be applied to words and their definitions or to two sides of math or science equations. Even changing where students sit brings freshness to their classroom experience.

Lessons don't all have to involve elaborate surprises to be motivating. In planning ways to punch up the memory links for the material taught, teachers can engage students' interest through student-centered lessons. Something as simple as a mirror can personalize a learning activity-ask the students to look in the mirror and respond to a writing prompt such as, "What will the person in the mirror do to make the world a better place?" or "What will the person in the mirror do if he or she hears a racial slur?" Even with a large class, strategies that connect individual students with the material in personal ways are key to keeping students tuned in and their brains turned on.

Personal Meaning

As noted previously, a student must care about new information or consider it important for it to go through the limbic system expeditiously, form new synaptic connections, and be stored as a long-term memory. In other words, memories with personal meaning are most likely to become relational and long-term memories available for later retrieval. Student-centered learning can lead to mastery, because the lesson has personal meaning that they can see has the potential to increase their success and skill in achieving something they care about.

Hooks to connect. Learning should and can be exciting when students relate new information to past experiences. This connecting lets them personalize the learning and increases opportunities for its placement in the relational memory system. If they don't have any links to hook into, teachers can start them off with scaffolding through structured outlines or graphic organizers that they can fill in after they participate in an active learning experience. They can then personalize the information by thinking of ways in which they might use it in future careers or hobbies.

This same positive neural circuit connecting occurs when the lesson is associated with a positive emotional experience. The positive emotional experience can be the result of feelings of accomplishment, pleasant social interactions with classmates or the teacher, or specific acknowledgment and praise. This emotional connection is particularly applicable during adolescence. The influences of emotions and hormones are greatest during the elementary and middle school years, making these years a particularly significant time to use teaching strategies that make the most of the heightened emotional state of students.

An example would be to help students reach a state of excited interest and emotional comfort by introducing the material in association with something that the class always enjoys. This association can be a lesson that starts out in the playing field or one that begins with a treat such as popcorn. For example, a new class literature book is sometimes introduced by having students read the first few pages aloud using the "popcorn" or "jump in anytime" read-aloud technique. (In popcorn reading, students take turns reading aloud, but instead of alternating pages or paragraphs, a reader pops in anytime, even in mid-sentence. This reading technique is useful to keep the students following the text while listening to others reading because they must be following the words carefully to pop in.) Before introducing "popcorn reading" you can give out or even pop some popcorn to demonstrate why the technique is called "popcorn." By associating the lesson with a positive emotional memory, the academic memory will be linked and related to the positive emotional memory.

Cross-curricular relational memory building. Learning related material across the curriculum involves activities that increase the connections between different areas of the brain where related information is stored. When students investigate topics creatively with thematic, interdisciplinary approaches, they learn patterns and skills, not just facts. When subjects are interrelated, they are more easily recalled and there is less need for memorization, because higher levels of thinking have been stimulated and there are increased numbers of pathways by which information can travel in and out of long-term memory banks.

Visualization. Visualization is another way for students to create personal connections to the material. After first modeling and describing a visualization of one's own, such as what the teacher pictures when thinking of a sunrise during the fall equinox at the North Pole (which direction are you looking in and at what time of day) and frontloading students with factual information, students are then asked to visualize the science they are learning about, such as the Big Bang that may have occurred at the birth of the universe.

After giving imagination free rein, more of their brains can be engaged if the students put their visualization into words, diagrams, or pictures. They can describe their images to each other, write them in words, or draw sketches. Just as athletes may visualize a move before they execute it, students can be encouraged to visualize a biological process or historical event as it is explained in class. When they draw diagrams, create models, and engage their sight, hearing, smell, touch, or movement, they are making connections between the new information and something they already know. They are engaging multiple brain pathways and increasing the likelihood of memory storage and effective retrieval.

The more bizarre the visual image, the more memorable it becomes. Modeling becomes important here to show them how their teacher pictures a high hangman's gallows, built with a right angle, with a pot in a noose hanging from it, to remember the word and position of the hy-pot-en-use in a right triangle. This visualization process can include humor, creativity, pleasure, and self-satisfaction. All of these predispose the limbic system to add emotional power as it passes the image and the attached concept into long-term memory storage. In addition to generating mental images, if kinesthetic activity can be incorporated, the student has at least two different memory circuits activated.

I have used visual images, accompanied by a sketch on the board, for unfamiliar terms, but two that always elicit groans and giggles are so well remembered that new students come to my class asking when I'm going to teach them about polygons and the rhombus. Similarly, former students come back and tell me they never forgot those terms. For the explanation of open versus closed polygons, I draw a closed, multisided polygon with a bird inside. I then open the polygon by erasing one of the sides. I next erase the bird and say, "When the polygon is open, Polly is gone." I'm glad I can't hear your groan or I might not proceed with the rhombus. I draw a rectangle and tell the students that one day a new, inexperienced bus driver was on the road and hit the rectangle. I then sketch the rectangle after it was struck by this WRONG BUS-it tilts to the side and becomes a "rong-bus" or a rhombus. After the groans, I have them stand like rectangles and imagine that the wrong bus taps them, so they tilt a bit and turn into human rhombus-like structures.

If I am short of lesson time for vocabulary words, I might act them out myself and have students select the word from a list on the board that matches my pantomime. Other times I ask them to make a physical response that reminds them of the word. I have a great class photo that was taken when I asked them all to show me a "haughty" expression, after first prompting them that it might be the expression a rude king or queen might make after being served tea from a dirty cup by an unwashed servant.

Even with highly conceptual learning, such as political systems or philosophy, if the students can actively do something with the new information, they can ultimately own it and store it in permanent memory. The more abstract the information, the more creative teachers need to be to help students relate the material to personal experiences or consider its practical or future applications.

For example, historical events can be personalized by turning them into ethical dilemmas students might face today. Students can experience firsthand the dilemmas of the non-Jews during the Holocaust who struggled with the risks to their own families in hiding Jews from Nazis. Follow a lesson about those events with a question relating that ethical dilemma to one that could happen today. "What if your neighbor was hurting his dog and you saw him do it again and again. What if he saw you watching him and told you he would poison your dog if you reported him. What would you do? How would you feel?" When children consider how they would respond, the history takes on personal meaning and becomes relational memory.

Limbic System Stimulation-Not Too Hot, Not Too Cold, but Just Right

The amygdala is part of the limbic system in the temporal lobe. It was first believed to function as a brain center for responding only to anxiety and fear. Indeed, when the amygdala senses threat, it becomes overactivated (high metabolic activity as seen by greatly increased radioactive glucose and oxygen use in the amygdala region on a PET scan). In students, these neuroimaging findings are seen when they feel helpless and anxious. When the amygdala is in this state of stress, fear, or anxiety-induced overactivation, new information coming through the sensory intake areas of the brain cannot pass through the amygdala to gain access to the memory circuits.

More recent studies have found that the amygdala also is stimulated, but to a lesser degree of metabolic activity, when students are in a positive emotional state with feelings of contentment, joy, play, and a comfortable, but stimulating, amount of challenge.

During these emotional states, neuroimaging shows metabolic states of low-level stimulation in the amygdala. Students tested under these conditions show better working memory, improved verbal fluency, better episodic memory for events, and more flexible thinking yielding creative ideas for problem solving. They even show more positive social behaviors-helpfulness, sociability, focus, patience, and other higher-order executive function and decision-making abilities.

Subsequent research revealed that after presentation of pleasurable, comforting, positively reinforcing, intrinsically motivating stimuli, the amygdala could be moderately stimulated or warmed up to the alert state that actually facilitates active processing and neuronal transport of information. This represents the actual neuroimaging visualization of what has been called the affective filter-an emotional state of stress in students during which they are not responsive to processing, learning, and storing new information. This represents objective physical evidence that during periods of high stress, new learning just doesn't get in to the information processing centers of the brain.

To prevent overactivation of the amygdala, protect students from aversive experiences that would block the passage of new information into long-term memory. The type of stressful experiences that can result in amygdala blockage include calling out students' failing test grades aloud as exams are returned, teaching a lesson in a language that students don't understand without using TPR (total physical response, with gesturing, pointing to objects, pantomime, and other techniques to give them the information they need), or ignoring hands raised with questions without telling the students that you will get to their questions within a few minutes after you finish making your point. (Once students don't understand a part of a process, such as a step in a math calculation, it is stressful to hear the teacher continue on while they are lost. If they are assured that their questions will soon be answered, they don't overstress.) In general the type of stress that is overpowering is a helplessness connected to hopelessness.

However, as important as it is to avoid overactivation of the amygdala, it is also important to provide mild-to-moderate challenge to stimulate authentic curiosity and engagement in lessons so the amygdala, tuned to just the ideal state of activation, can enhance the speed and efficiency of information flowing through into the memory storage areas of the brain. It is just the right balance of these emotional and intellectual opportunities, and the incorporation of students' own interests and curiosity into the lesson, that will motivate them to work toward greater understanding and connection with the material. As students access this pathway with open-ended and studentinitiated questioning, they will engage their higher-order executive functions and, with practice, experience the confidence to see themselves as learners with open minds. Educators can help students unlock the gatekeeper (amygdala or affective filter) for sensory data. Once the information can get through the amygdala, it can be linked with students' personal interpretations and teacher-guided meaning. These memories have the best chance of entering long-term memory storage banks.

