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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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Should mobile devices be encouraged in class? Trinity College, CC BY-NC-ND

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

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

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

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

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

Why attention matters for learning

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

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

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

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

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

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

What technology does to the ability to pay attention

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

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

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

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

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

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

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

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

College students and technology

There are other pitfalls to consider.

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

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

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

Evidence suggests that multitasking - such as tweeting in class - reduces learning, or at the very least makes it take longer.

Even sitting next to a classmate surfing the web on his or her own laptop hampers learning.

In sum, despite that appearance of being fused to their devices, today's students aren't immune to the distraction those devices cause. And they don't necessarily want technology in every corner of their educational lives.

How college teachers can help

College teachers need to include lots of tech support for online assignments and other kinds of educational technologies, because even students who have grown up with computers still get stuck when using them in new contexts.

Teachers must also avoid the trap of adding tech to a class just because they assume digital native students want it. Educational technology can be highly effective, but only when it is tightly coupled to the teacher's goals.

Even better, teachers can help students understand for themselves how attention works - knowledge that everyone ought to have in today's distracting era. Without vilifying technology, teachers can work to raise students' awareness about how attention impacts learning more than we may realize, no matter what our age.

The effects of technology on cognition are intriguing, but they don't justify teaching millennials as if they were a new species. Teachers need to think twice about tolerating devices in class, except as part of structured activities that link to the lesson at hand.

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

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From the look of it, the millennials appear to be very comfortable with technology. But are they as immune to the effects of digital distraction as some might assume - especially in the classroom?

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Apostolos Koutropoulos
University of Massachusetts
Boston, MA 02125 USA
a.koutropoulos@umb.edu

This year marks ten years from the first introduction to the term "Digital Natives," coined originally by Marc Prensky in two seminal articles that established the traits of the digital native (2001a, 2001b). Prensky is by no means the first person to try and identity a new, distinct, generation of humans, and digital natives isn't the only term proposed to describe them. Other common terms come from Oblinger & Oblinger (2005) and Tapscott (1997) who use the term net-generation, and Strauss & Howe (2000) use the term Millennials to describe this same generation of students. The dates do vary from author to author, but not by much; and the characteristics attributed to this new generation blend easily from author to author because a lot of the characteristics are predicated on access and utilization of technology and the Internet. This naming fetish didn't stop at these three terms, and these terms are used interchangeably in every day discussions, but for the purposes of this article, this article will use the term "digital native."

The emergence of the classification of this new generation lead to many articles, blog posts, columns, books and videos on educating this generation and taping into these learners' new learning styles (Dede, 2005). Popular viral videos were produced showing statistics of new technology usage (Socialnomics, 2009) and emotional pleas from self-professed young digital natives that would like to see change in the institutions that educate them and cater to their unique digital needs and learning styles (VALATV, 2010; Nesbitt, 2007) What's amazing about this term, and all that it implies, is the amazing speed with which it took hold in circles broader than the educational circle, and how it became part of our "common sense" without having been tested much in every day practice. The digital native became a rallying cry for change in education, (expensive) technological infusion at all levels of education, and broad-changes in institutions that are providing learning opportunities and environments to these digital natives. This article aims to critically examine the underlying digital native theory, review recent studies inquiring about the existence of digital natives, and to examine the effects that this "movement" has had on the learning professions.

When examining the key characteristics of digital natives I start by examining the works of Prensky (2001a, 2001b, 2003, 2006a, 2006b, 2010) for two reasons. He is the author most often quoted or referred to when discussing the characteristics and preferences of this generation in both peer reviewed and non-peer reviewed articles; especially in the "early literature" on digital natives between 2001 and 2006. He is also the person who coined the term "digital native" in his early writings. Other authors, such as Dede (2005), Oblinger (2005), Oblinger & Oblinger (2005), Howe & Strauss (2000), Tapscott (1999) and Frand (2000) also get referenced, although not with the same frequency as Prensky's writings. Thus it makes sense to examine Presky's arguments and positions first.

