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A Brain Marker Pinpoints Vulnerability for Future Life Stress {Duke University Research}

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Department of Psychology, University of Haifa, Haifa, Israel

Functional Brain Center, Wohl Institute of Advanced Imaging, and School of Psychological Sciences, Faculty of Medicine and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel

Department of Psychology, Neuroscience and Cognitive Science Program, and Maryland Neuroimaging Center, University of Maryland, College Park, College Park, MD, USA

Recent years have witnessed the emergence of powerful new tools for assaying the brain and a remarkable acceleration of research focused on the interplay of emotion and cognition. This work has begun to yield new insights into fundamental questions about the nature of the mind and important clues about the origins of mental illness. In particular, this research demonstrates that stress, anxiety, and other kinds of emotion can profoundly influence key elements of cognition, including selective attention, working memory, and cognitive control. Often, this influence persists beyond the duration of transient emotional challenges, partially reflecting the slower molecular dynamics of catecholamine and hormonal neurochemistry. In turn, circuits involved in attention, executive control, and working memory contribute to the regulation of emotion. The distinction between the 'emotional' and the 'cognitive' brain is fuzzy and context-dependent. Indeed, there is compelling evidence that brain territories and psychological processes commonly associated with cognition, such as the dorsolateral prefrontal cortex and working memory, play a central role in emotion. Furthermore, putatively emotional and cognitive regions influence one another via a complex web of connections in ways that jointly contribute to adaptive and maladaptive behavior. This work demonstrates that emotion and cognition are deeply interwoven in the fabric of the brain, suggesting that widely held beliefs about the key constituents of 'the emotional brain' and 'the cognitive brain' are fundamentally flawed. We conclude by outlining several strategies for enhancing future research. Developing a deeper understanding of the emotional-cognitive brain is important, not just for understanding the mind but also for elucidating the root causes of its disorders.

Until the 20th century, the study of emotion and cognition was largely a philosophical matter. Although modern perspectives on the mind and its disorders remain heavily influenced by the introspective measures that defined this earlier era of scholarship, the last several decades have witnessed the emergence of powerful new tools for assaying the brain and a remarkable acceleration of research to elucidate the interplay of emotion and cognition ( Pessoa, 2013; Braver et al., 2014; Dolcos and Denkova, 2014). The immediate goal of our Special Research Topic was to survey recent advances in understanding how emotional and cognitive processes interact, how they are integrated in the brain, and the implications for understanding the mind and its disorders ( Okon-Singer et al., 2014b; Figure 1). Here, we consider ways in which this rapidly growing body of work begins to address some more fundamental questions about the nature of cognition-emotion interactions, highlighting key points of consensus. By focusing attention on the most important outstanding questions, we hope to move the field forward. First, we hope that answers provided by our contributors will stimulate discussion. Second, we hope that juxtaposing clear theoretical goals against the current state of the science will motivate new and impactful research. Clearly, our understanding of emotion-cognition interactions remains far from complete. Indeed, we are reminded of Ekman and Davidson's comment: "There are many promising findings, many more leads, [and] a variety of theoretical stances" ( Ekman and Davidson, 1994, p. 3). We conclude by outlining several strategies for enhancing future research. With continuing effort, some of the fundamental questions will be decisively addressed. In some cases, the questions themselves will evolve, as in other areas of the biological sciences.

FIGURE 1. The top 200 scientific terms used in the Special Research Topic. The typeface is scaled proportional to the frequency of each term. The figure was generated using http://www.wordle.net.

How does Emotion Influence Cognition?

Many of our contributors highlighted evidence that the perception of emotionally-salient stimuli and the experience of emotional states can profoundly alter cognition.

Emotional Cues Grab Exogenous Attention and Modulate Endogenous Attention

Importantly, attention can also be guided in an endogenous fashion by internal goals (e.g., rules, instructions, and plans) as well as moods and motivational states (e.g., feeling anxious or hungry). Mohanty and Sussman (2013) discuss evidence demonstrating that emotion and motivation can guide attention to congruent cues (e.g., food when hungry). In particular, they show that subcortical regions proximally involved in determining value and orchestrating emotional states (e.g., amygdala, substantia nigra) can facilitate endogenous attentional processes implemented in frontoparietal regions and can strengthen activation in relevant sensory regions (e.g., face-selective regions of the fusiform gyrus when anticipating an angry face). This extended network, encompassing sensory, attentional, and emotional circuits, facilitates the rapid detection of emotionally-significant information.

Attentional Biases to Emotional Cues are Plastic

Anxious individuals tend to allocate excess attention to threat and there is evidence that this cognitive bias causally contributes to the development and maintenance of anxiety disorders ( Bar-Haim et al., 2007; Hakamata et al., 2010; MacLeod and Mathews, 2012; Singer et al., 2012; Van Bockstaele et al., 2013; MacLeod and Clarke, 2015). Extreme anxiety and behavioral inhibition often emerges early in development ( Fox et al., 2005a; Blackford and Pine, 2012; Fox and Kalin, 2014), raising important questions about the degree to which childhood attentional biases to threat are plastic and can be influenced by early experience ( Shechner et al., 2012; Bar-Haim and Pine, 2013; Henderson et al., 2014; MacLeod and Clarke, 2015).

Emotion Exerts Persistent Effects on Attention

Emotions are often conceptualized as fleeting and most imaging and psychophysiological studies of emotion focus on transient responses to punctate emotional challenges. Yet, there is growing evidence that emotions can have lingering consequences for cognition and behavior ( Davidson, 2004; Suls and Martin, 2005; Hajcak and Olvet, 2008; Qin et al., 2009).

Here, for example, Vaisvaser et al. (2013) combined serial measures of emotional state, neuroendocrine activity, and resting-state brain activity to demonstrate that alterations in amygdala-hippocampal functional connectivity persist for more than 2 h following exposure to intense social stress. Along conceptually similar lines, Morriss et al. (2013) use electrophysiological techniques to show that endogenous attention is potentiated for several seconds following brief emotional challenges (i.e., standardized emotional images).

Distracting Emotional Cues Readily Penetrate the Gate Protecting Working Memory

Distracting Emotional Cues Disrupt Cognitive Control and Working Memory

Emotion Strengthens Some Cognitive Processes while Weakening Others

With the ascent of evolutionary theory in the 19th century ( Darwin, 1872/2009, 1872), many scientists adopted the view that emotions are functional and enhance fitness ( Susskind et al., 2008; Todd et al., 2012; Sandi, 2013; Schwabe and Wolf, 2013; Todd and Anderson, 2013); in short, that emotions are more adaptive than not and "that there is typically more cooperation than strife" between emotion and cognition ( Levenson, 1994).

Emotional States Promote Mood-Congruent Thoughts and Actions

Emotional Traits Influence Cognitive Performance, Even when Emotional Cues, and Challenges are Absent

Emotional traits are often conceptualized as diatheses for emotional states ( Matthews et al., 2009). Thus, individuals with high levels of neuroticism or negative emotionality are thought to be prone to exaggerated anxiety in the face of trait-relevant cues, contexts, and challenges (e.g., punishment, negative feedback), as illustrated in the contributions from Kessel et al. (2013); Moser et al. (2013), and Proudfit et al. (2013). Yet, a considerable body of neurophysiological evidence indicates that emotional traits are embodied in the on-going activity and connectivity of the brain ( Canli et al., 2005; Fox et al., 2008; Shackman et al., 2009; Rohr et al., 2013; Birn et al., 2014a, b). Likewise, the sustained levels of heightened vigilance and distress characteristic of individuals with anxiety disorders are most apparent in the absence of clear and imminent threat ( Davis et al., 2010; Lissek, 2012; Grupe and Nitschke, 2013). These observations raise the possibility that emotional traits could influence cognition in the absence of explicit emotional distraction or challenge ( Watson and Clark, 1984; Bolger and Schilling, 1991; Suls and Martin, 2005).

How does Emotion Influence Emotion?

Emotion Alters Reinforcer Sensitivity

How does Cognition Influence and Regulate Emotion?

Humans frequently regulate their emotions and they do so using a variety of implicit and explicit cognitive strategies ( Gross, 1998a, b; Gross and Thompson, 2007; Gross et al., 2011; Webb et al., 2012; Okon-Singer et al., 2013). Implicit strategies are unintentional and appear to occur without effort or insight. In contrast, explicit strategies are voluntary and demand a degree of effortful control.

Several contributors to our Special Research Topic described new insights into the mechanisms supporting the cognitive regulation of emotion and the role of emotion regulation in psychiatric disorders, such as depression.

Attention Regulates Emotion

The Choice of Cognitive Regulation Strategy Depends on the Situation

Sheppes and Levin (2013) emphasize that humans frequently use effortful cognitive strategies to cope with and regulate their emotions (e.g., Egloff et al., 2006; Ehring et al., 2010). For example, they may try to distract themselves or they may try to reappraise the situation in a more positive light. Sheppes and Levin (2013) provide evidence that not only do individuals have the capacity to flexibly choose emotion regulation strategies, but that they do so in ways that are strongly influenced by the emotional context (e.g., choosing to reappraise when presented with mild negative pictures, and to distract themselves in face of highly aversive stimulation).

Working Memory Regulates Emotion

Some strategies for regulating emotional distress, such as reappraisal, require the effortful maintenance of an explicit regulatory goal. Rolls (2013) reviews evidence suggesting that this critically depends on working memory. More broadly, he suggests that goals, attentional sets, and other kinds of declarative knowledge held in working memory play a central role in regulating the output of emotional systems.

How are Emotion and Cognition Integrated?

A number of contributors highlighted advances in our understanding of the neural mechanisms that serve to integrate emotion and cognition.

Canonical Territories of the 'Cognitive' Brain Regulate Emotion

The dorsolateral prefrontal cortex (dlPFC) is a canonically 'cognitive' region of the brain, well known for its critical role in reasoning and higher cognition (e.g., endogenous attention, working memory, and cognitive control; Roberts et al., 1998; Miller and Cohen, 2001; D'Esposito and Postle, 2014). Yet, there is growing evidence that the dlPFC plays a key role in the top-down control of emotion and motivated behavior ( Fox et al., 2005b; Koenigs et al., 2008; Zaretsky et al., 2010; Buhle et al., 2013; Frank et al., 2014; Treadway et al., 2014).

Here, Clarke and Johnstone (2013) and Iordan et al. (2013) provide tantalizing, albeit correlational, evidence that dlPFC acts to protect the contents of working memory from emotional distraction. This converges with work by Peers et al. (2013) and Stollstorff et al. (2013) indicating that dlPFC plays a key role in regulating the focus of attention in the face of potentially distracting emotional cues.

Rolls (2013) extends this perspective to decision-making, arguing that behavior reflects a pervasive, dynamic competition between two kinds of brain systems: (a) emotional systems, including circuits centered on the amygdala and ventral striatum, that have been genetically programmed by our phylogenetic history (e.g., fear elicited by danger, joy elicited by sweets and fat); and (b) cognitive systems, such as the frontoparietal network, that are informed by our ontogenetic history and governed by our declarative knowledge and explicit goals (i.e., pick the healthy orange, not the unhealthy candy bar; cf. Hare et al., 2008, 2009). Rolls emphasizes that the lateral PFC can override the output of emotion circuitry, biasing behavior in favor of our explicit goals. John et al. (2013) articulate a complementary perspective, reviewing evidence that the PFC and amygdala functionally interact via a complex anatomical network of recurrent cortical and thalamic projections and intra-amygdalar microcircuits (see also Pessoa and Adolphs, 2010; Pessoa, 2012; Pessoa et al., 2012; Birn et al., 2014a, b; Treadway et al., 2014).

Evidence linking the dlPFC to mood and anxiety disorders, as in the papers contributed by Crocker et al. (2013) and Warren et al. (2013), underscores the importance of developing a more sophisticated understanding of the role played by 'cognitive' regions in normal and disordered emotion.

Canonical Territories of the 'Cognitive' Brain are Regulated by Emotion

Adaptive and Maladaptive Behavior Reflects the Integrated Contributions of Emotion and Cognitive Control

Oftentimes, cognitive control is associated with laboratory tasks that require the detection and adjudication of response conflict, as with incongruent trials of the Stroop, Eriksen Flanker, and go/no-go tasks. Yet, it is clear that control processes are engaged by a much broader range of cognitive and emotional challenges (e.g., Pochon et al., 2008; Shenhav et al., 2013). In particular, control is engaged when there is uncertainty about the optimal course of action (e.g., probabilistic learning), when potential actions are associated with the possibility of error or punishment, or when there is competition between alternative courses of action (e.g., flee/freeze, go/no-go). These features are hallmarks of dangerous environments, both in the real world and in laboratory studies of fear, anxiety, and pain. Consequently, it has long been thought that control processes are engaged in threatening environments in order to monitor risk, optimize learning, and avoid potentially catastrophic actions ( Norman and Shallice, 1986; Gray and McNaughton, 2000). These theoretical considerations raise the possibility that the neural circuitry underlying 'cognitive' control also contributes to the negative emotions elicited by potential threat. Indeed, there is compelling evidence from functional imaging studies that negative affect and cognitive control paradigms consistently activate an overlapping region of the midcingulate cortex (MCC; Shackman et al., 2011b; Lin et al., 2014). This overlap is consistent with anatomical evidence suggesting that the MCC represents a hub where information about pain, threat, and other more abstract forms of potential punishment and negative feedback are synthesized into a biasing signal that modulates regions involved in expressing fear and anxiety, executing goal-directed behaviors, and biasing the focus of selective attention ( Shackman et al., 2011b; Cavanagh and Shackman, 2014). Taken together, these observations suggest that anxiety and other emotions are tightly integrated with control processes implemented in the MCC and other brain regions.

Dreisbach and Fischer (2012) describe other evidence consistent with this integrative perspective. In particular, they show that 'cognitive' conflict is aversive. This converges with a growing body of evidence demonstrating that conflict and other prompts for increased control (e.g., errors, punishment), are experienced as unpleasant and facilitate avoidance ( Botvinick, 2007; Kool et al., 2010; Dreisbach and Fischer, 2012; Schouppe et al., 2012; Lindström et al., 2013; Proudfit et al., 2013; Shenhav and Buckner, 2014).

McDermott et al. (2013) describe important new evidence, gleaned from the study of Romanian orphans, that MCC control signals are plastic. In particular, they demonstrate that MCC-generated control signals are profoundly shaped by early experience in ways that confer risk or resilience for later socio-emotional problems. This underscores the need to clarify the neurodevelopmental mechanisms that serve to integrate emotion and cognition in the laboratory and in daily life.

Understanding the Interplay of Emotion and Cognition: Strategies for Future Research

Understanding the Significance of Emotional-Cognition Interactions in the Laboratory Requires More Sophisticated Measures of Behavior in the Real World

Given the limitations of ambulatory measures of brain activity-there is no 'fMRI helmet' as yet-addressing these fundamental questions requires pairing assays of brain and behavior obtained in the laboratory with measures of thoughts, feelings, and behavior obtained in the field. Recent work combining fMRI with ecological momentary assessment (EMA) techniques, in which surveys are repeatedly delivered to participants' mobile devices, highlights the value of this approach for identifying the neural systems underlying naturalistic variation in mood and behavior, a central goal of psychology, psychiatry, and the behavioral neurosciences ( Forbes et al., 2009; Berkman and Falk, 2013; Lopez et al., 2014; Wilson et al., 2014). The widespread dissemination of smart phone technology affords additional, largely unrealized opportunities for objectively and unobtrusively quantifying daily behavior (e.g., assessments of activity and context based on accelerometer and geographical positioning system data ( Gosling and Mason, 2015). In short, combining EMA with laboratory assays provides a critical means of testing theoretical validity and clinical relevance (e.g., does activation of the ventral striatum support craving and approach?), a novel strategy for assessing and dissociating the functional significance of new assays and derivative measures (e.g., functional connectivity between the striatum and PFC), and an impetus for the development of laboratory probes that more closely resemble the challenges we routinely encounter in life (e.g., appetitive social cues and temptations).