Syn-naps

Every brain needs periodic rests during which neurotransmitters can be replenished and executive function can process the new material. The use of the word "Syn- naps" is an example of the use of word play to help build memory. The synapse is the gap between nerve endings where neurotransmitters like dopamine carry information across the space separating the axon extensions of one neuron, from the dendrite that leads to the next neuron on the pathway. The creation of a word like syn-naps helps teachers recall that after repeated release of neurotransmitters from a nerve ending, there needs to be a brain rest when the neurotransmitter can be restored to be available for release when the next message comes traveling along the neuronal circuit. These syn-naps are restorative breaks that are as important for successful memory retention as are other elements such as surprise, positive emotional state, sensory memories, and other relational memories. Not only do these "naps" prevent overloading of the circuits and interference with maximal memory storage conditions, but they also help maintain positive emotional states.

If the lesson involves complex material, especially in a lecture mode, syn-naps can be necessary after as little as 15 minutes. When students are entering a state of depletion of neurotransmitters in their synapses, they will become fidgety, distracted, and unfocused. It is best to have students take the brain rest before neurotransmitter depletion occurs and before stress builds up in the amygdala, inhibiting new information intake. If the neurotransmitters are not being replenished as fast as they are being used, or if amygdala hyperactivity is beginning to block new information input, memory efficiency drops rapidly. In this burnout state, new memories can't be stored efficiently.

Depleted neurotransmitters rebuild within minutes if the break is taken before complete meltdown, but their rebuilding takes longer if they are severely depleted. It is ideal to prevent burnout by planning brain rests before students display the first signs of glazed expressions or distraction. If these overload/depletion times are anticipated before they occur, and students have a break before that point, the topic about which they were learning will not be linked or negatively reinforced by their associating feeling bored with that topic when it comes up again.

During these rests, the newly learned material has the opportunity to go from working or short-term memory to relational memory (although it will not become a permanent memory until time and practice follow). The students can start the break with a complete change of pace by moving about the room, drinking water, stretching, singing, dancing, or taking a bathroom break. However, after that transition, it is critical to implement the strategies that have proven most effective in cementing the working memory into relational memory and long-term memory.

After the rest or physical movement is the time to use a student-centered cementing strategy-one that was not used earlier in the lesson. It has been said that we file by similarities and we retrieve by differences, so here is the opportunity for students to identify and discuss similarities and differences. Here are a few techniques:

Draw Venn diagrams.

Generate mental images (if not done previously) and think about what other mental pictures come to mind in association with these new ones.

Create metaphors and analogies.

Analogies, although no longer part of the SAT, remain effective ways for students to conceptualize and thereby interact and connect with instruction by comparing the similarities or differences between two chunks of information. After syn-naps, students can try to create a simile or metaphor that helps them abstract the new material, such as, "Adverbs give more meaning to verbs like acting kind ly gives more meaning to a friendship." This analogy-building process is a way of physically structuring the memory circuits, or bringing stored similar memories online to connect with the new information.

Students may benefit from prompts to make analogous connections with questions such as these: In what way was the American Revolution like a baseball strike? How are human hands like bats' wings? How are babies like the new seedlings we are growing? How is mutation-based evolution similar to the TV show Survivor?

Greater connections to book reports, history reports, and empirical essays can occur when students use analogies in the form of personal anecdotes that begin the essay and are concluded at the end of the report. This strategy not only connects the student personally with the topic, but is also a compelling way to draw in readers.

Memory is strengthened by insight; when students understand concepts well, it is much easier for them to remember relevant facts. This memory strengthening is what occurs when students use analogies, metaphors, and personal anecdotes to connect new information to their own stored internal graphic organizers-their neurondendrite networks.

Repetition and Consolidation

Multiple mechanisms work to maintain stored memory, including recollection, familiarity, and priming. Once the information is remembered correctly and used with executive functions, it still needs to be reviewed on a regular basis, but at gradually lengthening intervals. This repetition, after the first correct response, results in reinforcement of the neuronal connections along the lengths of the axons and dendrites and across the synapses. The more the neural connections are activated by the stimulation that practice brings, the more dendrites grow to strengthen the connections between the neurons.

When the brain perceives information repeated in multiple ways, there is a priming process that makes encoding of that information more efficient. That is why writing a vocabulary word in a sentence, hearing classmates read their sentences, and then following the direction to use the word in conversation during that day will result in more successful long-term memory storage and retrieval than just memorizing the definition (Koutstaal et al., 1997).

This varied repetition of the information results in consolidation of information. Consolidation of information involves using the most effective strategies to first acquire information and then practice and rehearse it. The best-remembered information is learned through multiple and varied exposures followed by authentic use of the knowledge by processing it through the executive function centers. This executive function processing of new information can be achieved by student-centered or open-ended questions, active problem solving, or connecting the information to real-world situations.

These steps along the way will change the sensory data students are bombarded with into knowledge they will own. These multiple and varied exposures and higher cognitive processing result in more pathways leading to the newly stored information. That means there will be more ways to later access the information for retrieval after it has been stored in the long-term memory centers.

Strategies to Consolidate Learned Material into Long-Term Memory

Introduce the information when students are engaged, with focused attention.

Include practice of accurate and precise observation techniques where students learn the information in a meaningful context. Encourage students to repeat information you want them to remember over and over, even in conversation: "Isn't it odious how much chewing gum is on the bottom of some restaurant tables?" "Oh yes, it is even more odious when you have to clean it."

Use multisensory avenues of exposure to the information that result in multiple connections and relational memory links to existing memory circuits to increase recall and memory storage.

Create student-centered, personal motivation for learning. For example, if there is math or science that needs to be mastered in the curriculum standards, students can be motivated to learn, even memorize, the basics-algebra, structural geography, physiology, cellular chemistry, aerodynamics, and wave mechanics-to reach their goal of building a model land-water amphibious vehicle.

Use skilled and practiced observation techniques (on initial exposure and repeated opportunities to observe again as topic of study continues) to make personal connections and discoveries about the material to be learned.

Have students use the information to answer personally relevant, critical thinking questions or make and support judgments using the new knowledge.

Pose practical, real-world problems for students to solve using the new knowledge.

Ask students how they might use the information outside of school. How might it be important in what they are considering as a possible future career? How might it be valuable to their parents' jobs?

Just as personal interest and novel activities generate interest in the big picture of a new topic, these techniques are also valuable in culminating experiences. For example, after we studied the daily life of the early American colonists, we had Colony Day. Students could dress in colonial attire, bring authentic colonial foods, teach the class a colonial game, act in the role of a famous person from colonial times, or demonstrate a craft or professional skill from that era. Students could choose their type of participation, and use executive function and the newly acquired knowledge of colonial life to evaluate the best ways to proceed with their plans, plan and prioritize a schedule to prepare for their activity, and predict any problems that might come up. They also had to know their information well enough to respond to high-level peer questioning about the role of their person, food, or activity in colonial society.

Culminating Activities as Memory Cement

Students make ongoing observations and continually revise and refine their hypotheses. (The basis of my medical training and practice was to carefully observe patients, make a preliminary list of possible diagnoses, then question further, examine, and collect data to narrow and refine my diagnosis. This revising and refining process is actually done by students when they use an Internet search engine such as Google and refine their terms to cull the specific information they need from the thousands of initial references.)

Students are guided to analyze and compare their own work and the work of experts.

Students are encouraged to check on facts and details and to test their beliefs and conclusions.

Students use graphic organizers and activities like KWL. When students connect new information with similar stored knowledge in KWL, this "priming" increases familiarity and therefore improves recall. For example, after studying the word "seatbelt," when shown the word "seat" in word association, the most likely response is "belt."

Students are asked student-centered, open-ended questions and critical thinking questions to increase depth of understanding. These questions can be prompted by the teacher, but should come from students' personal interest in the information to be learned. Starting with a global initial presentation appealing to their interests, students will want to ask questions to gain more information and make sense of things they see, hear, and read about.

Students are given multiple exposures to the same or similar information over time. Scaffolding is provided through questions and summarizing activities to confirm that students have learned the facts and strategies needed to be successful in standardized tests and in the future use of the information to serve their needs.

Students are assessed using authentic assessment; they are evaluated in how they use the material for problem solving, good decision making, creative thinking, making predictions, comparisons (metaphors/analogies), and critical thinking.

Students use metacognition and reflection to learn from the learning process they engaged in and develop skills to monitor their own future learning.

The brain-based techniques already described to enhance memory are geared to increase connectedness through familiarity, personal engagement, and varied repetition and review. When these strategies are used, most of the work to promote long-term memory storage and successful memory retrieval has been done. Because the new material was reinforced through reminders of personal connection at the conclusion of the lesson, and because students were asked open-ended questions about what they found interesting, what they were reminded of, and what they still want to know about, they will be able to take the lesson beyond the classroom door, perhaps even into the lunchroom in a discussion with a classmate, or to the family dinner table.