Prensky's Digital Native Canon

In his first article on digital natives (2001a) Prensky writes about a singularity, an event that fundamentally changed things, our students in fact, so that the current educational system is ill prepared for this new generation of learner. Prensky supports his argument by providing some facts and figures, such as students spending fewer than 5,000 hours of their lives reading (assuming that reading refers to books only), but over 10,000 playing video games, 20,000 watching television, and he goes on to give us more similar statistics about Instant messages (IMs) sent, talking on (digital) cellphones and sending email. It is clear that in Prensky's writings, as well as other digital native author's writings, that they expect that these statistics hold true across the board, regardless of your socioeconomic background and your country of origin. What's clear is that the context isn't really considered. Who is spending all this time playing video games? Prensky owns a video game company so it may be that what he sees every day is what he thinks of the norm, but that doesn't mean that this norm is universal reality.

Other overgeneralizations put forth by authors like Prensky, is that the digital natives prefer images over text, they prefer games over "serious work," they function best when networked, digital natives can't pay attention (or they choose not to!), and finally digital natives have skills, with digital technologies, that they've perfected. There are a number of issues with these overgeneralizations. First, and foremost, what is the context? What is the Socioeconomic Status (SES) of these digital natives that have access to the technology that they've become skilled masters of? Do those general skills transfer over to the academic side? Could I seamlessly take my skill of posting facebook updates and apply this to an academic context without the help of a more experienced "digital immigrant"? Can Prensky's digital immigrants just pay attention even when they are bored? Of course not! Digital immigrants doodled, dozed off and day dreamt when they were bored, digital natives do the same. Being able to focus on a task has nothing to do with exposure to technology. Finally, I would say, that most people prefer to do fun things rather than something that they perceive of as work.

These figures and overgeneralizations have oft been repeated by followers of the digital native message, without much self-reflection or critique. They are taken as-is, as common sense, and as universal. Early on, when some suggested that the context does matter and that these are assumptions aren't universal (VanSlyke, 2003), Presky's (2003) rebutal, which included a lot of technological buzz words and no hint of pedagogy, said that these online services are a few of the things that kids are using online these days and he expects that his observations hold true in the US, Japan, Korean and much of the rest of the world. Prensky doesn't provide facts or empirical evidence, just suppositions. When Prensky writes about his preferred method of teaching (2001a) he writes that he prefers to invent video games, but he never considers that this may not be the most appropriate method of instruction, and that it might not be the learner's preferred method for instruction. Thus in the same article he talks about the needs of the learner, while at the same time ignoring the needs of learners by imposing his own preferred method of teaching.

Prensky's technological determinism culminates in a biological determinism in part 2 of his introduction to the concept of the digital native (2001b). Prensky argues that the brain's neuroplasticity makes it so that the brain adapts to the environment that it is in, so in a technology-infused environment the brain will adapt to better use the tools that are available in that environment. While this may be true, there are two things that Prensky does not take into account. The first is that as human beings our brain is continuously rewiring itself throughout our lives. We don't fossilize at a specific state of our lives, but we learn to use the tools that are available to us, thus digital natives should also exploit that physical ability to learn to function in environments that don't necessarily have the tools that they are used to. The second thing that Prensky never questions, in either article, is the need to impose radical change on our educational system. This, taken together with the, unknown at the time, numbers of technology use within the digital native population, means that we weren't really talking about pedagogy, and what's really good for the learners, but rather, perhaps, change for change's sake, or the technological equivalent of "throwing money at the educational problem."

Addenda and Extensions to the Canon

Other digital native evangelist authors have their own two cents to add into the mix of characteristics that defines this group of supposedly tech-savvy students. Oblinger (2005) for instance portrays a vision of technological utopia, something that supposedly exists today, where students are proactively using their iPods to learn, snap photos everywhere they go and use these tools for impromptu study meet-ups. Students don't wait for the professor to answer their question but they Google it for themselves and find the answer; however this isn't always the truth. The fact that one can mechanically go through the motions of searching for someone on Google doesn't mean that they possess the critical literacy and information literacy required to determine which results are quality search results. Even if they knew which results were quality results it does not imply that these students can then process what those results mean and to learn the answer to a question that they had; this is something that Oblinger glosses over.