Understanding the Interplay of Emotion and Cognition Requires a Dynamic Network Perspective

Thus, understanding the interplay of emotion and cognition requires that we accelerate the transition from localization strategies (i.e., mapping isolated brain structures to function; sometimes termed 'neo-phrenology') to a network-centered approach. This will require harnessing the kinds of analytic tools (e.g., functional connectivity fingerprinting, graph-theoretic and machine-learning approaches) that are necessary for elucidating how adaptive and maladaptive behavior emerges from functional coalitions of brain regions ( Kinnison et al., 2012; Raz et al., 2012, 2014; Anticevic et al., 2013; McMenamin et al., 2014; Uddin et al., 2014). A key challenge for future research will be to harness new techniques (e.g., EEG/fMRI fusions, sliding window analyses of functional connectivity, EEG source models of connectivity) for understanding how network activity dynamically changes across the broad range of time scales on which emotion and cognition interact ( Pessoa and Adolphs, 2010; Shackman et al., 2011a; Johnson et al., 2012; Raz et al., 2012, 2014).

Understanding the Interplay of Emotion and Cognition Requires Mechanistic Research

Most of the contributors to the Special Research Topic used non-invasive techniques, such as fMRI, to trace associations between emotion and cognition, on the one hand, and brain function on the other. Aside from unresolved questions about the origins and significance of the measured signals (e.g., Logothetis, 2008), the most important limitation of these techniques is that they do not address causation. A crucial challenge for future studies is to develop a mechanistic understanding of the distributed networks that support the interplay of emotion and cognition. This can be achieved by combining mechanistic techniques (e.g., optogenetics) or invasive analyses of neuromolecular pathways in animal models with the same whole-brain imaging strategies routinely applied in humans ( Borsook et al., 2006; Lerman et al., 2007; Fox et al., 2010, 2012; Lee et al., 2010; Desai et al., 2011; Casey et al., 2013; Narayanan et al., 2013; Roseboom et al., 2014). Similar strategies can be used with patients with circumscribed brain damage (e.g., Nomura et al., 2010; Gratton et al., 2012; Motzkin et al., 2014). Combining fMRI or EEG with non-invasive perturbation techniques (e.g., transcranial magnetic stimulation or transcranial direct current stimulation) or pharmacological manipulations provides another opportunity for understanding how regional changes in brain activity alter network function and, ultimately, behavior ( Paulus et al., 2005; Guller et al., 2012; Chen et al., 2013; Reinhart and Woodman, 2014). Prospective longitudinal designs represent another fruitful approach to identifying candidate mechanisms, especially in relation to the development of neuropsychiatric disorders ( Admon et al., 2013).

Conclusion

The last decade has witnessed an explosion of interest in the interplay of emotion and cognition. The research embodied in this Special Research Topic highlights the tremendous advances that have already been made. In particular, this work demonstrates that emotional cues, emotional states, and emotional traits can strongly influence key elements of on-going information processing, including selective attention, working memory, and cognitive control. Often, this influence persists beyond the duration of transient emotional challenges, perhaps reflecting slower changes in neurochemistry. In turn, circuits involved in attention and working memory contribute to the voluntary regulation of emotion. The distinction between the 'emotional' and the 'cognitive' brain is blurry and context-dependent. Indeed, there is compelling evidence that territories (e.g., dlPFC, MCC) and processes (e.g., working memory, cognitive control) conventionally associated with cognition play a central role in emotion. Furthermore, putatively emotional and cognitive regions dynamically influence one another via a complex web of recurrent, often indirect anatomical connections in ways that jointly contribute to adaptive behavior. Collectively, these observations show that emotion and cognition are deeply interwoven in the fabric of the brain, suggesting that widely held beliefs about the key constituents of 'the emotional brain' and 'the cognitive brain' are fundamentally flawed.

Developing a deeper understanding will require a greater emphasis on (a) assessing the real-world relevance of laboratory assays, including measures of brain activity; (b) a network approach to characterizing the neurobiology of emotion-cognition interactions, and (c) mechanistic research. Adopting these strategies mandates collaboration among researchers from different disciplines, with expertise in different species, populations, measurement tools, analytic strategies, and conceptual approaches.

Addressing the interplay of emotion and cognition is a matter of theoretical as well as practical importance. In particular, many of the most common and costly neuropsychiatric disorders-anxiety, depression, schizophrenia, substance abuse, chronic pain, autism, and so on-involve prominent disturbances of cognition and emotion ( Millan, 2013). Fundamentally, they are disorders of the emotional-cognitive brain. Collectively, these disorders far outstrip the global burden of cancer or cardiovascular disease ( Collins et al., 2011; Whiteford et al., 2013; DiLuca and Olesen, 2014), underscoring the importance of accelerating efforts to understand the neural systems underlying the interaction and integration of emotion and cognition.

Glossary of Terms Not Defined in the Main Text

Affect: The experience or expression of emotion (see also Barrett et al., 2007).

Anxiety: A sustained state of heightened apprehension in response to uncertain, distal, or diffuse threat ( Davis et al., 2010).

Cognition: Cognition is a fuzzy category that conventionally includes processes involved in knowing or 'thinking,' including attention, imagination, language, learning, memory, and perception (for discussion, see Duncan and Barrett, 2007).

Emotion: Like 'cognition,' 'emotion' is a fuzzy, contentious category that conventionally includes valenced processes (e.g., action tendencies, attention, overt behavior, subjective feelings, and alterations in peripheral physiology) that are triggered by specific external or internal stimuli (e.g., actual or remembered threat for fear); often taken to include states of anger, disgust, fear, happiness, and sadness (e.g., Ekman and Davidson, 1994; Duncan and Barrett, 2007; Gendron and Barrett, 2009; LeDoux, 2012, 2014).

Mood: A low-intensity emotional state that persists in the absence of an explicit triggering stimulus ( Ekman and Davidson, 1994).

Motivation: Internal states that are elicited by reinforcers and serve to organize behavioral direction (i.e., approach or avoidance) and intensity. Emotional states involve alterations in motivation (e.g., increased avoidance in the case of fear). However, motivation can be altered by homeostatic processes, such as hunger and satiety, that are not conventionally considered emotional ( Rolls, 1999).

Neuroticism/Negative Emotionality: A fundamental dimension of childhood temperament and adult personality; individuals with high levels of Neuroticism/Negative Emotionality are susceptible to more intense or long-lasting negative emotions, including anger, anxiety, fear, guilt, and sadness ( Watson and Clark, 1984; Caspi et al., 2005).

Reinforcer: Rewards and punishments; anything an organism will work to approach or avoid ( Rolls, 1999).

Author Contributions

All the authors supervised the Special Research Topic. Hadas Okon-Singer and Alexander J. Shackman wrote the paper. All the authors edited and revised the paper.

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 thank the many contributors and staff who made the Special Research Topic possible. We acknowledge the assistance of L. Friedman and support of the European Commission (Followship #334206 to Hadas Okon-Singer and Grant #602186 to Talma Hendler), Israeli Center of Research Excellence, Israeli Science Foundation (Grant #51/11 to Talma Hendler), National Institute of Mental Health (MH071589 to Luiz Pessoa), and University of Maryland (Alexander J. Shackman and Luiz Pessoa).

References

Coan, J. A., and Allen, J. J. B. (2007). Handbook of Emotion Elicitation and Assessment. New York: Oxford University Press.

Lewis-Peacock, J. A., and Norman, K. A. (2013). Multi-voxel pattern analysis of fMRI data: a review. Comput. Math. Methods Med. 2012, 1-14.

Oler, J. A., Fox, A. S., Shackman, A. J., and Kalin, N. H. (in press). "The central nucleus of the amygdala is a critical substrate for individual differences in anxiety," in Living Without an Amygdala, eds D. G. Amaral, M. Bauman, and R. Adolphs (New York, NY: Guilford Press).

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The neurobiology of emotion–cognition interactions: fundamental questions and strategies for future research

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Recent years have witnessed the emergence of powerful new tools for assaying the brain and a remarkable acceleration of research focused on the interplay of emotion and cognition. This work has begun to yield new insights into fundamental questions about the nature of the mind and important clues ab…

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Cite this guide: Chick, N. (2013). Metacognition. Vanderbilt University Center for Teaching. Retrieved [todaysdate] from https://cft.vanderbilt.edu/guides-sub-pages/metacognition/.

Thinking about One's Thinking | Putting Metacognition into Practice

Thinking about One's Thinking

Metacognition is, put simply, thinking about one's thinking. More precisely, it refers to the processes used to plan, monitor, and assess one's understanding and performance. Metacognition includes a critical awareness of a) one's thinking and learning and b) oneself as a thinker and learner.

Initially studied for its development in young children (Baker & Brown, 1984; Flavell, 1985), researchers soon began to look at how experts display metacognitive thinking and how, then, these thought processes can be taught to novices to improve their learning (Hatano & Inagaki, 1986). In How People Learn, the National Academy of Sciences' synthesis of decades of research on the science of learning, one of the three key findings of this work is the effectiveness of a "'metacognitive' approach to instruction" (Bransford, Brown, & Cocking, 2000, p. 18).

Metacognitive practices increase students' abilities to transfer or adapt their learning to new contexts and tasks (Bransford, Brown, & Cocking, p. 12; Palincsar & Brown, 1984; Scardamalia et al., 1984; Schoenfeld, 1983, 1985, 1991). They do this by gaining a level of awareness above the subject matter: they also think about the tasks and contexts of different learning situations and themselves as learners in these different contexts. When Pintrich (2002) asserts that "Students who know about the different kinds of strategies for learning, thinking, and problem solving will be more likely to use them" (p. 222), notice the students must "know about" these strategies, not just practice them. As Zohar and David (2009) explain, there must be a " conscious meta-strategic level of H[igher] O[rder] T[hinking]" (p. 179).

Metacognitive practices help students become aware of their strengths and weaknesses as learners, writers, readers, test-takers, group members, etc. A key element is recognizing the limit of one's knowledge or ability and then figuring out how to expand that knowledge or extend the ability. Those who know their strengths and weaknesses in these areas will be more likely to "actively monitor their learning strategies and resources and assess their readiness for particular tasks and performances" (Bransford, Brown, & Cocking, p. 67).

The absence of metacognition connects to the research by Dunning, Johnson, Ehrlinger, and Kruger on "Why People Fail to Recognize Their Own Incompetence" (2003). They found that "people tend to be blissfully unaware of their incompetence," lacking "insight about deficiencies in their intellectual and social skills." They identified this pattern across domains-from test-taking, writing grammatically, thinking logically, to recognizing humor, to hunters' knowledge about firearms and medical lab technicians' knowledge of medical terminology and problem-solving skills (p. 83-84). In short, "if people lack the skills to produce correct answers, they are also cursed with an inability to know when their answers, or anyone else's, are right or wrong" (p. 85). This research suggests that increased metacognitive abilities-to learn specific (and correct) skills, how to recognize them, and how to practice them-is needed in many contexts.

Putting Metacognition into Practice

In " Promoting Student Metacognition," Tanner (2012) offers a handful of specific activities for biology classes, but they can be adapted to any discipline. She first describes four assignments for explicit instruction (p. 116):

Preassessments-Encouraging Students to Examine Their Current Thinking: "What do I already know about this topic that could guide my learning?"

The Muddiest Point-Giving Students Practice in Identifying Confusions: "What was most confusing to me about the material explored in class today?"

Retrospective Postassessments-Pushing Students to Recognize Conceptual Change: "Before this course, I thought evolution was... Now I think that evolution is ...." or "How is my thinking changing (or not changing) over time?"

Reflective Journals-Providing a Forum in Which Students Monitor Their Own Thinking: "What about my exam preparation worked well that I should remember to do next time? What did not work so well that I should not do next time or that I should change?"

Next are recommendations for developing a "classroom culture grounded in metacognition" (p. 116-118):

Giving Students License to Identify Confusions within the Classroom Culture: ask students what they find confusing, acknowledge the difficulties

Integrating Reflection into Credited Course Work: integrate short reflection (oral or written) that ask students what they found challenging or what questions arose during an assignment/exam/project

Metacognitive Modeling by the Instructor for Students: model the thinking processes involved in your field and sought in your course by being explicit about "how you start, how you decide what to do first and then next, how you check your work, how you know when you are done" (p. 118)

To facilitate these activities, she also offers three useful tables:

Questions for students to ask themselves as they plan, monitor, and evaluate their thinking within four learning contexts-in class, assignments, quizzes/exams, and the course as a whole (p. 115)

Prompts for integrating metacognition into discussions of pairs during clicker activities, assignments, and quiz or exam preparation (p. 117)

Questions to help faculty metacognitively assess their own teaching (p. 119)

Weimer's " Deep Learning vs. Surface Learning: Getting Students to Understand the Difference " (2012) offers additional recommendations for developing students' metacognitive awareness and improvement of their study skills:

"[I]t is terribly important that in explicit and concerted ways we make students aware of themselves as learners. We must regularly ask, not only 'What are you learning?' but 'How are you learning?' We must confront them with the effectiveness (more often ineffectiveness) of their approaches. We must offer alternatives and then challenge students to test the efficacy of those approaches." (emphasis added)

She points to a tool developed by Stanger-Hall (2012, p. 297) for her students to identify their study strategies, which she divided into " cognitively passive" ("I previewed the reading before class," "I came to class," "I read the assigned text," "I highlighted the text," et al) and " cognitively active study behaviors" ("I asked myself: 'How does it work?' and 'Why does it work this way?'" "I wrote my own study questions," "I fit all the facts into a bigger picture," "I closed my notes and tested how much I remembered," et al). The specific focus of Stanger-Hall's study is tangential to this discussion, ¹ but imagine giving students lists like hers adapted to your course and then, after a major assignment, having students discuss which ones worked and which types of behaviors led to higher grades. Even further, follow Lovett's advice (2013) by assigning "exam wrappers," which include students reflecting on their previous exam-preparation strategies, assessing those strategies and then looking ahead to the next exam, and writing an action plan for a revised approach to studying. A common assignment in English composition courses is the self-assessment essay in which students apply course criteria to articulate their strengths and weaknesses within single papers or over the course of the semester. These activities can be adapted to assignments other than exams or essays, such as projects, speeches, discussions, and the like.

As these examples illustrate, for students to become more metacognitive, they must be taught the concept and its language explicitly (Pintrich, 2002; Tanner, 2012), though not in a content-delivery model (simply a reading or a lecture) and not in one lesson. Instead, the explicit instruction should be "designed according to a knowledge construction approach," or students need to recognize, assess, and connect new skills to old ones, "and it needs to take place over an extended period of time" (Zohar & David, p. 187). This kind of explicit instruction will help students expand or replace existing learning strategies with new and more effective ones, give students a way to talk about learning and thinking, compare strategies with their classmates' and make more informed choices, and render learning "less opaque to students, rather than being something that happens mysteriously or that some students 'get' and learn and others struggle and don't learn" (Pintrich, 2002, p. 223).

Metacognition instruction should also be embedded with the content and activities about which students are thinking. Why? Metacognition is "not generic" (Bransford, Brown, & Cocking, p. 19) but instead is most effective when it is adapted to reflect the specific learning contexts of a specific topic, course, or discipline (Zohar & David, 2009). In explicitly connecting a learning context to its relevant processes, learners will be more able to adapt strategies to new contexts, rather than assume that learning is the same everywhere and every time. For instance, students' abilities to read disciplinary texts in discipline-appropriate ways would also benefit from metacognitive practice. A literature professor may read a passage of a novel aloud in class, while also talking about what she's thinking as she reads: how she makes sense of specific words and phrases, what connections she makes, how she approaches difficult passages, etc. This kind of modeling is a good practice in metacognition instruction, as suggested by Tanner above. Concepción's " Reading Philosophy with Background Knowledge and Metacognition " (2004) includes his detailed "How to Read Philosophy" handout (pp. 358-367), which includes the following components:

What to Expect (when reading philosophy)

The Ultimate Goal (of reading philosophy)

Basic Good Reading Behaviors

Important Background Information, or discipline- and course-specific reading practices, such as "reading for enlightenment" rather than information, and "problem-based classes" rather than historical or figure-based classes

A Three-Part Reading Process (pre-reading, understanding, and evaluating)

Flagging, or annotating the reading

Linear vs. Dialogical Writing (Philosophical writing is rarely straightforward but instead "a monologue that contains a dialogue" [p. 365].)

What would such a handout look like for your discipline?