The list below is a summary of the path to successful memory storage and retention:

1. Information about the world enters the body through the senses.

2. The limbic system and reticular activating system prime the rest of the brain to respond to these sensory inputs.

3. When there is the ideal amount of comfort and stimulation, these activating systems engage memory circuits to an ideal state of readiness. Memory circuits are engaged and ready.

4. Dopamine, adrenaline, and norepinephrine are released in ideal quantities.

5. Information is conducted along memory circuits and connects with previously stored memories and personal experience to form relational memories and patterns.

6. Frontal lobe executive function is activated.

7. The learned, consolidated material is reflected by wisdom as it is retrieved and applied to new situations and future creative problem solving.

Technology as a Memory Tool

Multiple forms of review using different techniques for practicing the same material are of added benefit for memory consolidation, retrieval, and processing through executive function. One reason is that positive reinforcement can be a powerful factor in student learning, and because teachers can't always be there to provide that external reinforcement and reward, technology can help.

Some students don't have Internet access on a readily available computer at home, but most do have this access in computer labs or libraries at school. In addition, many current textbooks in mathematics, history, and other subjects have CD-ROM versions or extensions of the texts or Web pages with interactive activities for students and teachers.

Because much of the computer interactive technology starts in the mathematics field, an example available for trial use is the ALEKS system at www.K12aleks.com. This is an example of how a successful interactive computer program can reinforce learning and retention for students. The students are signed into the program by a teacher who can then monitor their time spent, progress, and learning speed, and see not only the concepts they have mastered, but also the concepts that are in their ZPD (Vygotsky's zone of proximal development or readiness). The topics that the student is ready to learn are then presented to them using a pie chart offering a selection of subtopics from which they can select.

One of the most powerful factors in student learning is feedback, because it reinforces neurons in the brain. This ALEKS system gives positive feedback to the students and therefore reinforces neuron circuits in their brains. The reward they receive is authentic because it acknowledges their accomplishments and is directly connected to the learning that just took place or was learned in earlier lessons and tested in a periodic assessment. In the ALEKS system, progress feedback is available to teachers and students at any time and each new lesson starts with a review of the material previously learned.

Well-engineered computer adjuncts can enhance students' memory connections, pathways for access, and retention of the material they learn in the classroom and read in their texts. However, it is up to teachers, administrators, and curriculum teams to evaluate a program's assessment system. Look for a system where periodic assessments review all topic areas of the course. This not only reinforces existing memory, but should also prompt appropriate review when knowledge gaps are revealed. Some computer systems evaluate only the student's recall of the topics taught since the last assessment. Those do not adequately address the long-term memory retrieval. If a student has forgotten things learned earlier in the course, the assessment should recognize and report these gaps when it measures true mastery. The best systems use all of this information when evaluating an individual student's readiness to proceed, and makes those assessments easily accessible and comprehensible for teachers to review.

Once They Leave the Classroom

Most popular magazines and self-help books devote pages to theories on how diet, exercise, and lifestyle affect health and well-being. These factors are so difficult to quantify that it is challenging to make informed decisions. Fortunately, neuroimaging has provided empirical evidence about some of these factors, especially the impact of sleep on memory.

Sleep. During sleep, the cortical executive functioning of the frontal lobes is less active because less sensory input is entering the nervous system. This reduced-activity brain state is just what is needed to allow recently learned material to be rehearsed or repeated, sometimes in dreams. Because sleep is the time when the brain is least distracted by the sensory input bombarding it all day, it can devote a greater portion of its energy (metabolism) to organizing and filing the memories formed during the day.

Sleep helps the brain consolidate and cement new knowledge and experience into memory. This sleep research gives validity to what students have discovered through their own study habits of reviewing notes when they are still alert, rather than just before they fall asleep. Studies suggest that if students review their notes thoroughly and stop and go to sleep when they begin to feel drowsy, the quality and quantity of retained memory is superior to extending the review time any number of hours once drowsiness has set in.

Even when sleep-deprived students catch up on their sleep, their test performance on recently learned information is lowered (Stickgold, 2000). A study of students who received low grades ( Cs, Ds, and Fs) revealed that they obtained about 25 minutes less sleep and went to bed an average of 40 minutes later on school nights than students with high grades ( As and B s). Adolescents who slept less than 7 hours reported increased daytime sleepiness, depressed mood, and behavior problems (Wolfson, 1998).

In 2004, Duke University canceled all 8:00 a.m. classes because students weren't getting enough sleep. "They're coming in to see us, and they're ragged," said Assistant Dean Ryan Lombardi. Duke University also plans to offer students individual health assessments for what to eat and how many hours to sleep.

The Future

When brain research on memory and retention is applied to the classroom, it not only drives the learning process, but it also allows educators to energize and enliven the minds of their students. As the research continues to build, it will be up to these professionals to develop and use new strategies that bring the brain-based research to students. That challenge will be a fascinating and exciting one to meet.

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Memory, Learning, and Test-Taking Success

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by Judy Willis The past two decades have provided extraordinary progress in our understanding of the nature of learning. Never before have neuroscience and classroom instruction been so closely linked. Because advances in technology enable us to view the working brain as it learns, educators can now find evidence-based neuroimaging and brain-mapping studies to determine the most effective ways to teach.

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A Multisensory Perspective of Working Memory

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Abstract

Although our sensory experience is mostly multisensory in nature, research on working memory representations has focused mainly on examining the senses in isolation. Results from the multisensory processing literature make it clear that the senses interact on a more intimate manner than previously assumed. These interactions raise questions regarding the manner in which multisensory information is maintained in working memory. We discuss the current status of research on multisensory processing and the implications of these findings on our theoretical understanding of working memory. To do so, we focus on reviewing working memory research conducted from a multisensory perspective, and discuss the relation between working memory, attention, and multisensory processing in the context of the predictive coding framework. We argue that a multisensory approach to the study of working memory is indispensable to achieve a realistic understanding of how working memory processes maintain and manipulate information.

Keywords: working memory, multisensory processing, multisensory integration, attention, top-down, bottom-up

A Multisensory Perspective of Working Memory

In everyday life we experience a continuous stream of information that we perceive through sight, sound, smell, taste, and touch. Even though this experience is mostly multisensory, that is, we receive information from multiple senses simultaneously, psychological research has primarily focused on studying our senses in isolation. While we are beginning to understand how our senses interact at various stages of processing (for an overview see, e.g., Wallace et al., 1993; Beauchamp, 2005; Ghazanfar and Schroeder, 2006; Stein and Stanford, 2008; Klemen and Chambers, 2012) it is still heavily debated whether the higher-order mental representations that are derived from these sensory inputs still contain modality- specific information or not. For instance, in working memory, research has focused on resolving whether information is memorized in the form of separate, modality or domain specific representations (Baddeley and Hitch, 1974; Schneider and Detweiler, 1988), or as integrated representations (Atkinson and Shiffrin, 1968; Cowan, 2001).

Multisensory processing refers to the interaction of signals arriving nearly simultaneously from different sensory modalities. This implies that information from one modality can influence information processing in another modality. Information from different sensory modalities can also be combined into a single multisensory event, a process that is referred to as multisensory integration (Stein et al., 2010). In accordance with the suggestions of Stein et al. ( 2010) we will use the terms "modality-specific" or "cross-modal" when describing the properties of objects and "unisensory" or "multisensory" when referring to neural or behavioral processes associated with a single or multiple sensory modalities.

The aim of this paper is to discuss the current status of research on multisensory processing and the implications of these findings for our theoretical understanding of working memory. To do so, we will focus on reviewing working memory research conducted from a multisensory perspective. We will argue that a multisensory approach to the study of working memory is indispensable to achieve a realistic understanding of how working memory processes maintain and manipulate information.

Working Memory and the Multisensory Brain

In their seminal work, Atkinson and Shiffrin ( 1968) devised a model for the flow of information in human memory, which subsequently became known as the modal model. They suggested that environmental information is processed by various modality-specific sensory registers before it is combined into a single, modality-independent, or more formally amodal, percept and transferred into a short-term store. According to this view, the short-term store is an amodal, general-purpose mechanism. Atkinson and Shiffrin referred to this mechanism as "working memory", as it was considered to be responsible for a variety of operations, such as the selection, manipulation, and rehearsal of the memorized items.

A few years later, Baddeley and Hitch ( 1974) proposed a multiple-component model of working memory where information is assumed to be stored in two domain-specific subsystems (the phonological loop and the visuo-spatial sketchpad) that are directed by a general control mechanism (the central executive). The phonological loop is responsible for short-term maintenance of speech-based and acoustic items. The visuo-spatial sketchpad maintains visually and/or spatially encoded items. In contrast to Atkinson and Shiffrin's ( 1968) idea of a domain-independent (i.e., amodal) store, Baddeley and Hitch ( 1974) assume that information (e.g., verbal or spatial) is maintained in its corresponding domain-specific store.