One of Frand's (2000) contributions to what makes a digital native a digital native is what he terms "Nintendo over logic," which claims that this generation doesn't read manuals and prefers a trial and error approach, as one might find in a video game. Prensky (2001a) and others also hit upon this note as an innovation of digital natives, and an "accent" (or hinderance) that digital immigrants have because they rely on manuals. This notion of trial and error über alles as a innovation of digital natives, and the non-reliance on manuals is false on two grounds. First, experiential learning, another name for learning by trial and error, goes back at least to the early 1900s with the work of Piaget. Presky's later proposals (2006a, 2006b; 2010) for using peer groups, allowing students to pursue their passions, and essentially going from a s age on the stage to a guide on the side aren't new, but they go back to Piaget (Singer & Revenson, 1996), Vygotsky (1978) and even Socrates (Karasmanis, 2002), just to name a few. If Piaget, Vygotsky and Socrates thought of these notions, this means that these traits aren't inherent to a population who grew up in a digital age, but rather these are traits inherent in humans as a whole, and everything else is just a tool that we can utilize.

Another trait that is ascribed to digital natives is that they are multitaskers, moreover they are efficient at it, and it is technology that encourages this multitasking. Dede (2005) gives us an example of his daughter doing her homework while at the same time listening to music, emailing and IMing friends and surfing the net. Dede isn't the only one who provides us with anecdotes like this one, and as a matter of fact there are many anecdotes like this in both peer-reviewed and non-peer reviewed publications, it's part of what passes as "common sense." The problem is that this type of multitasking wasn't taken to task. Are these tasks performed at the same time, or are they done serially, in smaller distinct segments? Has the efficiency of multitasking been proven? And how much brainpower are we giving to each individual task? Is the music something we pay attention to or is it the equivalent of white noise? Does the multitasker pay the same attention to each individual IM window or does he let some of them acquiesce?

Finally, tying in with multitasking, and "Nintendo over Logic", we have a depiction of how digital natives learn. According to Tapscott (1999) digital natives are non-sequential with their use of information, going back and forth between programs and sources and their learning style is an outgrowth of these ingrained habits of seeking and retrieving information from the Internet. This marks a striking contrast to previous generation of students, who tend to acquire info more passively from authority figures (Tapscott as quoted in Barnes, Marateo & Ferris, 2007). Perhaps one of the bigger claims made is that this generation (i.e. digital natives) exists across the world and across socio-economic conditions, not just in advanced economies (Tapscott as cited in Jones & Healing, 2010).

Just as with the number of email messages sent and read, the number of hours spent on watching TV and playing video games that Prensky (2001a) gives us, the importance is not in the metrics themselves, but rather the details of who provided this information, in what context, and what these numbers mean in the broader context. Knowing that one can multitask isn't new information, we've always been able to walk and chew gum at the same time, to borrow from the old saying, but how much attention are we paying to each task and why. The devil is in the details and unfortunately the early literature on digital natives that built upon the work of Presky, Oblinger, Tapscott, Dede and Frand lacked that fine attention to detail; they seemed to rework the same old assumptions, and fit their data within the Weltsaschauung of the digital native proponents.

Straight from the Digital Natives

Some information about digital natives comes from digital natives themselves, not just from members of others generations trying to describe digital natives. Two prime examples, from written sources, are Roberts (2005) and Windham (2005) who provide us with information about what it means to be a digital native from a technological and a social perspective. Roberts writes that he is " a member of the [digital natives] Generation. The Internet and related technologies have had a major influence on [his] generation's culture and development. Many, if not most, [digital native] students have never known a world without computers, the World Wide Web, highly interactive video games, and cellular phones."

Roberts continues by providing views of a supposed representative sample of digital native students and what technology means to them. Among the responses are "Reformatting my computer system and installing cutting-edge software that allows me to do what I want, when I want, without restrictions, viruses, and the rules of Bill Gates, " and "The ability to adapt and configure an already established program to [something that] benefits me daily." Roberts concludes with:

"The feedback from this select set of [digital native] students does contain some good news. It indicates that the [digital native's] general expectations regarding leading-edge technology have not fully impacted its expectations about the use of technology to support learning. This may signal a failure in the responsiveness of colleges and universities in terms of keeping pace with the rapidly changing technological landscape. However, it may also indicate that the opportunity to catch up with the [digital native] has not been lost."

There are several issues with what Roberts writes. An implicit assumption is made that his own lived experiences are the same across the lot of digital natives, something which isn't true. Up until recently access to video games, cellular phones and the Internet were costly enough to imply a certain level of affluence; as such these would not be the lived experiences of most members of this generation. Related to this is this assumed technological know how required to format, reinstall and customize one's computer (to the extent described); again this isn't the case with all digital natives. Finally, the digital native is viewed from a position of superiority, giving non-natives a chance to catch up with them, and the digital native's low expectations regarding academic technology must be a result of the non-native's failure to adapt quickly enough.