Students can even be metacognitively prepared (and then prepare themselves) for the overarching learning experiences expected in specific contexts. Salvatori and Donahue's The Elements (and Pleasures) of Difficulty (2004) encourages students to embrace difficult texts (and tasks) as part of deep learning, rather than an obstacle. Their "difficulty paper" assignment helps students reflect on and articulate the nature of the difficulty and work through their responses to it (p. 9). Similarly, in courses with sensitive subject matter, a different kind of learning occurs, one that involves complex emotional responses. In " Learning from Their Own Learning: How Metacognitive and Meta-affective Reflections Enhance Learning in Race-Related Courses" (Chick, Karis, & Kernahan, 2009), students were informed about the common reactions to learning about racial inequality (Helms, 1995; Adams, Bell, & Griffin, 1997; see student handout, Chick, Karis, & Kernahan, p. 23-24) and then regularly wrote about their cognitive and affective responses to specific racialized situations. The students with the most developed metacognitive and meta-affective practices at the end of the semester were able to "clear the obstacles and move away from" oversimplified thinking about race and racism "to places of greater questioning, acknowledging the complexities of identity, and redefining the world in racial terms" (p. 14).

Ultimately, metacognition requires students to "externalize mental events" (Bransford, Brown, & Cocking, p. 67), such as what it means to learn, awareness of one's strengths and weaknesses with specific skills or in a given learning context, plan what's required to accomplish a specific learning goal or activity, identifying and correcting errors, and preparing ahead for learning processes.

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1 Students who were tested with short answer in addition to multiple-choice questions on their exams reported more cognitively active behaviors than those tested with just multiple-choice questions, and these active behaviors led to improved performance on the final exam.
References

Adams, Maurianne, Bell, Lee Ann, and Griffin, Pat. (1997). Teaching for diversity and social justice: A sourcebook. New York: Routledge.

Bransford, John D., Brown Ann L., and Cocking Rodney R. (2000). How people learn: Brain, mind, experience, and school. Washington, D.C.: National Academy Press.

Baker, Linda, and Brown, Ann L. (1984). Metacognitive skills and reading. In Paul David Pearson, Michael L. Kamil, Rebecca Barr, & Peter Mosenthal (Eds.), Handbook of research in reading: Volume III (pp. 353-395). New York: Longman.

Brown, Ann L. (1980). Metacognitive development and reading. In Rand J. Spiro, Bertram C. Bruce, and William F. Brewer, (Eds.), Theoretical issues in reading comprehension: Perspectives from cognitive psychology, linguistics, artificial intelligence, and education (pp. 453-482). Hillsdale, NJ: Erlbaum.

Chick, Nancy, Karis, Terri, and Kernahan, Cyndi. (2009). Learning from their own learning: how metacognitive and meta-affective reflections enhance learning in race-related courses . International Journal for the Scholarship of Teaching and Learning, 3(1). 1-28.

Flavell, John H. (1985). Cognitive development. Englewood Cliffs, NJ: Prentice Hall.

Hatano, Giyoo and Inagaki, Kayoko. (1986). Two courses of expertise. In Harold Stevenson, Azuma, Horishi, and Hakuta, Kinji (Eds.), Child development and education in Japan, New York: W.H. Freeman.

Lovett, Marsha C. (2013). Make exams worth more than the grade. In Matthew Kaplan, Naomi Silver, Danielle LaVague-Manty, and Deborah Meizlish (Eds.), Using reflection and metacognition to improve student learning: Across the disciplines, across the academy. Sterling, VA: Stylus.

Salvatori, Mariolina Rizzi, and Donahue, Patricia. (2004). The Elements (and pleasures) of difficulty. New York: Pearson-Longman.

Schoenfeld, Alan H. (1991). On mathematics as sense making: An informal attack on the fortunate divorce of formal and informal mathematics. In James F. Voss, David N. Perkins, and Judith W. Segal (Eds.), Informal reasoning and education (pp. 311-344). Hillsdale, NJ: Erlbaum.

Weimer, Maryellen. (2012, November 19). Deep learning vs. surface learning: Getting students to understand the difference. Retrieved from the Teaching Professor Blog from http://www.facultyfocus.com/articles/teaching-professor-blog/deep-learning-vs-surface-learning-getting-students-to-understand-the-difference/.

This teaching guide is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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by Nancy Chick Print Version Cite this guide: Chick, N. (2013). Metacognition. Vanderbilt University Center for Teaching. Retrieved [todaysdate] from https://cft.vanderbilt.edu/guides-sub-pages/metacognition/. Thinking about One's Thinking | Putting Metacognition into Practice Thinking about One's Thinking Metacognition is, put simply, thinking about one's thinking. More precisely, it refers to the processes used to plan, monitor, and assess...

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

Designing activities with the goal of transferring knowledge

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

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

Define practice:

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

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

Benefits of deliberate practice

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

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

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

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

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

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

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

General recommendations for practice and instruction

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

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

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

Designing activities that maximize opportunities for students to succeed.

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

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

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

What type of feedback is most effective?

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

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

Do's:

1. Vary practice activities.

2. Distribute practice over extended periods of time.

3. Provide clear instructions on performance expectations and criteria.

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

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

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

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

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

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

Don'ts:

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

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

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

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

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

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

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

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

Short-term or working memory

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

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

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

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

Long-term memory

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

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

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

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

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

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

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

Example of chunking information

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

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

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

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

Theories explaining expert performance

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

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

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

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

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

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

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

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

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

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

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

Is homework always effective practice?

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

How much time should be spent on homework?

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

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

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

Does practice with "authentic" problems increase learning?

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

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

Is there such a thing as too much practice?

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

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

Does practice work for all academic subjects?

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

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

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

When does the strategy work?

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

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

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

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

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

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

Model problem-solving processes.

Design partially-completed examples on which students can practice.

Sequence activities logically.

Space practice activities appropriately.

Monitor student practice providing guidance and feedback.

Is practice effective across the age span?

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

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

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

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

Elementary

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

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

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

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

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

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

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

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

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

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

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

Middle School

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

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

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

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

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

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

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

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

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

High School

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

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

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

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

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

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

Where can teachers get more information?

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

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

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

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Practice for knowledge acquisition (not drill and kill)

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Researchers who have investigated expert and novice performance have uncovered important distinctions between deliberate practice and other activities, such as work, play and rote repetition.

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Neuroscience and Creativity | Siddharth Warrier | TEDxGLAU | Siddharth Warrier | TEDxGLAU

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How to practice effectively...for just about anything - Annie Bosler and Don Greene

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Frisbee coach Martin Levy is a big fan of the clicker. He uses it to train his border collies to perform complex jumps and twirls on the Frisbee field. In 2012, after successfully using a clicker to teach his other Frisbee students - the human ones - he decided to up the stakes, and test it out at his day job: as an orthopedic surgeon.

At the Bronx Montefiore Medical Center in New York, Dr. Martin Levy uses clicker training - a technique drawn from the world of animal training, modified for humans--to help new surgeons quickly learn their craft. It's one of the many tricks he uses to teach his inexperienced medical residents how to tie knots, drill holes and twist screws into broken bones and ligaments, among other techniques. Dr. Levy breaks the skills down into tiny, incremental steps. Each step, performed correctly, is marked with his clicker.

Click.

The only feedback is the sound of the click.

Click.

The only reward for the student is the mastery of the skill.

Click.

All the usual interference from the teacher - "great job," "well done," "no, wrong" - is removed. "This is why I use the clicker," says Dr. Levy. "It is baggage free, it is emotional free."

This week on Hidden Brain, we explore an innovative idea about how we learn. It will take us from the Russian laboratory of Ivan Pavlov, to a dolphin exhibit in Hawaii to a top teaching hospital in New York. It's about a method to quiet the noise. The sort of clutter that can turn learning into a minefield of misery.
More Resources:
Our show includes the story of Karen Pryor, one of the founders of clicker training. Dr. Levy's teaching techniques build on Pryor's influential work with dolphins, whales and dogs.

Read the 2016 study Dr. Levy co-authored with Pryor, which finds that surgical students taught with a clicker are more precise than students taught by demonstration.

Learn more about B.F. Skinner, a pioneer in the field of behaviorism.
This episode was produced by Jenny Schmidt and Thomas Lu and edited by Tara Boyle. Hidden Brain is hosted by Shankar Vedantam and includes Parth Shah, Rhaina Cohen, and Laura Kwerel. You can also follow us on Twitter @hiddenbrain, and listen for Hidden Brain stories on your local public radio station.

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When Everything Clicks: The Power Of Judgment-Free Learning

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There can be a lot of psychological noise involved in learning. And mental chit chat can make learning hard. One solution, silence it with a click.

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Retrieval Practice: A Powerful Strategy to Improve Learning

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Retrieval Practice: A Powerful Strategy to Improve Learning

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Harness powerful teaching strategies, unleash the science of learning, and transform your classroom with resources by cognitive scientists.

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How well do students learn when a lesson is mainly in PowerPoint? Henrik Berger Jørgensen, CC BY-NC-ND

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

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

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

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

Surprisingly, the answer is no.

Passive learning through PowerPoint?

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

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

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

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

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

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

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

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

What's wrong with slideshows in online courses

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

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

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

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

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

Using slideshows the right way

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

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

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

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

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

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

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

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

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

What this means in the larger context of online learning

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

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

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

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

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

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

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

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Learning from PowerPoint: is it time for teachers to move on?

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Slideshows, when designed right, can be a useful part of online instruction. But they shouldn't be the main, or the only, method of instruction.

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Faculty Focus | Higher Ed Teaching & Learning

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I was wrapping up a presentation on memory and learning when a colleague asked, "How do we help students learn in courses where there's a lot of memorization?" He explained that he taught introductory-level human anatomy, and although the course wasn't all memorization, it did challenge students' capacity to retain dozens of new terms and concepts.

The question itself is tricky because most teaching professionals are heavily invested in the idea that learning isn't about being able to regurgitate facts on an exam. We also worry, and with good reason, that emphasizing rote learning steals time and effort away from the deeper thinking that we want students to do. But in my work I've come to realize that memorization deserves some airtime because it is one important route to building content knowledge and expertise. Furthermore, acquiring content knowledge doesn't have to detract from critical thinking, reasoning, or innovation-rather, it can complement all these. Cognitive scientists are making new discoveries all the time about the connections between memory and processes such as drawing inferences, making predictions, and other skills that make up the ability to think like an expert in a discipline.

So what techniques target this specific teaching and learning challenge? We're all familiar with mnemonics such as the first-letter technique-using a word such as RICE (rest, ice, compression, elevation) or a catchy phrase (Every Good Boy Does Fine) to remember a sequence of information. Mnemonics are one good tool, but what else can we offer?

Learning isn't about being able to regurgitate facts on an exam, but memorization deserves some airtime because it is one important route to building content knowledge and expertise

For starters, we should convey to students (and keep in mind ourselves) that memorization challenges nearly everyone because the mind simply isn't set up to take in reams of disjointed facts. Our memory systems evolved to be picky about what we remember, selecting the information that is most relevant to our goals and discarding the rest. Understanding this helps us and our students have realistic expectations about the level of effort needed to succeed.

It also helps to understand how we create memories for words, because many memorization tasks involve scientific terms, foreign language vocabulary, and the like. How we do this has been hotly debated among researchers, but one view is that we rely on a special piece of mental machinery called the phonological loop that holds speech sounds.

If you've ever muttered a phone number to yourself while you ran around looking for a pencil to write it down with, you've experienced the phonological loop in action. But recycling phone numbers isn't the phonological loop's main reason for existing. Rather, its real job kicks in when we run into a word we haven't heard before. When this happens, the phonological loop grabs onto the sequence of sounds and keeps it fresh while other memory systems set up representations of what the new word means. The catch is that phonological loop capacity varies fairly substantially from individual to individual. This means that words of three, four, or more syllables overwhelm some people's ability to learn new words on the fly.

With these two points in mind-that memory doesn't handle disjointed facts well and new vocabulary hinges on one sometimes-shaky mechanism within memory-here are some ways to help students manage memorization:

Emphasize context and purpose. Ask yourself why students are being asked to memorize these facts in the first place. If students can readily answer that question and if they can picture future situations in which they will use the information, they will be better primed to remember it.

Break down new vocabulary words, especially those that are more than two syllables long. Allow time to rehearse and remember the first couple of syllables before tacking on later ones. Also keep in mind that this process will be easier for some students than others due to wide variation in phonological loop capacity; you may want to design in a "mastery learning" or other individualized approach for vocabulary so that students can move through at their own pace.

Visualize information. For most people, imagery is highly memorable, perhaps because so much of the brain is devoted to visual processing. Memory champions, such as the ones populating the best seller Moonwalking with Einstein, use elaborate visualization strategies to achieve incredible feats of memorization. Similarly, strategies such as the keyword mnemonic work by linking word sounds to images (such as using an image of a cowboy on a horse to remember the Spanish word "caballo," which sounds a bit like "cowboy").

Take advantage of the "Big Three" applied memory principles-testing, spacing, and interleaving. Briefly, these refer to the facts that quizzes are a great way to study and that we do best when we spread out our study sessions and alternate between different topics. Tackling a big memory project such as human anatomy means we need every advantage we can get, and dozens of research studies have supported these three as producing the biggest memory payoff for the time invested.

Avoid the rereading trap. Students tend to fall into passively reviewing material, and in doing so they miss the key advantage of techniques such as testing: retrieval practice. Retrieval practice strengthens memory, but it works only when we actively challenge memory. Flash cards, a favorite student strategy, are fine as long as students use them to actively quiz themselves.

It's okay to expect students to learn the facts and terms needed to become experts in a discipline. With an understanding of memory and some strategies to share, we can make this side of learning productive and maybe even painless-but certainly at least less painful.
Michelle Miller is a professor in the Department of Psychological Sciences at Northern Arizona University.
Reprinted from The Teaching Professor, 28.9 (2014): 3. © Magna Publications. All rights reserved.

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Helping Students Memorize: Tips from Cognitive Science

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Although there is more to learning than regurgitating facts on an exam, memorization is an important route to building content knowledge and expertise.

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Problem Library | Institute for Transforming University Education

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The problem evokes an exploration of texts, which requires students to explore and discuss the texts within a collaborative framework in an effort to uncover how they are a product of setting and society at a certain point in history yet represent elements which make them valuable in contemporary times.

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Welcome!

ITUE is a faculty-led group dedicated to improving the quality of teaching and learning. Along with our Faculty Commons partners, we are a resource for faculty at UD (and beyond) to help navigate the scholarship on teaching and learning, with a particular focus on Problem-based learning and related pedagogies.

If you have any questions or if you would like to discuss anything related to ITUE, please feel free to get in touch with Phil Duker ( pduker@udel.edu).

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Institute for Transforming University Education

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ITUE is a faculty-led group dedicated to improving the quality of teaching and learning. Along with our Faculty Commons partners, we are a resource for faculty at UD (and beyond) to help navigate the scholarship on teaching and learning, with a particular focus on Problem-based learning and related pedagogies.

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

Go to the first test.

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

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Learning and memory under stress: implications for the classroom - npj Science of Learning

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npj Science of Learning - Learning and memory under stress: implications for the classroom

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Making correct predictions is one of the strongest dopamine elevators. Concomitant effects include enhanced attentive focus, motivation, curiosity, memory, persistence, and perseverance. *case for frequent low-stakes assessments and activities* To further optimize students' success in school, you can engage the dopamine-reward response to motivate the brain to put forth the mental effort needed for new learning.

By showing students that they have the power to improve and by providing opportunities for them to see progress toward goals, they'll come to understand that their own effort may control the outcome. *case for allowing to re-do any work with a low grade*

Neuroplasticity refers to the brain's continuous capacity to generate new neural networks in response to stimuli.

The expression "neurons that fire together, wire together" refers to the process by which the brain constructs neural networks. The neuroplastic response includes the building of more neuronal connections as well as the thickening of the myelin around existing connections. The additional layers of myelin around the axons increases the speed of information travel and protects the circuit from being easily eroded through disuse.

Activating students' existing relevant prior knowledge takes place when they understand a framework into which the new learning belongs. This awareness guides the brain to recognize connections with existing memory networks in the hippocampus. To ensure that there is related existing memory in the hippocampus to link with the new input, it is essential to help students become aware of their prior knowledge. Strategies to ensure activation of prior knowledge include the use of pre-assessments, advance organizers, essential questions, concept maps, graphic organizers, and "hook" activities.

Once encoded, short-term memory requires mental manipulation of the new information—it must be thought about or applied—to form richer and deeper connections and ensure its place in long-term memory storage.