Over the years it has become clear that information from different domains showed more interaction in working memory than one would expect from a strongly domain-specific perspective (e.g., Jiang et al., 2000; Logie et al., 2000; Prabhakaran et al., 2000). An episodic buffer was added to Baddeley and Hitch ( 1974) original working memory model to account for, amongst other things, the apparent interaction between phonological and visual processes (Baddeley, 2000). The episodic buffer can be conceived as an amodal storage component, which was estimated to hold up to four chunks of information. Additionally, it was proposed to act as a link between all the other working memory components described above. For this revised model, Baddeley ( 2000) suggested that the episodic buffer integrates memory traces that may originate from different senses into a coherent perceptual scene.

On the basis of several studies, Postle ( 2006) has proposed that the brain areas involved in sensory perception are also responsible for the short-term storage of sensory information. For instance, functional magnetic resonance imaging (fMRI) studies showed object-specific memorization effects for faces in the posterior fusiform gyrus (e.g., Druzgal and D'Esposito, 2003; Ranganath et al., 2004), an area considered to be vital for face recognition. Postle and D'Esposito ( 1999) found activity related to memorization of visual object location and depiction in ventral temporal and occipital visual brain areas. Similarly, event-related potential (ERP) modulations can be seen in posterior and occipital recording sites during short-term memorization of visual objects contralateral to the to-be-remembered objects (e.g., Klaver et al., 1999; Vogel and Machizawa, 2004). Such findings (for an overview see, Postle, 2006; D'Esposito and Postle, 2015) indicate that memorizing modality-specific sensory information involves the same brain areas as those involved in the initial sensory processing of that information. This idea is compatible with the classical view that integration of the senses would take place at a later stage of processing, after initial unisensory processing has taken place (see Talsma, 2015, for a discussion). Indeed, using neurophysiological methods with animals (e.g., Wallace et al., 1993; Fuster et al., 2000) and fMRI with humans (e.g., Calvert et al., 2000; Wright et al., 2003; Beauchamp et al., 2004) several higher-order brain areas have been identified that seem to be dedicated to integrating information from multiple unisensory sources. Brain areas typically regarded as multisensory in the human brain can for example be found in the lateral occipital-temporal cortex, such as the superior temporal sulcus (STS; Beauchamp, 2005).

An increasing number of studies now suggest, however, that multisensory processing can already take place in brain areas that were considered to be strictly unisensory (see for a review, Foxe and Schroeder, 2005; Macaluso and Driver, 2005). For example, Giard and Peronnet ( 1999) found multisensory ERP effects as early as 40 ms post-stimulus over occipital scalp areas, suggesting that multisensory interactions take place much earlier than previously assumed. Using fMRI, Foxe et al. ( 2002) showed integration related effects of auditory and somatosensory stimuli within a region of the auditory cortex previously thought to be unisensory. This brain area was more strongly activated by multisensory stimuli than what might be expected on the basis of a mere summation of either auditory or tactile stimulation alone. Likewise, Dionne et al. ( 2010) found increased BOLD signal in the right primary somatosensory cortex during a delayed sensory-to-motor task for cross-modal visual-somatosensory stimuli compared to modality-specific stimuli.

These findings also have implications for the memorization of multisensory information. If indeed, as Postle ( 2006) proposes, the brain areas responsible for perceptual processing are the same as those involved in memorization, and if multisensory effects can already be observed in the primary sensory cortices, then we would expect that cross-modal information is stored as a unified representation in working memory. We specifically aim to focus on the questions regarding how multisensory information is encoded in working memory and whether we memorize the individual unisensory representations separately and integrate them at a later stage, or whether they are memorized as part of an integrated, multimodal representation instead.

Feature Binding in Working Memory

To fully understand the importance of considering working memory from a multisensory perspective, it is necessary to discuss how information is organized within working memory. An important question here is whether each feature of an object is remembered separately or not (e.g., Luck and Vogel, 1997; Klaver et al., 1999; Vogel et al., 2001, 2005; Wheeler and Treisman, 2002; Olsson and Poom, 2005; Luria et al., 2010; Diamantopoulou et al., 2011; Luria and Vogel, 2011). For example, Luck and Vogel ( 1997) used a change detection task to examine the capacity of working memory for visual objects. Participants were presented with an array of stimuli, which they had to remember during an interval without the stimuli being present. After this retention interval a second array was presented and participants responded by indicating whether any visual changes had occurred between the second and the first array. Varying the number of visual objects that need to be memorized allows estimating the capacity of visual working memory. Luck and Vogel ( 1997) found that capacity was limited to approximately four objects, regardless of the number of feature dimensions, or individual features that needed to be remembered per object. This led them to conclude that visual working memory has an object-based and not a feature-based organization. It is important to note that these findings have not been replicated (Oberauer and Eichenberger, 2013; Hardman and Cowan, 2015). At the very least this suggests that feature binding can, but does not always, occur automatically.

Interestingly, research has shown that an asymmetry exists in binding the visual and spatial features of an object. Multiple studies have shown that processing the visual features of an object automatically bind this object to its spatial location (e.g., Jiang et al., 2000; Olson and Marshuetz, 2005). However, processing an object's spatial location does not result in the automatic binding of that object's visual features (Jiang et al., 2000). While these findings show that binding of multiple features can occur within the visuo-spatial domain, other studies have shown that binding of features can even occur across domains.

Prabhakaran et al. ( 2000) showed that participants memorized verbal and spatial information in an integrated fashion. Participants in this study performed faster and more accurate on a verbal-spatial delayed-match-to-sample task when the probe was a letter-location combination that was presented together in the sample array compared to a letter-location combination that was presented separately. The findings on binding of verbal and spatial information have been replicated and extended in multiple studies (Bao et al., 2007; Campo et al., 2008, 2010; Elsley and Parmentier, 2009; Guérard et al., 2013; Meier et al., 2014). For example, Bao et al. ( 2007) found that switching attention between verbal and spatial features was faster when they were features from one object than when they were features from separate objects. Additionally, Guérard et al. ( 2013) showed that phonological similarity of verbal material can carry over to the recall of spatial locations in a combined verbal-spatial serial recall task. Participants were sequentially presented with letters in specific locations and were asked to either recall the order of spatial locations shown or the order of letters shown. They found that the harmful effect of phonological similarity on verbal recall carried over to spatial recall, but that the harmful effect of spatial complexity on spatial recall did not carry over to verbal recall. While the question remains under which exact circumstances automatic binding or integration of cross-domain information occurs, the asymmetry found in visual feature and location binding as well as verbal and spatial binding, suggest that the automatic integration of information across domains can occur.

Multisensory Working Memory Representations

Despite the evidence for integration of information from different domains, surprisingly little research has examined how multisensory information is represented in working memory. One of the first studies to use cross-modal stimuli was done by Thompson and Paivio ( 1994). Participants memorized three different types of items: visual, auditory, or audiovisual for a later free-recall test. Thompson and Paivio found an improvement of free recall of cross-modal audiovisual stimuli compared to modality-specific, audio or visual stimuli. This superior audiovisual performance was not simply due to the double presentation of information in audiovisual conditions (audio and visual dual presentation), because picture-picture and sound-sound dual presentation conditions did not yield a similar improvement. When pictures in the picture-picture dual presentation condition were two different exemplars of the same item a slight improvement in free recall was found but audiovisual performance still resulted in higher recall rates. Goolkasian and Foos ( 2005) also found that recall rates were higher for picture/spoken word and written/spoken word dual presentation conditions compared to the double visual presentation of pictures and written words. These findings suggest that the improved memory performance is due to the combination of information from different modalities and not because of the redundancy of the information itself.

In the multisensory literature, additive effects, such as for example linear increases of brain activity for multisensory stimuli (For an overview see; Calvert, 2001), are considered to be exemplary of multisensory processing. By contrast, in working memory research, similar additive effects, such as an increase in capacity for audiovisual material compared to modality-specific material, are considered evidence for the independence of the two modalities. For example, the advantage of cross-modal object recall, in the study of Thompson and Paivio ( 1994) was explained by Paivio ( 1971, 1986) "dual coding" theory. This theory states that a memory trace for a cross-modal stimulus is a combination of the independent sensory traces that were encoded, which in turn can be recalled separately when the task so requires. While information from different modalities can interact to provide certain behavioral benefits, this information is in fact independent.

Originally, the dual coding theory was developed to explain the independent, simultaneous processing of verbal and non-verbal information, but has later also been used to explain the independent, simultaneous processing of auditory and visual information. It is important to note that these forms of information can interact. Verbal information can be both visual (e.g., written words) and/or auditory (e.g., spoken words), and nonverbal information can also be visual (e.g., complex visual scenes) and/or auditory (e.g., white noise). We can make a distinction between the format of a working memory representation, i.e., the sensory modality in which the information is perceived and/or processed (e.g., auditory-visual), and the content of the representation, i.e., the actual information that is transferred (verbal-non-verbal). For example, when memorizing an array of blue squares or a picture of a cat, it might be more efficient to memorize this verbally as the verbal code "blue squares" or "red cat". However, when the task requires one to describe the exact spatial location of each square, or point out a specific cat in an array of red cat pictures, it would be more efficient to use a visual code. We assume that information is processed in the format code that is most optimal for the current task. This implies that multiple format codes might be used for one and the same object, if that is more effective for memorizing that object.