From a social perspective on digital natives we look to Windham (2005) who writes about encounters with a professor that one, reading her article, would characterize as a Luddite. While it is true that this particular professor could incorporate some newer ways of communication (like email) this particular digital native comes off as highly disrespectful to people who don't share her social conventions, relegating these non-digital natives into the category of "relics." This particular professor represented for her "a world [she] could scarcely remember-a world before driving directions on MapQuest, book buying on Amazon.com, and making plans on Instant Messenger." While this may be true it is hardly a reason to assume that all of the world operates in this same fashion, and that it is the only way of being.

Windham writes that members of the digital native generation are consumed by the notion of achievement, they join clubs, participate in community service and are engaged. Furthermore this generation has not seen corruption of power or felt the fear of the Cold War. It is argued that it is this type of social change that has brought on the technological adeptness in digital natives. Digital natives keep their addresses and plans in their PDAs, they listen to their music on MP3 players, record one television program while viewing another, and browse library databases instead of going to the library. These are viewed as digital native innovations over previous generations; however it is previous generations that brought these innovations to this current generation, the digital natives, not the other way around.

Finally, digital natives are described as striving "to stay ahead of the technology curve in ways that often exhaust older generations," and to achieve this they "rarely pick up the instruction pack to learn programming or a technique. Instead, spurred by our youthful exploration of the Internet, we tend to learn things ourselves, to experiment with new technology until we get it right, and to build by touch rather than tutorial" (Windham, 2005). From a surface view, this does corresponds to what other digital native evangelists claim, like Frand's (2000) "Nintendo over logic," but something is amiss here. Digital Natives may indeed start without looking at a manual, but when what they are using is not intuitive, they either get the manual, as is exemplified by the great numbers of computer game walkthroughs online; they will give up, as we shall see digital natives aren't that great at adapting when compared to older students; or they stick to what they know, which means not experimenting and goes counter the claims of digital native evangelists.

Demographics Matter

So, what does the research on digital natives tell us? The picture is not as black and white as digital native evangelists, would have us think. There are many variables that go into creating the stereotypical digital native. Location is important, as well as socioeconomic status. How much one uses a certain tool or technology, and what they use it for, are also factors; and how well those skills and behaviors transfer over into educational domains is important. After all, one can't advocate for radical change in the education system based on skills and behaviors that don't carry over.

VanSlyke (2003) had originally questioned the global reach of the digital native, and Prensky, in a rebutal, disagreed with him stating that he expected children in much of the rest of the world to exhibit the behaviors of the digital native (2003). Research, however, has shown that the location does matter. In the US (Smith & Caruso, 2010) we see different levels of computer and web technology usage among the same demographic of digital natives in Australia (Kennedy, et al., 2010; Margaryan & Littlejohn, 2008) and than those in the UK (Stoerger, 2009). In South Africa, as well, we see that only 26% of the population might be described as having grown up digital (Brown & Czerniewicz, 2010).

We also see that the semantics of the words "native" and "immigrant" make a difference. As Brown & Czerniewicz (2010) inform us, in the South African context the words "native" and "immigrant" have the opposite meaning from what Prensky (2001a) describes within his North American frame of reference. In South Africa, due to its colonial and apartheid past, the immigrant, the colonizer, is seen as the forward thinker, while the native is seen as the one who is backward. Digital native, as a term, according to many, including Brown & Czerniwicz, is an "othering" concept. It sets up a binary black and white, and those who fall into one category, whatever the connotation and the qualities implied, cannot exhibit characteristics of the other category that they are not members of.

This is problematic because there is an implied power relation, and superiority, attached to those particular sets of skills and dispositions of the digital native. In turn, this digital divide has spurred a Moral Panic, calling for radical change in education where arguments are articulated in dramatic language, with no empirical evidence or theoretical foundations, based only on "common sense" and personal anecdotes (Bennett & Maton, 2010). Anyone who resists or questions these calls radical change is said to be out of touch, lazy, or just dismissed as not having legitimate concerns (Jones & Healing, 2010).