What can we do to motivate sustained effort from a stingy brain and improve the mindset of students, especially those who have experienced failure and the erosion of their confidence in school? To answer this question, consider an activity that is popular among many young people and that leads them, despite repeated failures, to persevere—video games!

We have identified four elements of this model that educators can replicate to enhance the learning of their students: (1) establishing a desirable goal, (2) offering an achievable challenge, (3) providing constant assessment with specific feedback, and (4) acknowledging progress and achievement en route to a final goal.

*teaching their peers, teaching someone who doesn't know anything about the topic. In teaching their peers at the beginning of class...ok if didn't prepare/read ahead of time, can pair up with someone else who didn't prepare and teach last weeks material, or with me and teach me anything they remember. Scaffolding a larger assignment. Feedback as incremental pieces of information to adjust project, rather than as criticism or a deduction of grade.

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

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

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

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Upgrade Your Teaching: Understanding by Design Meets Neuroscience

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

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Interactive Brain | How the brain works & the impact of injury

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Take an interactive journey to see how the brain works and what impact an injury can have

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Recognizing that our brains are goal-driven is important for educators, because if we don’t make learning goals explicit to our learners, they have no way of knowing what the target is, how to reach it, or when they’ve achieved it.

The more explicit we are with our learners about the goals and incorporate their own goals, the more meaningful the learning experience will be, the more purposeful the options available will be, and the less likely our brains will focus on competing goals.

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

Coming soon! UDL Guidelines 3.0

The UDL Guidelines are a living, dynamic tool that is continuously developed based on new research and feedback from practitioners. In 2020, CAST launched our most recent effort to update the UDL Guidelines, with a specific focus on equity. There has been a strong call from the field-both practitioners and researchers alike-to more fully develop the Guidelines to address critical barriers rooted in biases and systems of oppression. The current update aims to respond to this call and to work toward fulfilling the promise of the Guidelines as a tool to guide the design of learning environments that more fully honor and value every learner.

Since our launch in 2020, we have been committed to a community-driven, inclusive, and transparent updating process. As part of this effort, we are:

Collaborating with an Advisory Board, a UDL Guidelines Collaborative, and a Young Adult Advisory Board to guide our work

Conducting focus groups with a diversity of participants to learn from their perspectives, lived experiences, and feedback

Reviewing the research on the UDL Guidelines research pages to understand the balance of different research fields, methodological approaches, epistemological approaches, and author positionalities

Conducting literature reviews of equity-oriented research that connect to and extend the Guidelines, such as disability studies and critical pedagogy studies

We are excited to share this next iteration of the UDL Guidelines in 2024. If you are interested in receiving our UDL Guidelines 3.0 newsletter to stay updated on our progress and to share your ideas and perspectives, please complete this brief form.

Review the Summary

Explore the Full Draft

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The UDL Guidelines are a tool used in the implementation of Universal Design for Learning, a framework to improve and optimize teaching and learning for all people based on scientific insights into how humans learn. Learn more about the Universal Design for Learning framework from CAST.

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The human brain is one of the most incredible and intricate parts of the human body. In fact, it's capable of creating more ideas than there are atoms of the universe.

Did you know that the brain changes constantly through a process called neuroplasticity?

But, what is neuroplasticity?

Through neuroplasticity, the brain is consistently rewiring itself and modifying its connections. It can reorganize itself both in structure and how it functions.

Without neuroplasticity, we wouldn't be able to do many of the things that make us human. This includes learning, developing, and forming memories.

So if the brain is malleable, can we rewire it?

Can we "rewrite" patterns in our brain to improve well-being?

Here's everything you need to know about how neuroplasticity works. Plus, we'll show you how you can improve your brain's plasticity.

What is neuroplasticity?

Let's start with a plasticity definition.

Neuroplasticity is also known as neural plasticity or brain plasticity. It's the brain's ability to reorganize and restructure itself on a cellular level.

This reorganization allows our brains to adapt to changes. These changes could come from:

New experiences

Environmental changes

Brain damage

Environmental pressure

Physiological changes

New experiences

How does neuroplasticity work?

The human brain consists of vast networks of neurons. These are the single individual working units of its structure.

Even the simplest of tasks require millions of interconnected neurons. These neurons function as connectivity networks to accomplish the action at hand.

The neural network is a unique and specific pattern of neural connections. They fire in equally specific sequences to allow you to accomplish different tasks.

From raising your hand to playing "Chopsticks" on the piano, they are always working. The ability of the brain to adapt is based on the alteration of existing neural networks. And the generation of new ones.

Psychologists have found that there are two primary types of neuroplasticity:

Functional neuroplasticity.This refers to the permanent structural changes in neural synapses. It's brought on by development and learning.

Structural neuroplasticity.This refers to the strength of the connections between neurons and changes to this strength.

Synapses between neurons alter through a process called synaptic pruning. This occurs mostly between early childhood and your mid-20s.

In this phase of nervous system development, synapses are removed.

5 benefits of brain plasticity

Neuroplasticity is beneficial to our cognition in every way.

It shapes our views of the world and how the brain works. It also impacts our:

Memories

Learning abilities

Subconscious beliefs

These are the five significant benefits of improving your brain plasticity.

1. Helps you learn new things

Every time you learn a new skill, you have your neurons to thank for it.

Activity-dependent neural plasticity is a form of functional and structural plasticity. It comes about due to the use of cognitive function and our personal experiences.

Essentially, it's the biological mechanism for learning and creating new memories.

2. Helps with depression

Neuroplasticity deficits are a possible contributor to conditions like anxietyand depression.

Studies show that the brains of people with depression indicate problems with plasticity. Plus, many antidepressants are believed to work because they promote neuroplasticity.

Experts suggest that certain lifestyle changes could cause neuroplasticity enhancement. In turn, this could potentially improve the symptoms of depression. These changes include:

3. Helps you engage in activities more thoughtfully

Mental exercises help create new connections between neurons and generate new brain cells. This develops plasticity.

It builds a functional reserve to guard against future brain cell loss. It also enables you to engage in activities more thoughtfully and consciously.

All mentally stimulating activities can help boost your brainpower and improve focus. This includes everything from Sudoku puzzles and reading to mindful breathing and math problems.

You can engage in activities that require manual dexterity. This includes activities like:

4. Aids recovery from strokes and other traumatic brain injuries

After suffering a traumatic brain injury, neuroplasticity can help you regain brain function.

A neuroscience study found that task-specific activities promoted stroke patients' recovery. It encouraged increased neurogenesis and neural plasticity.

5. Increases brain volume and memory

Improving your neuronal plasticity also boosts neurogenesis. This is the formation of new cells in your brain. This can boost your brain's volume considerably.

A high rate of neural plasticity strengthens the connections between these new neurons. This can further enhance your memory and learning abilities.

Key characteristics of brain plasticity

It was once thought that as we age, our brains' neural networks become fixed and rigid. But recent research shows that our brains never stop adjusting and changing.

Younger people are generally more sensitive to changes in their plasticity. But even seniors can learn new things and boost the plasticity of their brains as well.

If you play an instrument often, you're likely to become better at playing that instrument. This is due to your constant use of those neural networks.

Likewise, if you were to stop playing your instrument for a while, and you take it up again in a few months, you might find your playing rusty.

Although neuroplasticity is a promising scientific field, it does have its limitations. Brain plasticity cannot fix everything. Unfortunately, it cannot fix brain damage in severe cases.

For example, most of the evidence of neuroplasticity is around the cerebral cortex. When this area is damaged, other areas of the brain can often compensate for the loss.

However, the cortex cannot replicate the functions of more complex brain regions like the hippocampus.

Neuroplasticity is an ongoing process. It's hindered or promoted by factors like:

Practices such as neuroplasticity training can promote ongoing brain plasticity. They increase your brain's formation of strong synapses between neurons.

Neuroplasticity and psychology

People who undergo therapy need to learn vital new coping skills to handle life's challenges. As they do, they build new neural connections that promote lasting emotional regulation and resilience.

As you learn new habits, your synapses will replace the neural pathways that prompted unhealthy behaviors.

Once these synapses are removed, your counseling will rewire your brain. New coping mechanisms that you need to practice to turn into a habit will emerge.

Conditions such as depression and chronic stress have been associated with suppressed neurogenesis. Psychiatry experts believe that promoting this process could reduce their symptoms. It could even prevent the conditions in some cases.

Certain psychiatric medications can also improve neuroplasticity.

The reasons behind the efficacy of antidepressants were long thought to be a mystery. But today, neuroscientists know that they are at least in part based on brain plasticity.

SSRI and SNRI antidepressants often boost neuroplasticity. They may even reverse some of the negative effects inflicted on the brain during a depressive episode.

Often, boosting neuroplasticity can form part of a mental health treatment regime. Brains in the first stages of dementia use neuroplasticity to compensate for rapid cognitive declines.

Does neuroplasticity change with age?

As kids, our brains are more capable of change. Children are constantly learning and experiencing new things. This creates extraordinary changes in their brain's structure.

At birth, a baby's brain has 100 billion neurons. As the neurons mature, more synapses are made. When we're born, there are 2,500 synapses per neuron. But by age two or three, it's about 15,000 per neuron.

That's more than double the number of synapses of the average adult brain.

This explosion of synapse formation is called synaptogenesis. It plays a crucial part in early brain development.

Neuroplasticity continues to happen throughout our lifetime. But different types of plasticity are more prevalent during certain periods.

There are four main types of neuroplasticity observed in children:

Adaptive plasticity.This happens when children practice a skill or learn new information. It enhances skill development and recovery from brain injury.

Impaired plasticity.This type of neuroplasticity happens due to an acquired or genetic disorder. It's associated with cognitive impairment.

Excessive plasticity.Also known as maladaptive plasticity, this process involves the reorganization of maladaptive pathways. This can cause disorders or disabilities. The best example of maladaptive plasticity isfocal dystonia. It is a rare neurological disorder that involves involuntary spasms in small muscles in the body.

Injury vulnerability plasticity.This type of neuroplasticity involves the formation of harmful pathways in the brain. This makes the brain more vulnerable to injury.

As we age, the brain starts to remove synapses that it no longer needs. Old connections are deleted through synaptic pruning. This happens when we are about 2 to 3 years old, after the number of synapses reaches a peak level.

Our brain's plasticity is at its highest during the first 20 years of life. What's more, we are constantly losing neurons as we age.

But the adult brain can still create new neuronal connections. Neuroplasticity is not only prevalent in children.

With the right lifestyle, adults can increase their brain's plasticity.

How to rewire your brain with neuroplasticity training

Neuroplasticity training includes lifestyle choices that promote the regeneration of nerve cells. With regular practice, it helps to improve:

Let's look at five ways you can promote neuroplasticity.

1. Utilize brain games

Brain training exercises create targeted mental stimulation and activation. This reorganizes the connections between neurons and improves brain plasticity.

A study found that younger adults who enjoyed brain training games had better executive function. They also had improved memory, self-control, and brain-processing speed than their peers.

Nowadays, you can easily use apps like CogniFit and BrainHQ for mental stimulation.

2. Rest when you need to

A good night's rest helps to create lasting memories. It also generates synapses to store skills and information that you learned in the day.

3. Exercise regularly

Research shows that daily exercise is essential for focus, concentration, and mood. It's recommended that you get in 150 minutes of moderate-intensity exercise each week.

Exercise boosts the density and size of cortical neurons. This can benefit:

Attention

Perception

Memory

There's even some evidence that it can delay Alzheimer's disease.

Physical activity also helps to decrease inflammation and improve your quality of sleep. Both of which are factors that can impact your cognitive function.

4. Adopt a healthy diet

Nutrition plays a role in so many areas of our lives, and it's important for brain health too. You can promote neuroplasticity by eating a healthful, anti-inflammatory diet. This should include plenty of essential antioxidants and brain-fuelling omega-3 fats.

Improving the health of your gut microbiome can also promote neuroplasticity.

Eat unprocessed foods with prebiotic fibers to feed the good bacteria in your gut. Consider adding fermented foods such as kimchi to your daily menu.

5. Connect with others

Positive social experiences prime our neural connections to make meaningful connections with others.

The more we make an effort to connect with and care for others, the stronger these impulses will become. And the more naturally we'll find ourselves gravitating toward our peers.

History and research of neuroplasticity

Let's take a look at both early and modern theories surrounding the concept of neuroplasticity.

Early theories

The idea that the brain is not fixed was first proposed by William James in 1890. Later in the early 1900s, the father of neuroscience, Santiago Ramón y Cajal, used the term 'neuronal plasticity.' This referred to non-pathological changes in the structure of adult human brains.

In 1923, Karl Lashley performed experiments on rhesus monkeys. He noted changes in their neural pathways, which he believed was evidence of plasticity.

Then in 1945, Justo Gonzalo theorized that the central cortical mass was a 'maneuvering mass.' It could reorganize its functions with its neuroplastic properties.

Modern theories

One of the key founders of the modern field of neuroplasticity was Dr. Michael Merzenich. In the early 1970s, Merzenich conducted experiments to prove that the brain was fixed. He tried to prove that the brain was not capable of structural or functional change.

Interestingly, he proved his own theories incorrect. He discovered that the brain and its neurons are plastic. Lost skills stored in damaged tissue could be relearned in other parts of the brain.

Merzenich also found that the human brain has a 'cortical map' of the physical parts of the body. If one map was deprived of its information inputs, it could become active again in the future if other maps close to it were stimulated.

Merzenich suggested that neuroplasticity could happen beyond developmental periods and into adulthood.

In a study with Clinton Woosley, Merzenich tried to observe what happened in the brain when one peripheral nerve was severed and then regenerated. The pair micro-mapped the hand maps of monkeys' brains before and after severing the nerves and reattaching them.

They found that the brain maps could normalize their structure, even in response to abnormal inputs. This proved that the brain had to be plastic in order to reach this degree in compensation.

Merzenich was awarded the 2016 Kavli Prize in Neuroscience for his work in discovering adult brain plasticity.

Healing the brain with neuroplasticity after trauma

People with varying degrees of brain trauma can recover full functionality thanks to neuroplasticity. Based on research published in Translational Research in Traumatic Brain Injury, the brain goes through three main phases of neuroplasticity after experiencing trauma:

Phase 1

Directly after the injury, neurons start to die. Cortical inhibitory pathways are decreased. This initial phase lasts 24-48 hours.

It may stimulate secondary pathways that had rarely been used before the trauma.

Phase 2

The second phase takes place a few days after the trauma. The activity of these cortical pathways changes from inhibitory to excitatory.

New synapses are created. Neurons and other brain cells replace the damaged cells to facilitate healing.

Phase 3

The final phase takes place after a few weeks. The new synapses continue to be generated to remodel the brain.

During this phase, therapy and rehabilitation can help the brain learn new neural pathways. This allows for the brain to reduce the effects of the trauma.

There are several medical treatments in development that encourage neuroplasticity after brain injury. There are also therapies involving stem cellsand gene expression being studied for their potential to treat trauma.

Neuroplasticity rehabilitation for stroke recovery

A stroke causes damage by cutting off the flow of blood to certain parts of the brain. This deprives the brain of oxygen and essential nutrients.

Depending on the severity of the stroke, volumes of brain cells may die. Brain volume may be reduced, and dysfunction may occur as a result. The recovery process after a stroke relies on the brain's ability to heal itself.

The brain works around the dead brain cells. It attempts to build other neural pathways to compensate for lost function.

Physical, occupational, and speech therapies are all designed to promote neuroplasticity. They encourage the brain to overcome any mental and physical deficits.

It's important to begin the rehabilitation process as soon as possible after a stroke. This will make use of the brain's natural increase in neural plasticity after the trauma.

Stroke victims can promote recovery by participating in therapies that:

Focus on massed practice. This is the consistent repetition of a movement or skill that promotes fast learning.

Include physical exercises and therapies to improve patient mobility and strength.

Reteach them the skills they will need to go about their daily lives. This includes standing up, basic personal hygiene, simple cooking, andcommunication skills.

Include speech therapies. This will enable patients to practice their language skills while stimulating their brains.

How can neuroplasticity help with anxiety and depression?

Depression and anxiety have both been linked to a decrease in neural plasticity in the brain.

Modern therapies are aimed at encouraging neuroplasticity. This is so that patients can learn valuable coping skills for life's many challenges.

Neuropsychiatry's understanding of neuroplasticity can be summed up as follows:

Our daily behaviors can have remarkable effects on the structures of our brains. Anxiety and depression can, at least to a degree, be "unlearned." Their tendencies can be replaced with more constructive pathways through professional neural training.