Delogu et al. ( 2009) investigated how verbal and non-verbal auditory, visual, and audiovisual material is encoded in working memory. Participants were tested on immediate serial recall for sequentially presented visual, auditory, or audiovisual stimuli in either a non-verbal or verbal condition. In the non-verbal condition, stimuli were either pictures, environmental sounds, or a combination of both, and in the verbal condition, stimuli were either written words, spoken words, or a combination of both. Results showed that in the non-verbal condition serial recall for audiovisual stimuli was higher than recall for auditory or visual stimuli. In the verbal condition, recall for audiovisual material was still higher than recall for visual material, but auditory and audiovisual recall did not differ. The authors also found that preventing participants from articulating reduced memory performance in both the verbal and non-verbal conditions. This suggests that both in the verbal and in the non-verbal presentation conditions, the actual content of the representation was encoded in a verbal code. Furthermore, the verbal content seemed to play a key part in memorizing the stimuli in all conditions. This shows that the format in which information is presented is not necessarily the format in which the information is encoded. For example, when a participant is presented with an auditory stimulus of a meowing cat, it is possible that this sound calls forth a picture of a cat, or the word "cat", which is then kept in working memory instead of the auditory features of the original meowing sound that was presented. It is a requirement that the participant recognizes the presented sound as the meowing produced by a cat in order to "recode" the sound into a visual or verbal representation. This requires semantic information from long term memory to be integrated with the working memory representation. Delogu et al. ( 2009) concluded that their findings are compatible with Baddeley's ( 2000) working memory model where the existence of an episodic buffer integrates information from different modalities and combines this with semantic information from long term memory. Other studies have also shown the influence of semantic information from long term memory on visual working memory object representations (e.g., Olsson and Poom, 2005; Diamantopoulou et al., 2011) suggesting that information outside the pure visual domain can affect early visual object working memory. Similarly, Darling et al. ( 2012) found that accuracy on a digit serial recall task improved when the locations of presented digits matched the spatial configuration of a typical, numeral keypad (as found on a telephone or television remote) in a process they call visuospatial bootstrapping. They confirmed that this effect was due to the integration of the typical keypad representation from long-term memory with the working memory representation and not only to the binding between verbal and spatial information.

Thus far, the main goal of the studies discussed above was to provide insights into the dual code theory (Paivio, 1971, 1986) and/or the multiple component theory (Baddeley and Hitch, 1974; Baddeley, 2000) mainly by looking at recall performance for a wide variety of stimuli. To better understand how multisensory information interacts in working memory we can look at working memory capacity for cross-modal objects. As mentioned before, estimates of working memory capacity for features and objects have been used to infer that visual working memory representations are object based (Luck and Vogel, 1997). Likewise, by assuming that not only features within a modality but also across modalities are integrated into object representations, examining the number of cross-modal objects one can hold in memory compared to modality-specific objects could give insight into the organization of multisensory working memory. For instance, Saults and Cowan ( 2007) found that working-memory capacity for audiovisual material can exceed working-memory capacity for modality-specific material under certain conditions. In a series of five experiments, participants were presented with visual arrays of four to eight colored squares and auditory arrays of four spoken digits. They were instructed to memorize the visual array, the auditory array, or both. Interestingly, the performance advantage for audiovisual arrays disappeared when masks were used to block access to previously formed sensory memory traces. In this case, capacity for cross-modal stimuli was as high as the capacity of the highest modality-specific object, indicating that memory traces from an accessory sensory memory (echoic and/or iconic memory) contributed to the improvement of task performance. Since auditory and visual information did not additively contribute to memory performance when sensory memory traces were excluded, Saults and Cowan ( 2007) concluded that auditory and visual information share a common storage. Fougnie and Marois ( 2011) contested this interpretation by arguing that the formula used by Saults and Cowan ( 2007) to estimate the maximum number of object representations one can hold in working memory, might not adequately reflect the combined capacity of modality-specific stores. Fougnie and Marois argued that one item of auditory information generally places a larger load on memory than one item of visual information, suggesting that these modality-specific differences should be weighted accordingly in such a capacity estimate. Using an adapted formula in a series of three experiments, they found that even when using masks to exclude contributions of sensory memory traces, capacity for cross-modal items was superior to the capacity for modality-specific items. Contrary to Saults and Cowan ( 2007), they concluded that auditory and visual objects were stored in their own respective stores and contributed to performance without interfering.

Overall, there seems to be a performance benefit for the memorization of audiovisual stimuli compared to the memorization of modality-specific stimuli. It remains under debate, however, whether this benefit exists because these stimuli are integrated into a new amodal representation or because the independent storage of auditory and visual information contributes to performance in an additive fashion because they do not interfere. At this time the same effect is used to argue for both sides of the debate. Where some see the additive performance of audiovisual objects as proof for an interaction or even integration of information in working memory (e.g., Delogu et al., 2009), others see it as proof that sensory information is memorized in its own separate store (e.g., Fougnie and Marois, 2011).

In addition to examining performance benefits for the combination of auditory and visual processing, we can also study the disruption of processing for the combination of auditory and visual information. In traditional working memory research, interference paradigms have been used to show a double dissociation between two separate processing mechanisms. Meaning that when two processes use the same underlying system, interference will occur which impairs performance on both processes. The disruption of performance between modalities is referred to as cross-modal interference and would suggest that information from the different modalities interact at a certain level. For multisensory working memory this could mean that information from different modalities is maintained in a single, multisensory store. Evidence for cross-modal interference is still somewhat ambiguous, however. For instance, using a visual-pattern-recall and auditory-digit-recall dual task, Cocchini et al. ( 2002) did not find evidence for cross-modal interference on performance accuracy in working memory. The absence of such interference suggests that working memory operates in a domain-specific manner and is in accordance with the notion of parallel processing without interaction of information from different modalities. In contrast, Goolkasian and Foos ( 2005) showed that spoken words could interfere with the recall of pictures and written words when using long sequences of incongruent dually presented items. Likewise, Morey and Cowan ( 2004, 2005), did find cross-modal interference on performance accuracy when memory load was sufficiently high. They examined digit span using a verbal-visual dual task and found that participants showed interference for visual memory recall but only when the verbal load was sufficiently high (a load of 7 digits instead of 2). The interference patterns observed in audio-visual dual tasks are as of yet inconclusive on whether visual and auditory information share a limited capacity storage. Although interference paradigms could give us an answer on the question of whether information from different modalities share a limited capacity storage or not, they cannot answer whether the information from different modalities is integrated in this single storage, or maintained as independent modality-specific traces.

Thus far, research on multisensory working memory has shown that recall is better for cross-modal objects compared to modality-specific objects (Thompson and Paivio, 1994; Goolkasian and Foos, 2005; Delogu et al., 2009), working memory capacity is higher for cross-modal objects under certain circumstances (Saults and Cowan, 2007; Fougnie and Marois, 2011), and visual and auditory information can interfere with each other (Morey and Cowan, 2004, 2005; Goolkasian and Foos, 2005) but not always (Cocchini et al., 2002). Although a performance benefit for cross-modal objects is seen as evidence for integration in multisensory research, in working memory research it has traditionally been seen as evidence that modality-specific information from cross-modal objects is stored in separate stores. While we cannot definitively conclude that cross-modal objects are stored as fully integrated objects in working memory, it is apparent that cross-modal information interacts in working memory beyond what would be expected from modality-specific stores. The question is: at what stage or stages in the processing stream do these interactions occur?

Multisensory Processing, Selective Attention, and Working Memory

To answer this question we turn to research on multisensory processing and selective attention. The insights gained from this research could also inform questions about working memory for multisensory stimuli. In fact, more and more researchers have challenged the idea that working memory and attention are two separate systems (Cowan, 2001; Awh et al., 2006; Olivers, 2008; Oberauer and Hein, 2012; Kiyonaga and Egner, 2013; Klaver and Talsma, 2013). For example, Olivers ( 2008) reviews evidence for the notion that working memory and attention share the same capacity, content and control processes, suggesting they might be two aspects of the same process. Likewise, Kiyonaga and Egner ( 2013) discuss the literature that examined the effects of external attention on working memory representations, as well as, the effects of working memory representations on directing selective attention. These studies indicate that a competitive interaction between working memory and selective attention exists, implying that they share a limited resource. Kiyonaga and Egner ( 2013) state that attention and working memory should no longer be regarded as two separate concepts, but instead as one concept, where attention can be directed externally (selective attention) and/or internally (working memory). The idea of working memory as internal attention is in line with Cowan's ( 2001) original idea of working memory where a capacity limited focus of attention can shift between different levels of processing.

Given the above mentioned observations that working memory and attention are presumably two different aspects of the same underlying process, and considering that several studies have shown close ties between attention and multisensory processing, it is necessary to understand the implications of these ties for working memory. Instances where multisensory events guide and focus attention (also referred to as bottom-up effects) suggest an early integration of multisensory information, while instances where attention is needed for multisensory integration (also referred to as top-down effects) are indicative of late integration processes. There is evidence for both types of interaction between multisensory integration and attention. Factors that determine the predominance of either early and/or late interactions between information from different modalities are for example, task-relevancy (e.g., Busse et al., 2005), learned associations (e.g., Molholm et al., 2007), and saliency (e.g., Van der Burg et al., 2008).