Another major factor in this discussion are socioeconomic factors. Most of these studies poll students who are in college. College students don't represent whole populations because they tend to be from a segment of the population that has the financial capacity to afford to be able to go to college (Bradley, et al., 2008 in Bennett & Maton, 2010). As Brown & Czerniewicz (2010) framed it: it's not about a generation but an elite. Brown & Czerniewicz found that information and communication technology (ICT) use was along socioeconomic lines. Twenty-two percent of the students lacked both experience and opportunity to use ICT, had less than 4 years of experience and had no ICT access off-campus.

As Broos & Roe (2006) indicate, socioeconomic factors, as well as other factors such as race, gender and educational background, do play a role in how and how much people use technology. Those with higher incomes do tend to use technology and the Internet more often than those in middle and lower income categories. One's anticipated job prospects, in the Broos & Roe study, were also strong indicators as to whether one would use ICT or not. Finally, another interesting point to consider are the demographics of digital natives. In a recent US study by the Pew Internet and American Life Project (Rainie, 2011), most digital natives are white (61%) and live in the suburbs (54%). It is hard to believe that an American suburban white person will have the same life experiences as other people who are not in that same demographic group.

Access to, Utilization, and Quality of Engagement

With all the focus on having a generation "bathed in bits" (Tapscott, 1999) access to technologies and utilization of these technologies in both quality and quantity should be something that matters when we measure technological engagement of these digital natives. Access and utilization should also be something that ought to be scrutinized and carefully analyzed. First, keeping an eye toward the USA, we see that contributional usage by members of the digital native generation on social sites is quite low. Only 36% of digital native students contribute to blogs, only 40% contribute to wikis, and only 42% contribute to video sites. Social games and social bookmarking sites are only used by 25% of these digital natives. Fewer that 20% of the students said that they used course lecture podcasts or videos (Smith & Caruso, 2010). Similar results were also found by the Corrin, Bennett & Lockyer in the Australian academic context (2010) and the Pew Internet Internet and American Life Project in the broader US context (Fox & Madden, 2006; Jones & Fox, 2009; Zickuhr, 2010; Rainie, 2011).

Across the pond in England, Jones & Healing (2010) report that over 80% of first year students reported a "slight confidence" and "basic skills" with presentation software and online library resources - sources that they were familiar with. For sources that they were not familiar with, like blogs and wikis, these students reported that they didn't not feel confident in using them; this mirror's Kvavik's findings (2005) in the US. The Jones & Healing study reports that only a minority of students felt like it was important to them to share and upload content.

In Australia a study found that only 15% of the digital natives were "power users" and 45% were rudimentary technology users (Kennedy, et al., 2010). In a related study, more than 70% of Australian first year students never kept a blog, more than 80% had never produced a podcast and have never contributed to a wiki (Kennedy, et al., 2007). Similar results were reported by Corrin, Bennett and Lockyer (2010) indicating that only 23% of students self-reported as advanced computer users, 66% never had a blog, 69% did not maintain a website, video editing or creation was rare, and they seldom (31%) or never (41%) listened to podcasts. While it is true that the technological advancements of the past few decades have created a veritable cornucopia of information for digital natives and non-digital natives alike, as Dresang (2005) points out, the digital natives are missing out on this rich environment because they have poorly developed information-seeking skills, in other words they consume from sources that they already know.

If one were to take the claims of digital native evangelists at face value, or read student commentary such as the ones provided by Roberts (2005) and Windham (2005), or view popular viral videos by so-called digital natives (VALATV, 2010; Nesbitt, 2007), one might think that all of them are power users; that they are indeed media producers, that they collaborate often, frequently and with great skill. However the collected statistics from a variety of studies paint a different picture; the fact is that the average "digital native" entering college is not technologically sophisticated; this digital native is not a power user. Even in countries where there is more access to a computer and the Internet, usage of these technologies tends to be read-only, checking facebook or looking things up on Wikipedia (Selwyn, 2010; Margaryan & Littlejohn, 2008); in other words passive interaction.

Personal Technology and the Leap to Educational Technology

Even when students use a certain technology for personal use, it neither means that they want to use that technology for use in educational ventures, nor does it mean that they know how to use it in an educational context. As Kennedy, et al. (2008) discovered, the transfer from an entertainment technology to a learning technology is neither automatic nor guaranteed. Kvavik's study (2005) informs us that even high levels of skill and use did not necessarily translate into a preference for increased use of technology in the classroom; in addition students preferred technology in moderate mounts as a supplement to their courses. There are two factors in play here; first are student attitudes toward instruction, and the role of technology in instruction; and second the nature of personal technology when mixed with instruction.