COVID-19 PTSD is set to become a significant public health concern in the future. Prolonged exposure to stress and anxiety can lead to PTSD. But therapies focusing on promoting neural plasticity may induce positive plasticity.

This could help combat these conditions before they have a chance to develop into a disorder.

Simple neuroplasticity exercises can all promote neural plasticity. These include:

Regular exercise

Healthy diet

Connecting with your loved ones

They also help reduce the symptoms of anxiety and depression.

Experts recommend activities like learning a new language or skill. You could also perform a manual motor activity like painting or building a model. Or you can try playing brain-training games to promote neuroplasticity training.

The power to change your mind

Neuroplasticity and synaptic plasticity are intrinsic in every facet of our lives. Our brains are constantly performing synaptic pruning and making new neural connections. This is true regardless of what we happen to be doing at any given time. Or even whether we are awake or asleep.

Improving your brain's plasticity will sharpen your memory, concentration, and cognitive skills. Plus, it can help you address depression and anxiety. It may even promote healing in the case of adult brain trauma or injury.

BetterUp Coaches can help you understand the amazing ability of your brain to constantly learn. Coaching can guide you with how to put plasticity to work to your advantage to change behaviors and show up at your best. Use your brain's innate healing abilities to perform better and unlock more of your human potential.

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What is Neuroplasticity and Why is It Important?

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The human brain is constantly building new connections using its neuroplasticity. Read on to learn about what neuroplasticity is and how it benefits you.

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Learners cannot be passive recipients of content but must be active participants in the learning process

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Learners cannot be passive recipients of content but must be active participants in the learning process

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At the Ecole Internationale de Genève - or Ecolint - we aim to educate students to be "global citizens with the courage and capacity to create a just and joyful tomorrow together". But what does it mean to be a global citizen, and what do we mean by a just and joyful tomorrow?

Our work with our historical partners, UNESCO's International Bureau of Education, has led us to describe seven global competencies that encapsulate the knowledge, skills and attitudes necessary to flourish as a global citizen and contribute to a better world. These are the competencies that we look to nurture in every student and which go well beyond test scores or grades :

1. Lifelong learning: learning how to learn, curiosity, creativity, critical thinking, communication skills, problem-solving, reflection and innovation.

2. Self-agency: initiative, drive/motivation, endurance/grit/resilience, responsibility, entrepreneurship, accountability, self-management, exercising rights and responsibilities, self-value.

3. Interactively using diverse tools and resources: impactful and efficient use of resources, responsible consumption, interfacing with tools.

4. Interacting with others: teamwork, collaboration, negotiation, leadership, followership, conflict management, respect for others.

5. Interacting with the world: balancing rights with responsibilities, balancing freedom with respect, balancing power with restraint, being local and global, environmental custodianship, global awareness.

6. Multi-literateness: reading and writing, numeracy, digital literacy, data literacy, technological literacy, coding, media literacy, financial literacy, cultural literacy, health literacy.

7. Transdisciplinarity: mastery within and across STEM (sciences, technology, engineering, and mathematics), the arts, the humanities, social sciences, religions, languages and vocations.

There are many ways that we make these competencies flourish in our students: through our unique Universal Learning Programme with its character, passion and mastery projects, which develop initiative, drive and endurance; through a transdisciplinary "Mission to Mars" project, which stimulates critical and creative thinking; through our Student League of Nations, which enhances global awareness and respect for others, and in myriad other ways.

We are not unique in our desire to educate the whole child, with many schools across the world aiming to develop similar competencies. However, the approach was pioneering when we invented the IB Diploma here at Ecolint in the 1960s. All the IB programmes now do this, for example, the Primary Years Programme Student Exhibition, with its emphasis on responsible action, the Middle Years programme with its emphasis on interdisciplinary study and the Diploma Programme, with its broad and balanced curriculum, the core of Theory of Knowledge, the Extended Essay and CAS (Creativity, Activity, Service). All of these programmes are designed with much more than academic scores in mind as an outcome.

However, when it comes to admitting students to tertiary education, most universities only ask for a grade transcript and personal statement along with recommendations. All the work on creativity, thinking across subjects, developing responsibility and citizenship that has been a core part of every child's education is not looked at. The time has come to present universities with a much fuller story that truly reflects the breadth and depth of quality education.

This is why we have designed our Ecolint Learner Passport: to take the story of learning all the way to the end of Secondary School so that universities accept students on a broader range of criteria.

The Ecolint Learner Passport allows students to gain credit for competence development in the curriculum (academic subjects and class projects) and outside the curriculum (extracurriculars, vocational work, hobbies and passion). In describing a global competence, each credit area tells the story of how students have grown, who they are, and what makes them stand out.

Working with other like-minded schools across the globe, we have created the Coalition to Honour All Learning, which is federating other schools and universities to join this movement, recognising that students are so much more than a number or a grade. The Ecolint Learner Passport is a movement to celebrate the whole child.

To find out more about the Ecolint Learner Passport or to join the Coalition, contact *protected email*.

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Reinventing High School Transcripts: The Learner Passport

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At the Ecole Internationale de Genève - or Ecolint - we aim to educate students to be "global citizens with the courage and capacity to create a just and

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Mastery Transcript Consortium® (MTC) | Join the effort to create a high school transcript to transform high school.

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The power of the Mastery Transcript and MTC Learning Record is not only in what they communicate, but also in what they enable: learning that is deeply personalized, learner-driven, based in authentic engagement, and designed to educate the "whole student." Key benefits are:

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Mastery Transcript and MTC Learning Record | Mastery Transcript Consortium® (MTC)

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MTC has co-designed and built a software platform that high schools use to publish Mastery Transcripts for college admissions readers and/or employers.

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Formative assessment, which entails both formal and informal evaluations through the learning journey, encourages students to actually improve their performance rather than just have it evaluated.

Many universities are starting to abandon standardized testing. There have been some attempts to replace high-stake exams with other measures that not only assess learning outcomes but actually improve them.

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Education

Higher education needs to address the problems it faces by moving towards active learning, and teaching skills that will endure in a changing world. Image: Vasily Koloda for Unsplash

Senior Director, Strategic Communications and Thought Leadership, Minerva Project

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Many people gain admission to higher education based on standardized tests that skew to a certain socio-economic class Image: Fairtest, College Board

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4 trends that will shape the future of higher education

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Higher education needs to reform by moving towards active learning, teaching skills that will endure in a changing world, and adopting formative assessment. Here are 4 higher education trends to watch out.

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

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

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

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

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

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

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

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

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

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

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

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A powerful way to improve learning and memory

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

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Learners cannot be passive recipients of content but must be active participants in the learning process

An enriched environment for enhanced neuroplasticity offers physiological integrity, cognitive challenge, and emotional safety. More specifically, an enriched environment includes adequate sleep and nutrition, sensory–motor and cognitive challenges, opportunities for exploration and novelty, and secured relationships that act like a safety net and enable learners to take on challenges [22,23]. Conversely, a lack of these conditions may slow down or decrease the level of neuroplasticity in the developing brain.

The social and cognitive safety net that enables learners to aim high while taking risks and to turn failure into resilience is rooted in safe relationships (with adults and peers) and in holding a growth mindset.

A growth mindset is the belief that intelligence and learning potential are not fixed and can be developed [24]. Holding a growth mindset has been associated with academic success, emotional wellbeing, and motivation while reducing racial, gender, and social class achievement gaps [25,26,27,28,29,30]. ...the literature is clear about the potential of growth mindset intervention in supporting the academic development of high-risk and economically disadvantaged students [26,27,31,32].

teaching students about neuroplasticity and the dynamic potential of their brains has been shown to effectively reinforce a growth mindset [32]

“use it or lose it” and “use it to improve it” mean that, while teachers should support and guide them, learning occurs by and within the students. This physiology-based realization can help build students’ responsibility and ownership over their learning

Harnessing neuroplasticity and a growth mindset to motivate students can be especially important with neurodivergent learners...on the autistic spectrum (ASD), students with learning disabilities (e.g., dyslexia), attention disorders (e.g., ADHD), neurological disorders (e.g., epilepsy), and mental illness (e.g., PTSD). ...can be motivated to participate in evidence-based interventions. For example, teaching students with dyslexia about the specific structural and functional brain changes associated with the reading interventions that they apply [34,35,36] can motivate them to endure the hard work before noticing visible results.

Educational environments that promote neuroplasticity include encouraging and modeling a healthy lifestyle (physical exercise, a balanced diet, sufficient sleep, and regulated stress) - **weave this into my courses and how they benefit and support the learner in their other courses, learning career, and life in general**

While students of the digital era are the most stimulation-flooded and attention-challenged in human history, learning is a process that takes time, selective attention, and perseverance. Therefore, learning designs that harness students’ intrinsic motivation for training and the development of stamina and grit (skills that might be hampered in the digital era) are precious for students’ health and success.

Motivational drivers include an adequate level of challenge that fits the student’s sense of competence and that creates optimal arousal levels, opportunities to expand social relatedness and impact, and a balance between support and autonomy.

Social motivation has been shown to enhance the encoding of new information (even if the content is not social) [57]. Learning-for-teaching and peer tutoring (one student teaching another student) effectively encode information into memory.

As the environment provides more information than the brain can handle, survival depends on saliency detection and attention management to direct perception and behavior. The brain constantly selects and attends to relevant input while suppressing irrelevant or distracting information [67]. Information that is valuable or urgent for survival and prosperity receives attention.

...students will benefit from an educational design that stimulates the natural interplay between “intrinsic” (DMN) and “extrinsic” (CEN) brain networks by incorporating external stimulation (e.g., presenting content), allocating time and space for intrinsic reflection (e.g., guided reflection and journaling), and integrating the two (e.g., guided class discussion and insights sharing) [83,84].

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Department of Psychology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada

1. Educational Neuroscience (Teaching for the Brain and Teaching about the Brain)

Educational neuroscience is an interdisciplinary field exploring the effects of education on the human brain and promotes the translation of research findings to brain-based pedagogies and policies [ 1]. The brain is the target organ of education. Education is thought to influence brain development [ 2, 3] and health, even as the brain ages [ 4, 5]. Studying the dynamics between the brain and education can be instrumental in finding ways to better support learners across the lifespan.

Educational neuroscience research explores every possible relationship between the physiological, mental, and behavioral aspects of learning. Some studies have tried to identify the optimal physical conditions for neuroplasticity and learning. This stream of educational neuroscience research includes studies exploring the effects of sleep (or sleep deprivation), physical exercise, and environmental pollution on the brain and its cognitive performance [ 1]. While these studies focus on the effect of brain health on learning, other studies examine the effect of learning on brain health, assessing the long-term effects of learning/education on the human brain and exploring in what ways formal/informal education is associated with better aging of the human brain [ 2, 3, 4].

Some educational neuroscience studies take a developmental approach to study the relationship between cognitive and learning capacities across the lifespan. For example, multilevel measurements collected from adolescents (e.g., neuronal, hormonal, psychological, and behavioral) have advanced our understanding of how the massive neuronal changes that take place during adolescence promote cognitive development but also introduce immense neuronal and mental vulnerability (and the onset of most psychiatric disorders) [ 1, 5, 6, 7]. Other studies in this line of research explore the factors supporting neuroplasticity in the mature brain-to support lifelong learning [ 8].

Educational neuroscience also explores the nature-nurture aspects of learning, for example, examining how learning environments interact with genetic conditions and what DNA variations predict differential learning abilities [ 9]. Environmental influences on learning include studies about the impacts of socio-economic status (SES) on the brain and cognitive developmental trajectory [ 10]. Furthermore, educational neuroscience seeks to understand the mechanisms that facilitate general learning abilities (such as executive control and social and emotional skills), discipline-specific learning abilities (such as literacy, numeracy, and science), the connections between these mechanisms, and the extent to which these learning skills are trainable [ 11].

As a developing, interdisciplinary research field, educational neuroscience faces challenges, limitations, and criticism, especially concerning the ability to generalize research findings in lab conditions to classroom learning, and its validity and transferability to larger scales, such as mass education systems. Other challenges stem from the fact that learning is one of the most basic yet complex brain functions that incorporates the entire brain and has a continuous effect. Furthermore, empirical studies in educational neuroscience are challenging and cumbersome due to the interdisciplinary nature of the field (education, psychology, and neuroscience); the need for repeated measures over time; and the young target population (school students), which imposes ethical restrictions on experimental designs. Finally, while still evolving as a research field, educational neuroscience is intriguing for many educational leaders who are enthusiastic about applying neuroscience in education practices. Unfortunately, the current gap between the high demand and limited supply may lead to misuse of neuroscience in pedagogy (e.g., neuromyths or the justification of educational methods based on limited to no evidence) [ 1].

While educational neuroscience is preliminary in forming evidence-based pedagogy, it can already offer valuable information and a much-needed bridge between educators and scientists in translating the research of learning into effective educational practices.

Neuroscience-informed educational design (teaching the way the brain learns) can promote learning motivation, high-level information processing, and knowledge retention. Moreover, neuroscience educational content (teaching about the brain) can inform students about their developing brains to promote scientific education and self-exploration.

1.1. Learning and Neuroplasticity

Human development is based on nature (genetics), nurture (physical and social environments), and their interactions (epigenetics) [ 12, 13]. These factors play an essential role in learning processes and the reorganization of neuronal networks to create neuronal representations of new knowledge. Learning and training new knowledge or skills evoke specific and repeated activity patterns, and in the process of Hebbian neuroplasticity, neural pathways are reinforced by the strengthening of specific synapses, while less functional ones are eliminated [ 14, 15, 16].

Almost half a century ago, Vygotsky introduced the zone of proximal development (ZPD) [ 17] in education. According to the ZPD, learning and development depend on an optimal balance between support and challenge (see Figure 1: the zone of proximal development and neuroplasticity), which should be tuned and tailored for each learner based on their specific developmental stage. The ZPD model was revolutionary, as it emphasized the importance of the educational environment (nurture) in unlocking the internal potential (nature) of students, and it placed the learning process (as opposed to the learning product) as the central educational goal [ 17]. Some decades later, the biology of learning revealed a beautiful alignment with Vygotsky's theory-with evidence showing that brain neuroplasticity is highly affected by environmental conditions and the balance between demands (challenge) and available resources (support) [ 18]. The impact of stressors on learning can be constructive or destructive depending on the intensity, duration, and accumulation of the stressors and the coping mechanisms and support that one has.

Neuroscience research suggests that experience-dependent neuroplasticity [ 19], which facilitates learning processes, benefits from several principles. The central one is that learning a skill or new knowledge requires the activation of relevant neuronal pathways. The research also points to the saliency, intensity, and repetition of the learned skill/knowledge as valuable strategies for enhancing neuroplastic changes [ 16, 20, 21]. Learners cannot be passive recipients of content but must be active participants in the learning process.

An enriched environment for enhanced neuroplasticity offers physiological integrity, cognitive challenge, and emotional safety. More specifically, an enriched environment includes adequate sleep and nutrition, sensory-motor and cognitive challenges, opportunities for exploration and novelty, and secured relationships that act like a safety net and enable learners to take on challenges [ 22, 23]. Conversely, a lack of these conditions may slow down or decrease the level of neuroplasticity in the developing brain.

The social and cognitive safety net that enables learners to aim high while taking risks and to turn failure into resilience is rooted in safe relationships (with adults and peers) and in holding a growth mindset. A growth mindset is the belief that intelligence and learning potential are not fixed and can be developed [ 24]. Holding a growth mindset has been associated with academic success, emotional wellbeing, and motivation while reducing racial, gender, and social class achievement gaps [ 25, 26, 27, 28, 29, 30]. While the impact of mindset interventions on academic performance is debatable regarding the general population [ 31], the literature is clear about the potential of growth mindset intervention in supporting the academic development of high-risk and economically disadvantaged students [ 26, 27, 31, 32].

The notion of human potential as something dynamic resonates with the concept of the plastic brain. Moreover, teaching students about neuroplasticity and the dynamic potential of their brains has been shown to effectively reinforce a growth mindset [ 32].

1.1.1. Using Neuroplasticity as Educational Content

Teaching students about experience-based neuroplasticity and the dynamic changes in neuronal networks during learning provides strong evidence of their natural and powerful learning capacity. Furthermore, teaching students about neuroplasticity with explicit connections to the growth mindset and development creates a motivating premise for learners-according to which their learning potential is dynamic and depends significantly on their attitudes and learning practices.