An example of top-down influence of attention on multisensory integration was given by Talsma and colleagues (e.g., Senkowski et al., 2005; Talsma and Woldorff, 2005; Talsma et al., 2007). Using a rapid succession of task-relevant and irrelevant stimuli, they found that attention could influence the integration of cross-modal stimuli. Similarly, Alsius and colleagues (Alsius et al., 2005, 2007) have shown that attending elsewhere diminishes participants susceptibility to the McGurk illusion (McGurk and MacDonald, 1976). Based on these findings it appears that attending to the relevant, to-be-integrated stimuli is necessary to build a robust, integrated representation (Talsma et al., 2010).

However, evidence for bottom-up modulation of attention by multisensory integration has made it clear that multisensory processing can already happen in very early stages of perception (Giard and Peronnet, 1999; Molholm et al., 2002; Van der Burg et al., 2011). For instance, Van der Burg et al. ( 2011) presented dynamic displays consisting of line elements that randomly changed orientation. When a target orientation change was synchronized with a short, spatially uninformative tone, visual search was strongly facilitated as compared to when the tone was absent. The interpretation given to these results was that the tone and the synchronized orientation change were bound together into one coherent event, thereby forming a cross-modal singleton that "popped out" between the non-synchronized visual distractors. EEG data showed that this multisensory benefit was apparent as early as 50 ms post-stimulus onset and that the strength of this effect predicted the magnitude of the behavioral benefit during visual search, due to the auditory signal.

The findings above imply that both top-down (task-relevance and learned associations) as well as bottom-up (salience) processes are involved in multisensory integration. To resolve this apparent contradiction between a bottom-up view of multisensory processing, where early multisensory effects seem to drive attention, and a top-down view of multi-sensory processing, where attention seems to be required to integrate cross-modal objects, Talsma et al. ( 2010) proposed a unified framework of attention and multisensory processing. According to this framework, early pre-attentive processes can bind multisensory inputs together, but only when competition among the individual inputs is low. Thus, the early latency processes serve to cross-feed low-level information between the individual sensory cortices involved in the integration processes. Early interactions might serve to realign auditory and visual input signals. Auditory information might give temporal information to visual cortex whereas visual information might provide spatial information to auditory processing.

This pre-attentive early integration would, according to Talsma et al. ( 2010), only be possible, however, if the stimuli presented in one modality do not need to compete for processing capacity with other stimuli in that same modality. If there is competition among multiple stimuli in one modality, top-down attentional control may be required to filter out any stimulus that is not task relevant, thereby prioritizing those stimuli that are task relevant. Consistent with this view, Van der Burg et al. ( 2012) found that the earlier mentioned automatic capture by a synchronized cross-modal event can be modulated by the size of the attentional window, meaning that when participants were less focused the effect of the cross-modal pop out was stronger than when participants were forced to focus on a small cue before the synchronized cross-modal event. In conclusion, stimulus-driven, bottom-up processes can automatically capture attention towards multisensory events. Top-down attention can in turn facilitate the integration of multisensory information which leads to a spread of attention across sensory modalities.

Based on the previously mentioned idea that external attention and internal attention (working memory) are two aspects of the same process, findings in attentional research could be applied to working memory. It has been shown that spatial attention can actively influence working memory representations by facilitating encoding (Uncapher et al., 2011) and improving the recall of memorized representations (Murray et al., 2013). These effects are found not only within a single modality, but also across modalities. For instance, an auditory cue can draw attention to a visual object and vice versa (Spence and Driver, 1997; Koelewijn et al., 2009). Similar effects for working memory have been found by Botta et al. ( 2011). They examined the effect of visual, auditory, and audiovisual cues on working memory for arrays of colored squares in a change detection task. The cross-modal and modality-specific cues could either capture attention towards the hemifield which contained the to-be-remembered objects, or towards the opposite hemifield which contained the to-be-ignored objects. They found that audiovisual cues had a larger influence on performance accuracy than modality-specific visual or auditory cues. Memory accuracy was increased when an audiovisual cue was presented on the same side as the target and it was decreased when the audiovisual cue was presented on the opposite side. Both the facilitation and impairment of memory performance was larger for audiovisual cues compared to visual cues. Although these data do not directly address the question of how a cross-modal object is represented in working memory as such, they do tell us that multisensory information has a bottom-up effect on the subsequent memorization of a unisensory object.

Investigation of top-down effects of working memory on attention has revealed that working memory content can affect the allocation of visual selective attention (Olivers et al., 2006). In a multisensory context, Murray et al. ( 2004) found that discrimination accuracy of visual objects, presented 20 s after initial presentation, improved when the initial presentation was a picture-sound combination compared to a unisensory picture. EEG data revealed that the neuronal response to a cross-modal stimulus happened as fast as 60-136 ms and predominantly influenced activation in the right lateral occipital complex. Where a semantically congruent picture-sound combination increased discrimination accuracy on a second presentation, a pure tone decreased discrimination accuracy on a second presentation (Lehmann and Murray, 2005; Thelen et al., 2012). Thelen et al. ( 2015) replicate these earlier findings, while also showing the same effects in the auditory modality. Single-trial multisensory memories affect later auditory recognition. If cross-modal objects were congruent (visual and auditory information match semantically) accuracy was higher compared to unisensory stimuli but became worse if objects were incongruent or meaningless. Unisensory percepts seem to trigger the multisensory representations associated with them, suggesting at least a partially integrated storage in memory. Yet, it seems a multisensory representation stored in memory is only beneficial for memory performance when sounds and pictures are semantically congruent. These studies show that an internal representation is formed in which both the visual and auditory information is encoded. Moreover, they also indicate that information presented in a task irrelevant modality interferes with the task relevant representation. But although this still does not address the question of whether unisensory information is still accessible it does show that the original unisensory representations are closely related. Similar to the findings in research on attention and multisensory integration, it seems that top-down and bottom-up processes play an important part in the integration of cross-modal information in working memory representations.

Predictive Coding and Multisensory Working Memory

One influential framework that can explain the intricacies of top-down and bottom-up interactions in multisensory memory is that of predictive coding. The predictive coding framework states that the brain produces a Bayesian estimate of the environment (Friston, 2010). According to this view, stochastic models of the environment exist in the brain, which are continuously updated on the basis of processed sensory information. Higher-order brain areas thus provide the lower areas with predictions (or in Bayesian terms "priors") that influence the processing of ongoing sensory input. A strong mismatch between the prediction and the actual sensory input will then result in a major update of the internal model. Thus when we are in a complex environment with many stimuli competing for processing capacity, incongruence between the top-down predictions of the environment and the present incoming environmental information can determine the priority with which incoming stimuli need to be processed and integrated. The processed information changes the predictions and vice versa. Bottom-up sensory processing and top-down predictions mutually define each other continuously. In this way, the predictive coding view can explain how top-down and bottom-up processes interact in multisensory integration.

Talsma ( 2015) recently argued that the dynamic model of our environment provided by the aforementioned stochastic representations is essential to understanding the interaction between basic (multi)sensory processing on the one hand, and memory and attention on the other. For instance, Vetter et al. ( 2014) showed that actual auditory stimulation as well as imagined sounds could activate the visual cortex. Based on the predictive coding framework, these authors argued that visual cortex activation came about because either direct sensory information or a stored memory representation thereof could update the internal representation of the sound and therefore indirectly influence processing in visual cortex accordingly. This suggests that attention, memory, and multisensory processing are intrinsically intertwined. Similarly, Berger and Ehrsson ( 2013, 2014) showed that imagined sounds can mimic the effects of actual sounds in a number of well-known multisensory illusions, such as the bounce-pass illusion (Sekuler et al., 1997), the McGurk effect (McGurk and MacDonald, 1976), or the ventriloquist illusion (Howard and Templeton, 1966), and show independent of each other that visual cortex can be activated both by multisensory stimulation and by memory. Based on these findings, Talsma ( 2015) argued that despite the fact that several studies showed that auditory and visual inputs can interact at very early processing stages, the actual integration of the sensory inputs into a coherent mental representation occurs at later, higher-order processing stages.

An important consequence of applying the predictive coding framework is that our internal representation is assumed not only to be built on the basis of direct sensory input, but that it is also updated (and made consistent with) information stored in memory. Thus, attention is assumed to play an essential role in regulating how our sensory input is combined with these pre-existing representations stored in long-term memory. This is largely consistent with Cowan's ( 2001) idea of the focus of attention, which is a part of activated long-term memory, as well as with Baddeley's ( 2000) episodic buffer, although, Baddeley recently argued that attention in the form of the central executive was not necessary for the integration of multiple sources of information in the episodic buffer (Baddeley et al., 2011).

A further consequence of applying the predictive coding framework is that the internal representation is by definition always multisensory. Moreover, the active representation integrates all possible sources of information, including semantic information from long-term memory. Thus, even when only a unisensory stimulus is presented, associated representations will be activated as well. These can include information from other modalities, prior experience with the stimulus, or learned associations. Because the formation of this internal mental representation is an active process that influences ongoing processes in the sensory cortices, this model can explain why memory traces in one modality can be strengthened or corrupted by traces in another one. Furthermore, because the active representation sends feedback information to the low-level processes in sensory cortices it can be assumed that the original unisensory memory traces are still present albeit in a relatively fragile state.