First one has to examine student motivations and perceptions as to what constitutes instruction. Nicholas (2008), through his surveys, found that the majority of students prefer lecture as the format of class instruction, in addition to collaborative group work; a similar result was seen in an Australian study (Margaryan & Littlejohn, 2008). Lohnes & Kinzer (2007) discovered that student's perceptions of education were fairly traditional: students expected to go to a classroom and viewed this space as a separate space. They also expected to be lead through the materials by a subject matter expert. Technology isn't necessarily ruled out, however it needs to tie into the subject of the class, in other words, is the application of this technology appropriate for the subject matter? In Kvavik's study (2005) he discovered that students did not feel that the use of information technology in the class increased the amount of time that they were engaged with course activities. Some students (JISC, 2007 in Bayne & Ross, 2007) actually go a step further and suspect that if all learning in mediated through technology, the value of learning will diminish.

The second factor has to do with the perception of the space: is it a private space or a public space? Students are reluctant to mix their private sphere, exemplified by the use of services like facebook and instant messaging, with the classroom sphere. Students were asked if they would like to use their favorite IM client to support classroom communication. This was rejected by students, saying that their "friends" on MSN are actually their friends, so adding many classmates to their MSN account, with whom they generally don't speak, is too laborious, and potentially an issue of privacy (Margaryan & Littlejohn, 2008). An interesting adjunct to this are the findings of Jones & Romanau (2009) whose study found that "collaboration and collaborative learning did not seem to be a strong feature of the students' experience at university and the kinds of social networking that was done was mainly informal and largely unrelated to formal learning."

Locus of Control

One final element to consider is student locus of control and the independence to experiment freely (and without consequence) with the technology. Kvavik (2005) found that in quantitative studies students say that they have the skills that they need, however qualitative data contradicts the collected quantitative data. Students only have very basic office suite skills, and they have difficulty moving beyond those basic activities; it would appear that these students don't recognize that their applications have enhanced functionalities that they can use. The same study, discovered that these digital natives are mystified by technology and some are afraid to putz around, to experiment, for fear that they will do something wrong and break the computer; Margaryan & Littlejohn (2008) found similar results. This casts further doubt on the "Nintendo over logic" assertions that digital native evangelist authors have put forth.

One possibility for this lack of confidence on the part of computer users may lie in how much time they've spent using technology. Studies have shown that those who have taken up a technology more recently, and who lack confidence, take up fewer opportunities (Linvingstone & Helsper, 2007). Older students (the assumption being non-digital native older students) have been shown to have more proficiency with technology (Eynon, 2010), indicating that greater time on task is beneficial. Control of access has also been shown to have an affect on computer literacy. Young people who use the Internet more at school are more likely to use the Internet for homework activities; however sporadic and monitored access at schools and libraries may provide sufficient access for basic information seeking, but is insufficient for the immersed kind of social engagements that we expect students to possess (Ito, et al., 2008: p.2 in Eynon, 2010).

Educators are perhaps falling into the same trap as parents are; that is that we have a tacit expectation that kids will have spontaneous engagement with schooled interests spurred by the availability of the computer as a tool (Kerwalla & Crook, 2002), this of course has proven to not be the case. If computer access and behaviors are controlled, either by supervision by an authority figure, or inconvenient placement of the computing device, the locus of control is external (Kerwalla & Crook, 2002), and this has an effect of inhibiting creative experimentation, and thus limiting the learner. These limitations lead to computer usage behaviors are counter to what "common sense" has us associate with digital natives.

Finally, from a social perspective, in contrast to the earlier writings about digital natives by digital native evangelists that portrayed digital natives as masters of their own destiny, there is some work that goes counter to this argument. Johnson (2006), a digital native herself teaching other digital natives, indicates that digital natives are complacent, actively seek authority figures and are unable to cast a critical gaze on their lives. This can be seen in digital native's own writing as exemplified in the previous section by Roberts (2005) and Windham (2005).