The neuroplasticity rules of "use it or lose it" and "use it to improve it" mean that, while teachers should support and guide them, learning occurs by and within the students. This physiology-based realization can help build students' responsibility and ownership over their learning.

Harnessing neuroplasticity and a growth mindset to motivate students can be especially important with neurodivergent learners, whose cognitive development and learning styles deviate from the typical range. Twenty percent of the population is neurodivergent, including students on the autistic spectrum (ASD), students with learning disabilities (e.g., dyslexia), attention disorders (e.g., ADHD), neurological disorders (e.g., epilepsy), and mental illness (e.g., PTSD). While neurodiversity and variations in neuronal and cognitive expressions hold many advantages [ 33], neurodivergent students face extra challenges navigating neurotypical-oriented school systems. Learning about neuroplasticity can be a potent form of validation for neurodivergent students, as neurodiversity is a natural result of experience-dependent neuroplasticity [ 19]. In addition, by fostering a growth mindset and neuroplasticity awareness, neurodivergent students can be motivated to participate in evidence-based interventions. For example, teaching students with dyslexia about the specific structural and functional brain changes associated with the reading interventions that they apply [ 34, 35, 36] can motivate them to endure the hard work before noticing visible results.

1.1.2. Using Neuroplasticity to Guide Learning Design

Organizing learning systems around conditions that promote neuroplasticity can enhance learners' academic development and wellbeing. When a student accomplishes today what was not in their reach yesterday, it is the product of neuroplasticity through a growth mindset.

Educational environments that promote neuroplasticity include encouraging and modeling a healthy lifestyle (physical exercise, a balanced diet, sufficient sleep, and regulated stress), -for example, educating students about the counter-productiveness of sleep deprivation (e.g., "all-nighter" study marathons) on learning. In addition, learning systems should invest in intellectual stimulation (novelty and challenge) and the system's social and emotional climate (human connections). Neuroplasticity and development are optimal in the stretch zone, where learners experience a motivating level of challenge and stimulation while feeling emotionally supported and socially safe. This ratio between support and challenge should be individualized (between learners and within learners over time).

Educating teachers about neuroplasticity can be powerful in understanding and supporting students that were affected by trauma. Childhood adversity hampers neuroplasticity duration and magnitude [ 37]; a surviving brain is not a learning brain. While neuroplasticity is compromised by early trauma, neuroplasticity is also the key to healing from trauma. Schools have a pivotal role in battling the damage of early trauma by creating enriched and safe learning environments that reinforce alternative neuronal pathways to reverse the effects of early adverse environments on child brain development [ 22, 38, 39, 40].

1.2. Learning Motivation and Reward

Learning and adaptation are essential for surviving and thriving in dynamic environments. The brain evolved to make sense of information from our external and internal environments and to produce adaptive behaviors that promote survival. The brain is, therefore, a learning machine by nature, and learning does not require external initiation. However, learning is highly experience-dependent and can be directed and enhanced through education.

The brain reward system evolved to reinforce effortful behaviors that are essential for survival (e.g., foraging, reproduction, and caregiving). Such behaviors activate the dopaminergic system associated with reward and motivation [ 41]. The hormone/neurotransmitter dopamine is a central player in reward-motivated behavior and learning through the modulation of striatal and prefrontal functions [ 42]. The human brain reward system balances between (limbic) impulsive desire and (cortical) goal-directed wanting to guide flexible decision-making and adaptive motivational behaviors.

Psychologically, intrinsic motivation is driven by the need to experience a sense of competence, self-determination, and relatedness [ 43, 44, 45, 46, 47].

Competence refers to a perception of self-efficacy and confidence in one's abilities to achieve a valuable outcome. Self-determination refers to the sense of autonomy and agency in the learning process. Relatedness refers to the drive to pursue goals that hold social value, which can be achieved by working collaboratively as part of a team or by creating something that resonates with others. Relatedness is a strong motivational driver, as it touches on a primary and primordial need to be part of a group and a higher spiritual and intellectual need for self-transcendence and impact.

Overall, these components are based on the human inclination to be valued and validated by the self and others. Biologically, they reflect basic survival needs that combine self-reliance (competence and ownership) and social reliance. Psychologically, these are all subjective perceptions that serve the need to maintain positive self-perception and self-integration. Finally, educationally, they reflect the natural human curiosity and tendency to learn and develop continuously.

The human brain reward system in the 21st century is an evolutionary mismatch. There is a discrepancy between the conditions that the reward system evolved to serve and those that it often faces in the 21st century. The reward system evolved over millions of years to motivate humans to work hard (invest time and energy) in maintaining their survival needs (e.g., nutrition, protection, reproduction, and the learning of new skills). However, this system is not designed for the abundance and immediacy of stimulation in the digital and instant reward era, which promotes the persistent release of dopamine that leads to an increased craving for reward (seeking behavior; wanting) and a decreased sense of pleasure and satisfaction (liking) [ 42, 48].

Some of the most significant challenges of modern education systems relate to the massive changes in how people consume information and communicate in the digital era. Digital platforms have become dominant in information consumption and communication, which provide access to unlimited information and reinforce immediate rewards.

1.2.1. Using Neuroscience (of Reward and Motivation) as Educational Content

The science of human motivation, including its evolutionary mismatch, can be utilized to shed some light on students' struggles with learning motivation. It can further provide a framework for students to explore their motivational (approach or avoid) tendencies regarding learning and academic challenges. Moreover, learning the neuroscience underlying motivation and reward can raise students' awareness and proactivity in managing and protecting their reward system. Since adolescence is the peak time for the initiation of substance use, and early onset imposes a higher risk of mental health and substance abuse disorders persisting into adulthood [ 49, 50, 51], neuroscience knowledge about the reward system and its vulnerability (especially during brain development) is essential educational knowledge that can help in the prevention and mitigation of teen addiction.

1.2.2. Using Neuroscience to Guide Learning Design and Intrinsic Motivation

While students of the digital era are the most stimulation-flooded and attention-challenged in human history, learning is a process that takes time, selective attention, and perseverance. Therefore, learning designs that harness students' intrinsic motivation for training and the development of stamina and grit (skills that might be hampered in the digital era) are precious for students' health and success.

Motivational drivers include an adequate level of challenge that fits the student's sense of competence and that creates optimal arousal levels, opportunities to expand social relatedness and impact, and balance between support and autonomy (see the ZPD, Figure 1).

Importantly, in classroom learning, educators are required to manage the attention, motivation, and reward system of not one but many students, which is a complex task. The typical classroom presents a broad spectrum of learners with diverse learning needs and stretch zones ( Figure 1). While the facilitation of autonomy and the sense of competence varies between learners and requires personalized support, the social norms that promote learning are more ubiquitous and apply to most learners. While educators do not always have the resources to support students' motivation individually, harnessing the social aspects of classroom learning is a manageable, effective strategy to elevate students' motivation. Learning environments that demonstrate empathy, inclusiveness, and psychological safety have shown positive results in students' behavior, self-esteem, motivation, and academic success [ 52, 53, 54, 55, 56]. Social motivation has been shown to enhance the encoding of new information (even if the content is not social) [ 57]. Learning-for-teaching and peer tutoring (one student teaching another student) effectively encode information into memory. Beyond memory improvement, peer tutoring has many further benefits to both the tutor and the learner in academic achievements [ 58, 59], motivation, and ownership over the learning process and results in a deep conceptual understanding of the material [ 60].

The teacher's demeanor is another controllable factor with a high potential to affect students' motivation. For example, the literature points to teachers' immediacy (creating physical and psychological closeness with students) as an effective way to enhance students' engagement, learning motivation, and performance (including memory retention) [ 61, 62, 63, 64, 65]. Immediacy can be demonstrated through verbal and non-verbal gestures that communicate interest and personal connection (relating to personal stories, using animated voice and body language, creating eye contact, and using humor).

The research also indicates that, when students perceive the content as being personally relevant, they are more motivated to study [ 66]. Therefore, educators can actively make the learning content more relevant by using stories and real-life examples, making explicit connections and demonstrations of how the content may be relevant/applicable to the students, and giving students opportunities to reflect and share their connections to the learning material.

In summary, physiological and psychological approaches point to primary motivational drivers that direct engagement and investment in the learning process. Not surprisingly, these drivers that are anchored around social and intellectual needs align with the conditions supporting neuroplasticity discussed in the first part of this review.

1.3. Intrinsic and Extrinsic Processing in Learning and Meaning-Making

As the environment provides more information than the brain can handle, survival depends on saliency detection and attention management to direct perception and behavior. The brain constantly selects and attends to relevant input while suppressing irrelevant or distracting information [ 67]. Information that is valuable or urgent for survival and prosperity receives attention. Attention capacities (e.g., alerting, orienting, and controlling attention) are managed by several brain systems that interact and coordinate [ 68, 69, 70]. Top-down, cognitive-driven attention that fosters a goal-directed thinking process is associated with the dorsal attention network (consisting of the intraparietal sulcus and the frontal eye fields) [ 71]. This mechanism enables students to read a paragraph, listen to a lecture, think about the teacher's question, or write an essay. A second attention system is bottom-up and stimulus-driven, and it orients attention to unexpected and behaviorally relevant stimuli. This ventral attention network consists of the right temporoparietal junction and the ventral frontal cortex [ 71]. This attention-grabbing mechanism enables the individual to respond quickly to urgent environmental demands, for example, moving away to prevent a struck-by-object accident. Flexible attention control depends on dynamic interactions and switching between the two systems and involves the central executive network (CEN) [ 68, 70].

The insula and anterior cingulate cortex comprise the core structures of the saliency network [ 72], another major player in attention altering to emotionally salient stimuli through the interaction of the sensory and cognitive influences that control attention [ 72, 73, 74].

In addition to outward-focused attention, the human brain is also invested in inward-focused processing. Functional brain imaging studies of the human brain show a robust functional anticorrelation between two large-scale systems, one highly extrinsic and the other deeply intrinsic [ 75, 76, 77]. The central executive network (CEN) is an externally driven system and is paramount for attention control, working memory, flexible thinking, and goal-directed behavior. The core components of the CEN are the dorsolateral PFC and the lateral posterior parietal cortex (hence, the frontoparietal network) [ 72, 78]. When the human brain is not occupied with external tasks, the default mode network (DMN) is activated. This internally driven cognitive network includes the posterior cingulate cortex (PCC) and the medial prefrontal cortex (MPFC) as core components. The DMN is thought to facilitate reminiscing, contemplating, autobiographical memory, self-reflecting, and social cognition [ 79]. Conversely, the DMN is immediately suppressed when the brain is engaged in externally driven tasks and stimulation.

Resting-state brain imaging studies revealed that the activity in the DMN during resting awake states indicates the quality of subsequent neural and behavioral responses to environmental stimuli [ 72, 80]. Moreover, a high connectivity between "intrinsic" (DMN) and "extrinsic" (CEN) brain networks, and specifically emotional saliency, attention (extrinsic), and reflection (intrinsic) networks is associated with better cognitive performance, meaning-making, and broad perspective thinking [ 75, 76, 81]. These networks function antagonistically but are highly connected and balance each other. Furthermore, the anticorrelation between their function is associated with better task performance and positive mental health [ 79, 82]. Recent studies also suggest that a causal hierarchical architecture orchestrates this anticorrelation between externally and internally driven brain activities. More specifically, that regions of the saliency network and the dorsal attention network impose inhibition on the DMN. Conversely, the DMN exhibits an excitatory influence on the saliency and attention system [ 79].

1.3.1. The Neuroscience of Extrinsic and Intrinsic Processing as Educational Content

Teaching students about the dynamics of the default mode and executive control network can help them understand how their brain processes information, the importance of each process (e.g., extrinsic and intrinsic), and their integration for meaningful learning. This knowledge can be applied as students explore and experiment with ways to enhance their learning and memory by intentionally engaging both intrinsic and extrinsic processing and integrating the two.

1.3.2. Using the Neuroscience of Extrinsic and Intrinsic Processing to Guide Learning Design

Traditionally, instructional education is based on learning objectives that are externally dictated and is focused on outward attention (stimulus-driven lectures and assignments). Mind-wandering has become the enemy of classroom teachers, as it indicates students' lack of attention and poor learning.

Nevertheless, neuroscience research indicates that meaning-making and cognitive performance benefit from the interplay between extrinsic and intrinsic oriented attention and processing [ 56, 75].

Learning instructions should consider the different attention mechanisms, evoking adequate arousal levels and leading to goal-directed thinking. Furthermore, students will benefit from an educational design that stimulates the natural interplay between "intrinsic" (DMN) and "extrinsic" (CEN) brain networks by incorporating external stimulation (e.g., presenting content), allocating time and space for intrinsic reflection (e.g., guided reflection and journaling), and integrating the two (e.g., guided class discussion and insights sharing) [ 83, 84].

2. Discussion

2.1. Teaching Students about Their Developing Brains

As far as we know, humankind is the only species with access to the underlying mechanisms of its perception, learning, and inner workings. In addition, the human brain is endowed with a lengthy developmental period of approximately 25 years [ 85, 86]. Therefore, schooling years are the prime time for neuroplasticity, and students can learn about their brains while they are highly malleable and can utilize this to amplify their learning and growth.

While students were traditionally required to choose whether to focus on the humanities or science fields, an integrative view is becoming increasingly common in academic institutes. Multidisciplinary studies have been shown to promote students' positive learning and professional outcomes [ 87]. Teaching neuroscience from a dual perspective, both scientific/objective and humanistic/subjective, is a novel but natural bridge between the humanities and science fields.

Studying neuroscience with explicit connections to the lived experience of brain development and its behavioral manifestation can be academically and personally transformative for students.

Shedding a scientific light on students' experiences as they unfold can support significant developmental processes during those years, such as improvements in executive functions, emotional regulation skills, meta-cognition, and social cognition [ 88].

Among the topics and burning issues of teens and young adults that neuroscience can offer insights into are selective and leaky attention [ 89], the reward system and addiction [ 90], the PFC-limbic developmental mismatch during adolescence [ 91], neurodiversity and inclusion, emotion regulation, and mental health [ 92].

Moreover, adding a personal layer to neuroscience studies fits the notion that personal relatedness and relevance are essential for learning motivation. Teaching neuroscience from a dual (scientific and personal) perspective and connecting neuroscience knowledge to a deeper understanding of the self and others can elevate engagement and nurture students' passion for science and their ability to integrate and transfer scientific knowledge across contexts. In addition, similar to the effect of physical education, educational neuroscience can promote the awareness of brain health and encourage students to be intentional about their education and developmental trajectory.

2.2. Teaching the Way(s) the Human Brain Learns Best

Teaching students in brain-friendly ways means implementing principles that align with how the human brain encodes, consolidates, and retrieves information. Educational neuroscience points to the importance of a holistic and integrated view of cognitive, emotional, and social aspects to support learning and development [ 52, 75, 93, 94]. Maintaining physical health, cognitive challenge, and emotional safety are essential factors in creating an enriched environment that supports neuroplasticity and learning.

Assessing the learning progress rather than the end product can encourage students to move away from rote memorization to more meaningful learning that carries on beyond the final exam.

Meaningful learning can be promoted by learning designs that encourage students to take experimental and explorative approaches, take risks, and make mistakes without detrimental consequences to their grades.

Furthermore, assessments throughout the learning process and not only at the end of it, using multiple sample points and low-risk tasks, can provide information on the student's learning curve and allow for personalized and timely feedback that students can apply to improve their learning on the go.

These methods not only promote psychological safety but also align with the evidence-based practices of building long-term and accessible knowledge by spreading out the learning concept across time (spacing), practicing information retrieval from memory (recall), and integrating and transferring knowledge (the application of knowledge in different contexts) [ 95].

3. Conclusions

Brain knowledge is brainpower; teaching students about their developing brain can support their academic and personal development by deepening their understanding of science and humanities, their mental capacity, and their self-identity. Educational neuroscience is a promising field in teaching students about their brains and teaching them in brain-friendly ways to support them in becoming lifelong learners.

Funding

This research received no external funding.

Institutional Review Board Statement

The study did not require ethical approval.