Multisensory Working Memory Representations in Current Models

The active internal environmental model as proposed by the predictive coding framework would be akin to what we would describe as a multisensory working memory representation. This memory representation does not only consist of information coming from different modalities but also includes information from long-term memory such as semantic knowledge or learned associations. Taking the previously mentioned example of memorizing a cat picture the multisensory representation includes not only the visual features of the cat, but also long-term semantic knowledge of cats, autobiographical knowledge (previous personal experience with cats), and information from modalities not presented with the picture (the sound a cat makes or the knowledge that its fur is soft to the touch). We assume that working memory has an amodal central storage component. Whether this is the main component of working memory as suggested by Cowan ( 2001) or a part of a bigger system like the episodic buffer in (Baddeley's, 2000; Baddeley et al., 2011) remains a point for further investigation.

The predictive coding framework would suggest that incoming sensory information is constantly used to update the internal environmental model, implying that incoming stimuli tend to integrate into a coherent multisensory representation. This framework can also explain why working memory is amodal in some cases and modality specific in others. For instance, Postle ( 2006) argued that working memory for modality-specific stimuli occurs in the sensory cortices. Recently, Yonelinas ( 2013) suggested that high-resolution bindings are stored in the hippocampus that can be used to support perception and working memory, specifically in memorizing (combinations of) complex features. In the latter case it is plausible that the multisensory representation will be activated, whereas in the former case it is not. Based on this, one important implication of the predictive coding approach is that differences in task and stimulus complexity can yield rather drastically different outcomes. With this in mind a recommendation for future research would be to consider effects of task and stimulus complexity on working memory activation.

Based on the above mentioned framework, we assume that sensory cortices can retain small amounts of modality-specific information (as suggested by Postle, 2006) and that this information supports a multisensory memory representation in higher order areas (e.g., the hippocampus; Yonelinas, 2013). Whether working memory for a specific task involves the higher-order areas or the sensory areas to retain information for limited time depends on the task and the information that needs to be memorized. For example, simple flashes and beeps could be retained in the sensory areas, whereas more complex information would also require the higher-order areas. In that sense the sensory cortices would retain information in a manner similar to separate slave systems (Baddeley and Hitch, 1974) or the recently suggested peripheral storage (Cowan et al., 2014).

Summary and Conclusions

In this paper we have reviewed recent developments in multisensory working memory research. Research has shown that cross-modal information interacts in working memory beyond what would be expected from the traditional modality-specific stores. Recall is better for cross-modal objects compared to modality-specific objects (Thompson and Paivio, 1994; Goolkasian and Foos, 2005; Delogu et al., 2009), working memory capacity can be higher for cross-modal objects than for unimodal objects (Saults and Cowan, 2007; Fougnie and Marois, 2011), and visual and auditory memory can interfere with each other (Morey and Cowan, 2004, 2005; Goolkasian and Foos, 2005). Furthermore, multisensory information has an effect on the subsequent memorization of a unisensory object (Botta et al., 2011) and multisensory memory representations can influence subsequent unisensory stimulus discrimination (Murray et al., 2004; Lehmann and Murray, 2005; Thelen et al., 2012, 2015). Taken together, these studies show that sensory representations in multiple modalities interact more with each other than can be explained by classical modal models.

Paivio's ( 1971, 1986) dual coding theory states that although cross-modal information can interact it is in fact independent, because modality-specific information can still be retrieved in isolation. However, studies done by Thelen and colleagues (Thelen et al., 2012, 2015) show that this retrieval of modality-specific information from a cross-modal representation is more difficult than assumed, because a task irrelevant modality interferes with the task relevant representation. Moreover, higher-order representations of the external world built from memorized information have been shown to influence visual processing. Complex representations seem to be formed in working memory, consisting of the integration of several independent representations that can be sensory, and short- or long-term memory activations. Depending on task requirements either just the simple modal representation or the complex high-resolution binding of several features at once will become active. Therefore, we conclude that working memory is in essence multisensory, and that this must be taken into account to achieve a realistic understanding of how working memory processes maintain and manipulate information.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank the editor and reviewers for their helpful comments and suggestions on earlier drafts of this paper.

References

Howard I. P., Templeton W. B. (1966). Human Spatial Orientation. Oxford, England: John Wiley and Sons.

Paivio A. (1971). Imagery and Verbal Processes. New York: Holt, Rinehart and Winston.

Paivio A. (1986). Mental Representation: A Dual Coding Approach. New York: Oxford University Press.

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A multisensory perspective of working memory

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Although our sensory experience is mostly multisensory in nature, research on working memory representations has focused mainly on examining the senses in isolation. Results from the multisensory processing literature make it clear that the senses interact on a more intimate manner than previously assumed.

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What College Teachers Should Know About Memory: A
Perspective From Cognitive Psychology

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Rethinking Transfer

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Memory,Attention & Distraction

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Memory, Attention, and Distraction [Internet]. Salt Lake City (UT): Genetic Science Learning Center; 2016 [cited 2020 Apr 30] Available from https://learn.genetics.utah.edu/content/memory/

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How can teachers at Sycamore Middle School meet the educational needs of all of their students?

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How can teachers at Sycamore Middle School meet the educational needs of all of their students?

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How can teachers at Sycamore Middle School meet the educational needs of all of their students?

Today’s classrooms are more diverse than ever. Students see, hear, speak, move, read, write, understand English, organize, engage, and remember in so many different ways. At the same time, current law (e.g., Every Student Succeeds Act [ESSA], Individuals with Disabilities in Education Act, 2004 [IDEA 2004]) and contemporary teaching practices not only expect and encourage education in inclusive settings but they also require evidence of it. The teachers at Sycamore Middle School know that meeting such diverse needs in the classroom is a challenging task.

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Every Student Succeeds Act [ESSA]

Federal education law originally enacted in 1965 as the Elementary and Secondary Education Act (ESEA). This law now mandates the use of academic and behavioral evidence-based practices. When this act was reauthorized in 2001, it was referred to as the No Child Left Behind Act (NCLB). The Every Student Succeeds Act (ESSA) reauthorized the Elementary and Secondary Education Act in 2015 and went into effect in the 2017–2018 school year.

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Individuals with Disabilities in Education Act, 2004 [IDEA 2004]

Name given in 1990 to the Education for All Handicapped Children Act (EHA) and used for all reauthorizations of the law that guarantees students with disabilities the right to a free appropriate public education in the least-restrictive environment.

Did You Know?

UDL adapts and applies the ideas and concepts associated with universal design in architecture. The overarching idea of universal design is that buildings and tools should be accessible to everyone—those with and those without disabilities. For example, curb cuts allow people who use wheelchairs to move freely and independently from sidewalks to streets or parking lots. At the same time, they benefit people who use strollers, shopping carts, scooters, and skateboards.

To meet the needs of all students in the general education classroom to the greatest extent possible, a team of Sycamore Middle School personnel convenes to research and evaluate potential approaches. They discover Universal Design for Learning (UDL), which appears to meet their needs. UDL provides a research-based framework for teachers to incorporate flexible materials, techniques, and strategies for delivering instruction and for students to demonstrate their knowledge in a variety of ways. Developed by researchers at the Center for Applied Special Technology (CAST), this framework stands in contrast with the “one size fits all” instructional approach that has traditionally been used in classrooms, as outlined in the table below.

Universal Design in Architecture

In 1990 Congress passed the Americans with Disabilities Act (ADA), a law that prohibits discrimination against persons with disabilities in employment, transportation, public accommodations, and telecommunications. The ADA guarantees individuals with disabilities greater access to participation in the everyday activities enjoyed by those without disabilities. In response, architects developed the principles of universal design to guide the creation of new buildings and tools for living so that they are accessible to as many people as possible, including those with disabilities. Whether we realize it or not, we encounter many examples of universally designed features or products in our daily lives. The seven basic principles of universal design that guide the creation of new buildings and tools for living are described in the table below.

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Americans with Disabilities Act (ADA)

Federal disability antidiscrimination legislation passed in 1990 to guarantee basic civil rights to people with disabilities; similar to those provided to individuals on the basis of race, sex, national origin, and religion, ADA guarantees equal opportunity for individuals in areas of employment, transportation, government services, telecommunications, and public accommodations.

Principles of Universal Design
Principle | Description | Example

Equitable use

The design is useful and marketable to people with diverse abilities.

Curb cuts

Flexibility of use

The design accommodates a wide range of individual preferences and abilities.

Tools that can be used by both left- and right-handed people

Simple and intuitive

Use of the design is easy to understand, regardless of the user’s experience, knowledge, language skills, or current concentration level.

Universal symbols

Perceptible information

The design communicates necessary information effectively to the user, regardless of ambient conditions or the user’s sensory abilities.

Crosswalk signal with auditory indicator

Tolerance for error

The design minimizes hazards and the adverse consequences of accidental or unintended actions.

“Are you sure you want to delete this file?”

Low physical effort

The design can be used efficiently and comfortably and with a minimum of fatigue.