In the past ten years, a lot of articles have been written about how to reach out and how to teach these so-called digital natives. Many professionals, in many diverse fields, have written on the topic and they, like Smith & Caruso (2010) believe some version of the myth that these digital natives are cloud-savvy information consumers. Much of this thinking is seen as "common sense," however as Ng informs us "common-sense thinking is uncritical, episodic, and disjointed, but it is also powerful because it is taken for granted" (1997, in Selwyn, 2009). Looking at the research, however, we see that there is no one, monolithic, group that we can point to and say that those are digital natives. As a matter of fact, the individuals who would fit the stereotype of the digital native appear to be in the minority of the population.

The person who coined the term digital native, Mark Prensky, acknowledges this fact in his recent writings by saying that "by virtue of being born in the digital age, our students are digital natives by definition, but that doesn't mean that they were ever taught everything (or anything, in some cases) about computers or other technologies, or that all of them learned on their own" (p64, 2010). The problem is that he, and other digital native evangelists, are still clinging to this flawed concept of the digital native. At best it doesn't describe a population because digital technology was in our day-to-day life before the digital native came along; at worst it is an "othering" concept, a concept which creates an artificial dichotomy with a privileged and a non-privileged position. Depending on your own cultural context, the native may be the privileged or the non-privileged one.

In earlier writings about digital natives (Frand, 2000; Prensky 2001a; Prensky, 2001b; Dede, 2005; Oblinger, 2005; Oblinger & Oblinger, 2005) the native was clearly superior, however uncritically accepting such terminology not only creates a second class citizen of the non-natives, but it also places the majority of digital natives in a depriviledged position. These digital natives try to catch up to the stereotype; obstacles are added to the education of the digital native due to the moral panic (Bennett & Maton, 2010) created by the calls for radical change in education to help these digital natives with the tools that they supposedly use every day.

Student surveys showed that older students more likely to change their approach to learning, whereas the digital native students were the least likely to change their approach to learning (Garcia & Qin , 2007). As Ramaley & Zia (2005) point out, "by the time students enter high school, disengagement from course work and serious study is common." From a US context, in a post- No Child Left Behind USA, if our digital native learners aren't engaged, they have no incentive to work around the problem and find a solution. In contrast, older learners, I would posit, are more engaged and thus do work at changing their approach in order to find solutions.

Instead of having education professionals focus on the technology aspect of the debate and in certain digital native behaviors, which "common sense" has told us, are immutable, we ought to be focusing on proper pedagogy and exposing our students to information retrieval and critical information analysis skills that are in both the digital and the analog realms. We out to teach our students to actually change their approaches to learning when what they are trying out is not working for them, instead of assuming that they possess this "Nintendo over logic" which enables them to modify their learning plans when things aren't working out.

Finally, we need to move away from this fetish of insisting in naming this generation the Digital/Net/Google Generation because those terms don't describe them, and have the potential of keeping this group of students from realizing personal growth by assuming that they've already grown in areas that they so clearly have not. Learners don't know what they don't know (Christensen, 2006), but if they come to the table from a position of superiority, like they are better than the so-called digital immigrants (Roberts, 2005; Windham, 2005) they lose an opportunity to learn something that they don't know that they don't know, something that may be beneficial to them. Let's resist "common sense" because common sense isn't all that common.

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Wilber, D. J. (2007). MyLiteracies: Understanding the net Generation through LiveJournals and Literacy Practices. Innovate, 3(4) Retrieved from http :// innovateonline . info / pdf / vol 3_ issue 4/ MyLiteracies -__ Understanding _ the _ Net _ Generation _ through _ LiveJournals _ and _ Literacy _ Practices . pdf

Zickuhr, K. (2010) Generations 2010. Pew Internet and American Life Project. Retrieved November 4, 2011 from: http :// www . pewinternet . org / Reports /2010/ Generations -2010. aspx

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The Journal of Online Learning and Teaching

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We can pick out a conversation in a loud room, amid the rise and fall of other voices or the hum of an air conditioner. We can spot a set of keys in a sea of clutter, or register a raccoon darting into the path of our onrushing car. Somehow, even with massive amounts of information flooding our senses, we're able to focus on what's important and act on it.

Attentional processes are the brain's way of shining a searchlight on relevant stimuli and filtering out the rest. Neuroscientists want to determine the circuits that aim and power that searchlight. For decades, their studies have revolved around the cortex, the folded structure on the outside of the brain commonly associated with intelligence and higher-order cognition. It's become clear that activity in the cortex boosts sensory processing to enhance features of interest.

But now, some researchers are trying a different approach, studying how the brain suppresses information rather than how it augments it. Perhaps more importantly, they've found that this process involves more ancient regions much deeper in the brain - regions not often considered when it comes to attention.