Informed Consent Statement

Data Availability Statement

The study did not report any data.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The zone of proximal development and neuroplasticity. An integrative approach between Vygotsky's educational model and the neuroscience of learning. When learning and performance demands exceed the available support and resources, students are likely to be overwhelmed and resort to survival mode (stress zone). When learning and performance demands are significantly lower than the available support and resources, students are likely to be under stimulated and resort to static mode (comfort zone). When learning and performance demands match the available support and resources, students are likely to be appropriately challenged and work within their zone of proximal development, which promotes neuroplasticity and growth (stretch zone).

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Growing Brains, Nurturing Minds-Neuroscience as an Educational Tool to Support Students' Development as Life-Long Learners

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Compared to other primates, humans are late bloomers, with exceptionally long childhood and adolescence. The extensive developmental period of humans is thought to facilitate the learning processes required for the growth and maturation of the complex human brain.

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Operation ARA: A computerized learning game that teaches critical thinking and scientific reasoning

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Operation ARA (Acquiring Research Acumen) is a computerized learning game that teaches critical thinking and scientific reasoning. It is a valuable le...

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[00:00:00] Bonni Stachowiak: On today's episode of Teaching in Higher Ed, Michelle M. Miller joins me for Your Must Remember This episode 348.

[00:00:12] Production Credit: Produced by Innovate Learning, maximizing human potential.

[music]

[00:00:21] Bonni: Welcome to this episode of Teaching in Higher Ed. I'm Bonni Stachowiak and this is the space where we explore the art and science of being more effective at facilitating learning. We also share ways to improve our productivity approaches, so we can have more peace in our lives and be even more present for our students.

[music]

Michelle M. Miller is back for today's episode. Dr. Miller is a Professor of Psychological Sciences and President's Distinguished Teaching Fellow at Northern Arizona University. Dr. Miller completed her PhD in Cognitive Psychology and Behavioral Neuroscience at the University of California, Los Angeles. Her research interests include memory, attention and the impacts of technology on learning and the mind.

Dr. Miller co-created the first-year Learning Initiative at Northern Arizona University and is active and course redesign serving as a redesign scholar for the National Center for Academic Transformation. She is the author of Minds Online, Teaching Effectively with Technology, and has written about Evidence-Based Pedagogy in scholarly as well as general-interest publications, including College Teaching, Change, The Magazine of Higher learning, The Chronicle of Higher Education and The Conversation.

Michelle is currently working on a book for the University of West Virginia press tentatively titled, Remembering and Forgetting In The Age of Technology, what the science of memory tells us about teaching, learning and thriving in a wired world. Michelle, welcome back to Teaching in Higher Ed.

[00:02:15] Michelle M. Miller: Thanks. It's great to be here.

[00:02:17] Bonni: I saw on Twitter, you sharing that you had developed a new talk and I instantly had a song come into my head, do you know what song it was by chance?

[00:02:26] Michelle: I think I have a feeling.

[laughter]

[00:02:29] Bonni: You must remember this.

[laughter]

I have to know did you think of the song first or the title first or it's a chicken-egg thing we can't quite identify here today?

[00:02:41] Michelle: Well, you know, it did grow out of some talks that I even did in the community years ago for our science on tap event, which is on pause right now. Years ago, I called it Everything You Wanted to Know About Memory But Forgot to Ask.

[laughter]

There are lots of different ways. This is a little bit more refined version of this same kind of topic that I've been talking about for years, but it's really come together in this brand new way. Yes, you must remember this.

[00:03:09] Bonni: There's so much that we could talk about and I know we're already both thinking, "How do we do this?" Because it's designed to be a 75-minute talk when this podcast is not designed to be a 75-minute podcast. I just want to start with you sharing a bit about some of the ways in which conversations around lower stakes testing, what that has helped with and small stakes assignments and a lot of these emerging practices in teaching.

Sometimes then I know from learning from you, makes us think, well, then, it's not important than to memorize things. That's quite the opposite of what you'd like to share. Talk a little bit about what we're learning about learning, but how that doesn't mean that we have to then say memorization, just isn't important.

[00:04:01] Michelle: Right. Finding that great middle path, that's so often what we're doing when we try to bring learning sciences into our teaching, but still make it absolutely unique to our teaching so unique to our students. I think it's perhaps part of a familiar dynamic in a way. Some of this also goes back to the very first conversations that I started having with fellow faculty and when I was lucky enough to reach out to some leaders in the teaching and learning space about this topic.

Even when I first started really saying, "Oh, I want to reach out to fellow faculty about Cognitive Psychology, so the findings of my discipline of psychology and flow that out into this great stuff and marry it with some of the really neat innovations and new ways of looking at teaching and learning in higher education."

Right away, I knew that memory was a hot topic. You're right, it did sometimes come up. We talked about more concrete things like, why should we have frequent low stakes testing in a course? I would notice when I would be able to be in front of a group, this is maybe 10, 12 years ago, that I really started doing this work. I'd started talking about memory and memory research.

In cognitive psychology, that is what we have studied more than anything else. This is really at the core of it and so naturally, I'm jumping into that. I would say the M word, memory or memorization, there'll be a few people in the group who would start- you'd feel that disapproval coming off of them. I'd say, "Oh, I must have said something wrong." For some people, they had this very negative reaction to it of saying, "Oh, shouldn't we be moving away from that in our teaching and learning?"

At the same time, people would come up to me after talks like this and say, hey, I teach Anatomy and Physiology or I teach electrical engineering or something like that, and my gosh, you came out and said it, what I have not said for all this time, I've avoided asking about, which is the memory component of teaching and learning.

There's a lot of different dynamics that go into it but at the end of the day, I recommitted to saying, okay, I'm going to find a way to frame this in a way that's appealing to people who really do care about teaching and learning but to get into some of the nuances and then lastly, to get into the concrete aspects of how we reinforce memory and even memorization sometimes in our teaching.

[00:06:46] Bonni: Now, the second half of the title of your newly developed talk is Why Memory is Important for Learning Even in the Age of Google. I don't know if the track I'm about to go on is going to resonate with you. One of the things I love to teach, I teach a Technology and Leadership class and we talk about personal knowledge mastery. One aspect of personal knowledge mastery is introducing them to the idea of digital bookmarks.

As you can imagine, digital bookmarks can be sorted, they can have tags and I get often a lot of resistance saying, if I wanted to know something, I would just search for it on Google. It's very hard for me to explain, I hopefully, I'm getting a little better at it, Michelle, but it's hard to explain, "Yes, but see, you don't always know what you want to search for." Your brain just doesn't work that way with some of this stuff.

One very personal example, I think I've given it before on the show, but we had infertility in our family for many years. There's a lot of garbage out there, Michelle, [laughs] on the internet about infertility. I don't need to revisit it.

[00:07:57] Michelle: Oh, yes.

[00:07:57] Bonni: I found those treasures and then not only did they help me both from just a personal standpoint, the grief of it and that kind of thing, but also from an informational standpoint, but then I had this top collection of things that would be helpful. Again, that's a very personal thing but within our disciplines, of course, building that network of knowledge.

Now, again, I mentioned, I don't know if this is gonna resonate, I sense, Michelle, that the next thing is then, memorization because having it tucked away in my digital bookmarking tool, there's still love a barrier for me in terms of that opportunity for that deeper learning. I'm I on the right track that this is on the way to what you're advocating?

[00:08:40] Michelle: Yes. You're bringing out yet another kind of layer that's introduced by technology and yes, that I was alluding to in my own way with that little tagline of "even in the age of Google", we need to know things, but you're talking about this other layer of, even knowing what the best sources are and the way to search is also something that is part of knowledge and learning and knowledge is knowledge management in a way in today's world.

Yes, if students are, Heaven forbid, they're researching for things that they're going to need over and over as they progress in a discipline, there's many reasons why it's not going to work. I will say that what you're describing does remind me of one intriguing line of research we're actually going- it's funny, we're going to talk about this today in one of my seminar classes. A line of research that quite provocatively and pretty convincingly showed that when we expect to be able to get back to something, like if we've saved in a particular folder, it dampens or inhibits our memory for it in the moment.

We don't, what we call, encode it as readily and this was very systematically manipulated in this series of studies where people were told some things about trivia facts. It really obscured stuff and they worked it all out and they said, okay, you can either save these in your folder and you can have them later but you have to remember the name of the folder. Just so you know, we're going to erase all this, but we will have a test at the end of this study. If you're really good at remembering and saying, okay, it was in the folder called, bird facts or something, then you didn't remember the facts themselves.

Is this a huge hefty effect that it's going to leap out in real life? Maybe not. This is not the converging lines of lots and lots of evidence, but it was a well put together study. We have to keep that in mind too, that while that may have suited your purposes, to have those bookmarks, memory for the facts themselves might have been a little bit inhibited by going through that process. As those authors also pointed out, I thought- one of the reasons I assign my students to read that article is that they say, you know what, memory has always been collective. It's always been shared.

The net is not necessarily dramatically different than knowing, hey, my dad knows the brand of paint that I should buy or there are certain things that I'm never going to remember because my husband remembers them and vice versa so may be ... it may be part of that too not just some one time thing of it's just specific to Google. What you're describing is a very deliberate way of talking about what do you need to know, at what level do you need to know it and you've really thought that through as part of your teaching.

[00:11:46] Bonni: Yes. I didn't know about that study but it doesn't surprise me at all because I can see it in my own brain. That is not necessarily a bad thing if it's not something that you need to know. Like you said, all of these is in terms of degrees. If we have decided that something is central enough to a discipline, to a skill, attempting to be taught, what have you, what then does your research tell us about the best ways to go about that?

[00:12:19] Michelle: Right. As with a lot of aspects of very mindful learner-centered teaching, it does first come down to that process of very consciously deciding, okay, what do students need to know like the back of their hand? You do not pull out a phone, thinking that through. For many of us, we may not have done that for particular courses. Even if we've taught these courses for years and years, we maybe have never reflected on that so I think it does start with a reflection component.

We're not just saying, well, I'm going to be- What I did when I was a beginning teacher, I used to say, what am I going to put on this test? I'm going to open up the glossary in the back and start picking things so be mindful about that. Now, beyond that, once we've zeroed in on okay, here's what students do need to know, for fluent, good useful practice in a discipline, how do we then make sure that we do not have to spend all of our study time and interaction time just on those things?

Tapping into the findings or core findings of applied memory research, which is this wonderful aspect of the literature that's out there. Top of the mind, retrieval practice, ask any cognitive psychologists, we will evangelize about this. It's so wonderful because this is such a success story. Again, when I think back to 10, 12, 13 years ago, if I said, hey, retrieval practice is this process where you actively pull information out of memory. It can be a quiz. It can be a formal test of some kind, but it can also be sneakier stuff like, hey, let's all have a brain dump and write down what we remember. All that's retrieval practice.

If I said that, people would stop in their tracks and say that's very counterintuitive. That can't be- but now when you say it, then more and more hands go up and say yes, I've heard of this or sometimes it's called the testing effect. We found that this is just a super accelerator to memory. These days, I know I'm always referencing this one example about online shopping and you've got your credit card. It's got the three numbers on the back and you always have to type them in.

If you always pull out your card and look at the numbers, you're not going to remember them but if you just leave that card face up for one or two times and just try to pull it out of memory and type it in, actually, you'll start to remember them a lot better. You may make a mistake or two here and there but that's what we find as well is even when students answer a question incorrectly, then if they have the opportunity to go back and review, then you have a better chance of actually picking it up.

That's one of the biggest things we can share with students, we can build into our courses, we can pick technologies that are really geared to retrieval practice, all that. That's a very big one but there are some other principles as well, ones that many skilled teachers have probably hit on intuitively in their own practices.

[00:15:26] Bonni: I'm smiling so big right now because I'm remembering back to, it was a very early episode, I got to speak with Robert Bjork who's at UCLA and runs a memory lab there. Still, I don't forget his quote, "Forgetting is the friend of learning". I recall very vividly standing up in front of hundreds of people and not remembering his name. It is rather ironic to not get the name of the memory researcher you're trying so hard, guess what, never forgotten it since.

I will say that sometimes when we're able to model this with our students because I forget stuff, you forget stuff, for sure, then they can see that, oh, wow, this actually does work. That everybody forgets stuff, but it doesn't have to be this high anxiety-producing thing. The other thing I'd love to have you share a little bit is how the interleaving and how spacing also get together and do a dance with retrieval practice. [laughs]

[00:16:32] Michelle: Love the imagery here. Well, interleaving is one that does spark so much curiosity and so much interest among those of us who are really looking to innovate with teaching and learning these days. Here's the thing though, is that it's a little tricky. People think the term interleaving, and it's a very evocative term. We think, oh, that means switching it up so 10 minutes on my English class and five minutes on my math class. Here we go back to English and now I'm going to work on my research methods class. That's technically not what interleaving really is. Now, as per the value of taking breaks or setting something aside when you hit an impasse, there's a case to be made for that.

Technically speaking, interleaving is really most relevant when we're selecting from different ways of solving a problem or a lot of the research is actually on learning to identify and classify examples of categories. That may be a little involved like, for example, a lot of the research, we'll have people study different art styles and different artists and that's a category and there's examples within the category. They're not identical, but they share some features.

Your mind and your brain are doing some computations that are still not totally well understood when you're learning to do that. When I see a new painting and say, okay, how if I have to slot this in a style and an artist, what I would do. Biological categories, bird examples or some neat research that's on? All right, what general bird? Specifically what bird is it? If you've learned on this set of examples, can I show you a new example and can you do that? That's not everything we're doing in teaching but it is occasionally what people are doing and so here's where interleaving comes in.

People do tend to retain more and to pick up this learning more quickly when they study in this interleave fashion, where maybe I'm going to study some paintings from this artist and a few from that artist and I'm going to toggle back over to this kind. Instead of saying, okay, I'm going to sit down with all the impressionists and I'm going to spend an hour on them and then switch gears. That wouldn't be that big a deal, except that that's the way the textbooks are organized and that also tends to give us what a lot of ineffective study techniques do, which is a false sense of fluency or security.

After I've seen the 20th impressionist, I go like I got it, but maybe I don't got it. If I saw that counter juxtaposed against a completely different painting, it would put a little bit more taxing for me to go back and figure that out. The other big thing is that interleaving is still a scientific work in progress. There's research goes back quite a bit. We're not talking about just one or two studies but we're also not talking about this big, deep well of research that we have, for example, with retrieval practice.

That's something I think is also something that I think you know if this is the learning problem, the categories of different ways of solving problems, you know that if that applies to you. If so, yes, take a look at some of the interleaving stuff and see if that would affect how you say set up a homework set or something like that.

[00:20:01] Bonni: What I've tended to do in the past is I'll often create flashcards, maybe using a tool like Quizlet, just as an example, there are a lot of tools out there, but then start with, this is where we just looked at ethical thinkers and frameworks and then we're going to go into this new area, but I keep this in the set. I keep it in the deck and I bring it forward.

A lot of these tools are actually designed to already do this for us, where if I've had a lot of success on one of the cards, I can mark it as, "I got it" or it can mark it for me as, "I got it" and I might see it less frequently and that kind of thing. Should I be thinking more carefully about what goes in that ever-growing deck in the sense of- Because I think I might be- I appreciate what you said about it's a growing area. There's no absolute right or absolute wrong, but I think I might be getting bird examples in there with art examples. Is there something I should be thinking about in terms of that as I help to try to support students in this way?

[00:21:05] Michelle: Yes. This is one of those inside baseball issues but it is a very practical one. Just simply, do you drop an example out of a deck if you've answered it correctly once? There is a school of thought that says, actually, no. Even if you've answered a question or a type of question correctly once, twice or something like that, that there's still benefit to the retrieval practice. I might balance it too. If it's key, if it's an absolute core, that might be good to stay in that deck till the last day of the course.

I think, for example, in psychology with research methods or something like that, P-values, that's a statistical decision. This decision but it's not a complicated thing to learn, but you have to know these and students forget. That it is a bedrock thing that maybe should be in there all the time. There are probably other terms I might want to drop out if they're a lower priority. Other people will say, well, from an efficiency standpoint it makes sense to concentrate more on what you miss and keep those in the deck even if the deck is more of a figurative thing.

I think as students get that metacognitive, savvy and insight developing, that's something that they're probably naturally going to do as a function of quizzes and tests. That's yet another wonderful thing the tests do, is we can't just gravitate unconsciously towards the stuff we already got, which I always did that ... when I was a college student. It's like, "I like this part. I'm going to stay on this. I'll just pretend that this isn't over here." Tests, really, they lay it on the line for you. You look at it and go, "Yes, I got that one wrong again." There's a real balance there.