Motion sensor to open door

Size and space for approach and use

Appropriate size and space is provided for approach, reach, manipulation, and use, regardless of user’s body size, posture, or mobility.

Wide doorways, low thresholds

The Center for Universal Design

(Close this panel)

Traditional Instruction

Universal Design
for Learning Instruction

Teachers typically deliver content one way.

Students are passive learners who acquire information through memorizing, practicing, and taking tests.

The learning environment encourages students to sit quietly and work on an identical task.

Students’ skills and knowledge of content are assessed using one method.

Teachers deliver content in multiple ways.

Students are active learners who engage and analyze the content to gain understanding.

The learning environment encourages students to explore the content based on personal interests, preferences, or abilities.

Students are allowed to demonstrate their skills and knowledge of content using one of several methods.

Adapted from Universal Design for Learning: A Guide for Teachers and Education Professionals.

CAST is an organization that primarily conducts research related to Universal Design for Learning. Listen as David Rose, a founder of CAST, and Grace Meo, formerly of CAST, describe UDL.

David Rose
CAST founder; Chief Scientist,
Cognition & Learning

(time: 0:29)

Grace Meo
Former CAST Director of Professional
Development & Outreach Services

(time: 0:24)

Transcript: David Rose

UDL is a framework for teaching and learning. It assumes from the beginning that learners are very different. The design part of universal design is designing a learning environment that is as diverse as the students are. There’s many options for how to learn within it. So the idea of Universal Design for Learning is to create good learning environments that work across a wide spectrum of students.

Transcript: Transcript: Grace Meo

In addition to thinking about the diversity of students, the focus of UDL is to really engage all students in learning and to support all individuals to gain knowledge and to gain skills in learning. So UDL is a framework for learning but focusing on engaging, building knowledge and skills, and ensuring an enthusiasm for learning.

The primary reason the Sycamore team favors UDL is that it addresses the educational needs of all students: average learners, English learners, students who have received poor instruction in the past, students with learning disabilities, students with sensory and motor challenges, and gifted and talented students, among others. UDL benefits all students by:

Meeting the needs of the widest range of students by reducing the number of barriers to learning

Providing challenging, salient, and age-appropriate materials to students with a range of abilities

Allowing students to learn in accordance with their learning preferences

Creating alternative ways for students to both receive and deliver information

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Learning Preference

Learning preference refers to the mode by which a person prefers to learn or process information. The four primary learning modalities (i.e., sensory modalities) are visual, auditory, tactile, and kinesthetic.

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Visual Learners: remember what they see and benefit from visual aids such as charts, diagrams, and maps

Auditory Learners: learn through lectures and class discussions and do well at following oral instructions

Kinesthetic Learners: benefit from movement activities that require them to use their bodies

Tactile Learners: prefer to learn through tactile or hands-on activities

Listen as David Rose discusses the benefits of UDL (time: 1:27).

David Rose
CAST founder; Chief Scientist,
Cognition & Learning

Transcript: David Rose

The benefits of Universal Design for Learning are higher achievement across the full spectrum of students. Sometimes, people think that Universal Design for Learning is primary for students with disabilities or English language learners, students who are struggling in the classroom. But when Universal Design for Learning is done well, it actually provides just the right challenge and just the right support for students throughout the classroom, including students who are gifted and talented, students who are average in most respects, and students who have disabilities. There’s three kinds of benefits of UDL. First, the benefit of UDL for students is that there are many ways to succeed, and the fact that there are many ways to succeed means that students can be engaged, can make rapid progress and feel like competent learners. The real goal is that, by the end of their schooling, they’ll be expert learners. Two, there are benefits for teachers. What UDL does is provide ways for teachers to succeed as well. And, thirdly, the benefits of UDL for administrator is that there’s more ways to support teachers in doing a good job that are not cost ineffective.

Activity

Teachers, like students, have particular learning strengths or preferences. In fact, teachers’ learning strengths often influence their teaching styles. For example, a teacher who prefers to learn through auditory means might tend to present information through lectures and discussions, a decision that might prove disadvantageous for students who have difficulty grasping information this way (e.g, students with auditory processing difficulties, English language learners). Remember that it is helpful for both teachers and students to be aware of their learning strengths or preferences. Click here to assess your preferred learning modality using the Barsch Inventory. Be aware that research does not support the “learning styles” theory that students learn better when they are taught via preferred modalities. In other words, there is no evidence that visual learners show greater learning gains when taught using visual means. However, the use of preferred modalities can improve engagement and reduce barriers for some students (e.g., those with disabilities, English language learners).

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IRIS | Page 1: Universal Design for Learning (UDL)

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Today's classrooms are more diverse than ever. Students see, hear, speak, move, read, write, understand English, organize, engage, and remember in so many different ways. At the same time, current law (e.g., Every Student Succeeds Act [ESSA], Individuals with Disabilities in Education Act, 2004 [IDEA 2004]) and contemporary teaching practices not only expect and encourage education in inclusive settings but they also require evidence of it.

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Learning & Transfer

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Read "How People Learn: Brain, Mind, Experience, and School: Expanded Edition" at NAP.edu

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Read chapter 3 Learning and Transfer: First released in the Spring of 1999, How People Learn has been expanded to show how the theories and insights from ...

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8 Reasons Why Experiential Learning Is the Future of Learning

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8 Reasons Why Experiential Learning Is The Future Of Learning by Mr Rajiv Jayaraman, Founder and CEO, KNOLSKAPE

Experiential Learning Is The Future Of Learning

More than a hundred years ago, Hermann Ebbinghaus formulated the learning curve, which describes the relationship between memory and time. In a nutshell, it says that, during a lecture, if your absorption rate is at 100 percent on day one, there is a 50-80 percent loss of learning from the second day onward, which is reduced to a retention rate of just 2-3 percent at the end of thirty days.

This theory is even more relevant in today's world where attention spans have come down and learning sometimes is reduced to 140 characters!

How then can 'Experiential Learning' help overcome this situation?

We believe there are eight reasons why experiential learning is the future of learning.

1. Accelerates Learning
Repetitive Learning or learning by rote has long been replaced by 'Learning by Doing.' Experiential Learning methodology uses critical thinking, problem solving and decision making to deliver a training module. This has become an established method to accelerate learning.

2. Provides a Safe Learning Environment
Simulations use real life scenarios that depict several challenges, which a participant will eventually face after the course completion. It is only natural that mistakes happen during the course of learning, and using simulations is like taking kids to a playground, and getting them to have fun, try new things and learn, in a safe controlled environment.

3. Bridges the Gap Between Theory and Practice
By moving beyond theory to the realm of "learning by doing,' the trainee gets a first hand experience of practicing what has been taught. This plays a crucial role in retaining concepts and ideas.

4. Produces Demonstrable Mindset Changes
There are very few learning methods that can have a dramatic impact on the participant's mindset. Experiential Learning is one of them. Management guru Henry Mintzberg pointed out long ago that, "Leadership, like swimming, cannot be learned by reading about it".

5. Increases Engagement Levels
The high focus on collaboration and learning from each other benefits the participant as it increases engagement. On the other hand, since the participant is immediately involved in the problem solving activity or event, the level of ownership of the outcome is high.

6. Delivers Exceptional Return on Investment (RoI)
Experiential learning is personal and effective in nature, influencing both feelings and emotions as well as enhancing knowledge and skills. It goes beyond classroom learning and ensures that there is high level of retention, thereby delivering exceptional RoI over a traditional learning program.

7. Provides Accurate Assessment Results
Assessing the effectiveness of the training program in terms of the benefits to the trainees and the company is a crucial element of any learning program. Most assessments are data driven and traditional tools use tests to measure effectiveness. When it comes to experiential learning programs, it is extremely difficult to gather data, which can be used for assessments. This is where analytics come in. When combined with simulations and gamification, experiential training products become a powerhouse of data, which can be used to deliver assessments results accurately across cognitive learning, skills affect and objective results. The analytics engines in these simulations record, analyze and provide a detailed report on the participants' interaction throughout the simulation.

8. Enables Personalized Learning
In order to enable personalized learning, every program needs to enable a journey through the following phases: Assessment, teaching and learning strategy, and curriculum choice. Experiential learning methodology is highly effective in meeting these requirements to enable personalized learning. It is a radical departure from traditional learning methods and takes the learning beyond the classroom. The participants set their own learning pace. By combining technology and simulations with experiential learning, companies are making this concept available anytime and anywhere, across multiple devices. This has introduced the concepts of flipped classroom, where the learning goes to the students and not the other way.

Mr Rajiv Jayaraman is one of the speakers at LEARNTech Asia 2014. LEARNTech Asia 2014 will be held in Singapore at the Marina Bay Sands (13-14 November 2014). The topic he will be speaking on is "Designing Immersive Games for Experiential Learning". For more information on the conference, please visit http://learntechconf.com/.

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8 Reasons Why Experiential Learning Is The Future Of Learning - eLearning Industry

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8 Reasons Why Experiential Learning Is The Future Of Learning by Mr Rajiv Jayaraman, Founder and CEO, KNOLSKAPE More than a hundred years ago, Hermann Ebbinghaus formulated the learning curve, which describes the relationship between memory and time.

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Beginning with What Students Know