[00:22:55] Bonni: I like your example of the teaching a research methods class. You mentioned the P-value. I don't think that you're saying keep the quantitative stuff separate from the qualitative stuff because how it's going to show up to me in real life as a researcher, I might be doing a mixed method. Because, again, I think I might be caught up on the categories of stuff, okay to mixed categories, yes?

[00:23:19] Michelle: Yes, mixing categories during the study phase or maybe a way to make this intuitive for some, say, in STEM disciplines. Ecuador's working with a lot of faculty in one of our first-year programs. I would hear some version of this from different STEM faculties. They say, well, students come into my course, a chemistry course, and they're like, they've got all this math coursework under their belts. They've got the pre reqs. They've got good grades. We know that they can do the mechanics of the problem. The issue is when I haven't set the problem up for them and said, okay, it's this kind of problem. That's where they get stuck. They'll be so frustrated, like, why? What is it with today's students?

Well, that's a practice issue. You can just say, well, that is a skill unto itself, identifying and setting up the problem. We see versions of that. I saw it at research methods too, just like, first, you got to figure out how to break this down and identify the parts of it or figure out what statistical test is appropriate, then you can go run and do the test. Well, if students are never in that position of, I got to set it up for myself and it's messy, and it's frustrating, and I just want to get to that solution part, if they're not sitting in that stage, well, what do you know? Like anything else, we don't practice it, it doesn't happen.

[00:24:46] Bonni: That's such a good example too because we wouldn't want to be giving the impression that retrieval practice is only practiced in something akin to flashcards, that there's different ways. It's that practice part or what is it that you're trying to practice? Anyway, I know you had something to share about spacing as well and now that we've touched on these other dance partners for retrieval practice.

[00:25:10] Michelle: Spacing is another one of these that I think a lot of students hit on for themselves, faculty hit on for themselves, although they may not really have this full grasp of why it works. It works for various reasons. Now, spacing is sometimes called distributed practice. That's a really descriptive term. It's the anti-cramming principle that if you recurs or retrieve or study something in small, small bites more distributed over as much time as you can, that each one of those bites will deliver more than it would if it were aggregated into one big mass.

We tell students, ... they may not really understand that it's not just about an organizational issue, it's also a memory issue and they're getting more out of the time. You've described Quizlets, for example. Those are great because you can do those while you're waiting for your Zoom meeting to start. I think, as students, they can start to develop some of these neat techniques for themselves and practices for themselves. They also hit on, "Well, hey, I can fit this in here and fit that in there."

If we're talking about academic work where I'm really getting involved in producing something, I'm writing a paper, I'm setting up a study, I'm conducting analyses, well, there, the takeaway is not memory. I'm not saying, "Work on your paper for 10 minutes and then put it in." There are times when you do need momentum and you do need that, I guess, what Cal Newport calls the Deep Work. We're just talking about, let's establish, get those basic facts down in this course. That's where spacing is absolutely your friend.

[00:26:57] Bonni: We've talked about different ways of enhancing our memory. I know a big part of your work then is that that's not where it's over. It's not an either/or. It's not that I either focus on memorization or deep learning. Could you talk about the connection between memorization and that deeper learning?

[00:27:18] Michelle: Right. Or another metaphor is higher learning. I think it's wonderful that Bloom's taxonomy, that now-famous pyramid, it's set up like a pyramid for a reason, there's a hierarchy here and that's fine. It's great that we all know about Bloom, and we're thinking about it, but it does, I think quite naturally, we want to shoot straight to the top. We want to hit the good stuff. I want my students to be doing critical thinking and analyzing and finding different ways to interpret or critique articles that they read and setting up their own studies someday. I want that. I want that really badly.

I do think that many of us have absorbed, I know absorbed early on, a real false dichotomy. Well, do you want this lame thing where they can tell you where Sigmund Freud was born, or do you want this thing where they can critique his theory? This is a timely example. We actually touched on this a week or two ago in one of my Introduction to Psychology courses. Well, if I say, hey, I want you to be able to look at Sigmund Freud's psychodynamic theory of the mind and look at how that really reflects his culture and it's not universal, you need to know where he was born.

I had a student I always talk about from Austria and blah, blah, and they'd chat, go, "Wait a minute, he was from Austria? What? I didn't know that." These things do naturally go together. I would invite all of your listeners to, again, reflect, sit back and think, "Where are those touchpoints between things that I really just know, again, not without googling it, and things that have the complements, these higher things that I really want students to know?" There's that kind of really intuitive way we can come at this and start to break down that dichotomy and see how these complement each other.

There's also, again, more emerging research out there. A lot of it is actually anchored in looking at retrieval practice, but I guess the bottom line of some of these newer studies is that they show when students are doing study practices that are more efficient for memory, like retrieval practice instead of just passively review. When they're doing that, you see a quicker shift towards some aspects of higher thinking that we can actually pin down. Things like being able to draw inferences when you're given a set of facts saying, okay, you're looking at this, therefore, this.

I want to caution people here that there's not really a study or a line of research emerging about thinking skills in general. In fact, I'm not sure that that sort of global, I can think about anything ability exists. I'm just going to say that. In these very specific things that we can pin down, we can measure, that's pretty exciting. Probably what's going on is I'm establishing this more strongly, I've got down past these facts about Freud or I know about the Impressionists. Now I can think about them more. There's also that argument to be made.

[00:30:31] Bonni: I experimented a bit with having students memorize the Seven Habits of Highly Effective People. That's from a book by Stephen Covey from long ago. The reason why I had them do it- and you talked about this, Michelle, the importance of reflecting on what's important, it wasn't important. I never gave them a test that was a graded test that they had to show me that skill, but we would do regular practice. You can do that pretty quick within our class sessions, but the reason why I did it was because, otherwise, I was not sure that it would be enough in their mind to be able to look in for the ways that these habits did or did not show up in their life.

Because a lot of what was graded, what was assessed, one of them is, be proactive. Being able to see examples of that showing up in their lives and in the lives of other people that they know, it's really hard to do that kind of reflective work, and again, I'm speaking not as a researcher, this is very anecdotal, but if they're not already in your mind to be thinking about.

Since I don't have the opportunity to send them all little messages to their phones or- those studies where they're like, "How are you feeling right now?" That wasn't set up for this given class, it seemed like that was a way from my understanding of how to help them have the deeper reflection. I don't know if that sits well with this example. I just thought I'd throw that out there and see what you think.

[00:32:05] Michelle: Well, among other things, I think you hit on other than retrieval practice, one of the powerful things that we do do to get students to really, really remember. Stephen Covey's principles, five years later, 10 years later, they're going to know that and understand them. You asked them to link it to their own lives. I think you're doing both. Here, there's that dance again. We're doing the tango, and here's, "Okay, I remember what the principles are. Here's what they look like. Here's why I care about them."

Both of those are going to carry each other forward. We call it self-reference effect, hugely powerful. Who couldn't stand to bring this into their classroom more to say, "Okay, you give me three examples of whether this has ever applied to you and if not, let's talk about that too." You are getting those, down-pad. I think a really conscious teacher too, they'd it's not just enough to say, "Okay, now my exam's list of principles." Maybe it has that, but it's both-and, and we also want to look at the application of it.

My money would be on the active learning that your students, years from now, will have that deeper understanding and also be able to characterize it. Even if they don't remember all seven, they can probably get a few of them and they can characterize that group in general. That's what we want.

[00:33:36] Bonni: The reflection is just so key, and we also need to be doing it with each other, with colleagues. I say colleagues specific to our universities where we work, but also collectively in our disciplines, to be having an inter-discipline- Is there a place where this kind of reflection doesn't bode well? Really so crucial to be thinking and talking about those things. That's, I think, one of the ways that your research in this area is just so hopeful because we can get so many different examples that can both challenge us and inspire us in these areas.

Speaking of which, I guess before we get to the recommendations segment, I'd love to hear from you if there's anything that's really inspiring you. You've already shared a number of examples in this episode, but is there anything that I didn't ask you about where you think, "Wow, this practice is inspiring me or this person is inspiring me or here's some of the thinking I'm doing in these areas that's really creating a spark" in your own work?

[00:34:38] Michelle: The faculty who are so patient with my follow-ups that I do get to work with now remotely, that is a big inspiration. Each group that I get to work with bootstraps me up to bring more insights to the next group and so on. We've really done a good job I think in the professional development area and in higher learning in general to make the most of these remote events. I would say to all the folks who've sat with me on many a Zoom conference or a workshop that we did in Teams and you responded to the key questions that I asked folks are, "Okay, you tell me, what are the key things in your discipline?"

It's so amazing that every single time, well, not as frequently as I used to, but I'll get to talk to somebody in a discipline that I'm not familiar with. I teach Civics and Government or I teach Air Conditioning Repair. There's always a first. That ties in as well to my great love of and advocacy for whenever we can, working across disciplines and across specialization. That's a really, really big one.

[00:35:55] Bonni: I don't know if you've seen this but I can't imagine that you wouldn't have. So much of it prior to the pandemic was, "Oh, you could never do that online." Or technology would never provide those affordances. While I do not want to dismiss the devastation of the pandemic and I always have to be very careful when I say this because it's had awful effects all around the world, and so I never want to be a silver lining kind of person, that's not at all.

In this very bad time, in this very time of devastation, there are still those people, though, that conversation feels like it's shifted to me to "How could I do this?" Those have been some really interesting conversations, and so much with our colleagues and faculty.

[00:36:45] Michelle: Yes, I agree too. The silver lining narrative is going to be one that we are going to need to counter that for a long time going forward. Absolutely. With a lot of online learning, with our online interactions, it's also sometimes not, oh, here's this completely other thing that we never could do before, now we can. How do we hang on to that? Now we go back, and many people say, "After I taught online, I picked up things I took in my face to face classrooms." I think that you're absolutely right. There's things that we can take. Instead of just a straight replica, making everything just like it was face to face, sometimes you can find hidden gems.

[00:37:37] Bonni: I've got a perfect segue coming up for the recommendations segment, but I can't quite get to it until I start by thanking today's sponsor, and that is TextExpander. If you've been listening for a while, you know that they are the longest-running sponsor and are a big part of my productivity system. In fact, I just got my annual 2020 report of how much time I saved with it. Let's just say it confirmed, I didn't need it to confirm, it confirmed that it really does save a lot of time.

Also, I noticed that it sends out, not just how much time you save but your common snippets, what they call snippets where you have these easy to remember letters or numbers or whatever it is. For me it's the letter Z, often, followed by a series of letters. Z-E-S-I-G is going to get my electronic signature, for example. It showed me all the ways in which it helps me be more consistent in terms of my writing and correcting things as I'm going. T-H-E is often spelled apparently T-E-H by me as I'm typing. It's just a wonderful tool.

It works across a number of platforms, including Windows and Mac and also on the iOS operating system, so your iPhone and any tablet, if you've got an iPad, for example. It just helps us save time, be productive and it's really easy to set up and get started. You can have it make suggestions to you. It can notice when you are repetitively typing the same thing. I've turned that setting off. Although, maybe I should turn it back on. I find that, if I put my mind to it, I can find really easy ways to save a little bit of time on something simple.

It could be something a little bit more complex. It's not hard to set up but I've got the show notes in there. I just type T-I-H-E, as in teaching in higher ed, S-N as in show notes, and it pops up and says, "Who's the episode with, and when's it supposed to air, and what other information do you have?" It just saves that time of inputting the information so I can spend a lot more time in preparing for the conversations I'll have with the guests and also in putting together the resources for the show.

Once again, I'd like to thank TextExpander for sponsoring today. If you head over to textexpander.com/podcast, you can get 20% off your first year. You also can just try it out for a while as well. Thanks once again to TextExpander for being such an integral part of my computing life and productivity. Thanks for supporting the show in this way.

Speaking of finding hidden gems, I've got one for you. It's time for the recommendations segment, Michelle. I heard about this television show so many different places, and I just resisted it and I resisted it because the premise is that it is based no something about sports, and I'm not a big sports person, so I thought that's not the show for me. I finally succumbed to the temptation and loved it and binged watched it. It's Ted Lasso, which is available on the Apple TV Plus network.

It's an American sitcom television series. I'm reading now from their show description by Bill Lawrence, Jason Sudeikis, and Joe Kelly and Brendan Hunt based on a character of that same name, Ted Lasso, that Sudeikis first portrayed in a series of promos for NBC Sports coverage of the Premier League. The premise of it is that a guy is a coach in the United States and then he ends up being selected to be a coach in a totally different sport that he doesn't know how to coach. There are so many great leadership lessons in this show. It is so uplifting.

It's funny and it's heart-wrenching. It is just a delight, but it also is very difficult to describe. Well, in fact, if I just read that description to myself, I'd be like, "There's plenty of other things out there that I'd really want to watch." I just really recommend it. Again, it's one of those things I know not everybody has subscriptions to all these services, but if you happen to have a subscription already, you can't miss it. It's just so, so very good. Michelle, I'm going to pass it over to you for your recommendations.

[00:41:51] Michelle: Oh my goodness. Well, as a psychologist, I would be remiss if I did not tell people that in as much as people are able, exercise, movement, this is just absolutely the thing to keep doing. It's close to a magic remedy for just a cognitive, staying sharp cognitively, mood, memory, that included. There's nothing else like it. Sorry, guys, but brain games don't do it. Crossword puzzle are fun, but it doesn't really "exercise" your brain, but that does. I'll say that in my household, it's mostly teenagers and young adults. We do enjoy the Les Mills OnDemand exercise subscription service.

It's streaming of a variety of different programs. I can usually get somebody in my house to agree to get up a session of yoga Pilates fusion or cardio, weights or something like that. We really enjoy it. It's a lot of the same classes that I was taking at the local gym when that was open, so it's really nice to have that carry over into, yes, an online format. It's form New Zealand. It's a lovely New Zealand company, so it's very international. There's every delightful version of English that's out there. The New Zealand accents are always a kick, so we love that a lot. That's a really, really big one that I would put out there for people.

Brain games may not help you, but some games are just for fun. I think that's okay. I am not a gamer. I have never really liked games, board games, video games, you name it, but one finally got me, SpellTower. I know I have a limit on a phone playing SpellTower. It's a cross between Tetris and Boggle and Chess. It appeals to my very, very word and verbally oriented self.

[00:44:03] Bonni: These sound spectacular. [laughs] They sound just wonderful. I haven't heard any of these. I've never heard of this exercise thing you speak of. Oh my gosh. I tell you what is keeping me going, it does make such a difference and so, thank you so much for joining me today for the episode and for these wonderful recommendations. It was so great to reconnect. What I love about us ending this episode, Michelle, is I know you'll be back because [laughs] you always do so much good stuff.

I now you'll have a book coming out at some point, as of this recording, we don't know exactly when, but I'm just looking forward to our future conversations and just love getting to continue learning from you all these years.

[00:44:46] Michelle: You as well. Thank you for all that you're doing to help people keep growing and developing and doing everything we can for our students.

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[00:45:00] Bonni: Thanks so much for Michelle Miller for joining me on today's episode of Teaching in Higher Ed. It was great to reconnect and be inspired by your work in memory. Thanks to all of you for listening to this episode of Teaching in Higher Ed. I'd like to encourage you to subscribe to our newly rethought, redone, reconceived weekly updates. They are now weekly. If you have yet to subscribe, head on over to teachinginhighered.com/subscribe. What that will get you is highlights of the most recent episode along with some related episodes and some resources, quotable words, and such. Thanks so much for listening and I'll see you next time on Teaching In Higher Ed.

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[00:46:00] [END OF AUDIO] The transcript of this episode has been made possible through a financial contribution by the Association of College and University Educators (ACUE). ACUE is on a mission to ensure student success through quality instruction. In partnership with institutions of higher education nationwide, ACUE supports and credentials faculty members in the use of evidence-based teaching practices that drive student engagement, retention, and learning. Teaching in Higher Ed transcripts are created using a combination of an automated transcription service and human beings. This text likely will not represent the precise, word-for-word conversation that was had. The accuracy of the transcripts will vary. The authoritative record of the Teaching in Higher Ed podcasts is contained in the audio file.

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You Must Remember This, with Michelle M. Miller - Teaching in Higher Ed

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Michelle M. Miller discusses why memory is important for learning - even in the age of Google on episode 348 of the Teaching in Higher Ed podcast