By doing so, scientists have also inadvertently started to take baby steps toward a better understanding of how body and mind - through automatic sensory experiences, physical movements and higher-level consciousness - are deeply and inextricably intertwined.

Hunting for Circuits

For a long time, because attention seemed so intricately tied up with consciousness and other complex functions, scientists assumed that it was first and foremost a cortical phenomenon. A major departure from that line of thinking came in 1984, when Francis Crick, known for his work on the structure of DNA, proposed that the attentional searchlight was controlled by a region deep in the brain called the thalamus, parts of which receive input from sensory domains and feed information to the cortex. He developed a theory in which the sensory thalamus acted not just as a relay station, but also as a gatekeeper - not just a bridge, but a sieve - staunching some of the flow of data to establish a certain level of focus.

But decades passed, and attempts to identify an actual mechanism proved less than fruitful - not least because of how enormously difficult it is to establish methods for studying attention in lab animals.

That didn't stop Michael Halassa, a neuroscientist at the McGovern Institute for Brain Research at the Massachusetts Institute of Technology. He wanted to determine exactly how sensory inputs got filtered before information reached the cortex, to pin down the precise circuit that Crick's work implied would be there.

He was drawn to a thin layer of inhibitory neurons called the thalamic reticular nucleus (TRN), which wraps around the rest of the thalamus like a shell. By the time Halassa was a postdoctoral researcher, he had already found a coarse level of gating in that brain area: The TRN seemed to let sensory inputs through when an animal was awake and attentive to something in its environment, but it suppressed them when the animal was asleep.

In 2015, Halassa and his colleagues discovered another, finer level of gating that further implicated the TRN as part of Crick's long-sought circuit - this time involving how animals select what to focus on when their attention is divided among different senses. In the study, the researchers used mice trained to run as directed by flashing lights and sweeping audio tones. They then simultaneously presented the animals with conflicting commands from the lights and tones, but also cued them about which signal to disregard. The mice's responses showed how effectively they were focusing their attention. Throughout the task, the researchers used well-established techniques to shut off activity in various brain regions to see what interfered with the animals' performance.

As expected, the prefrontal cortex, which issues high-level commands to other parts of the brain, was crucial. But the team also observed that if a trial required the mice to attend to vision, turning on neurons in the visual TRN interfered with their performance. And when those neurons were silenced, the mice had more difficulty paying attention to sound. In effect, the network was turning the knobs on inhibitory processes, not excitatory ones, with the TRN inhibiting information that the prefrontal cortex deemed distracting. If the mouse needed to prioritize auditory information, the prefrontal cortex told the visual TRN to increase its activity to suppress the visual thalamus - stripping away irrelevant visual data.

The attentional searchlight metaphor was backward: The brain wasn't brightening the light on stimuli of interest; it was lowering the lights on everything else.

Despite the success of the study, the researchers recognized a problem. They had confirmed Crick's hunch: The prefrontal cortex controls a filter on incoming sensory information in the thalamus. But the prefrontal cortex doesn't have any direct connections to the sensory portions of the TRN. Some part of the circuit was missing.

Until now. Halassa and his colleagues have finally put the rest of the pieces in place, and the results reveal much about how we should be approaching the study of attention.

Obscuring, Dimming, Blinking

With tasks similar to those they'd used in 2015, the team probed the functional effects of various brain regions on one another, as well as the neuronal connections between them. The full circuit, they found, goes from the prefrontal cortex to a much deeper structure called the basal ganglia (often associated with motor control and a host of other functions), then to the TRN and the thalamus, before finally going back up to higher cortical regions. So, for instance, as visual information passes from the eye to the visual thalamus, it can get intercepted almost immediately if it's not relevant to the given task. The basal ganglia can step in and activate the visual TRN to screen out the extraneous stimuli, in keeping with the prefrontal cortex's directive.

"It's an interesting feedback pathway, which I don't think has been described before," said Richard Krauzlis, a neuroscientist at the National Eye Institute at the National Institutes of Health in Maryland who did not participate in this study.

Furthermore, the researchers found that the mechanism doesn't just filter out one sense to raise awareness of another: It filters information within a single sense too. When the mice were cued to pay attention to certain sounds, the TRN helped to suppress irrelevant background noise within the auditory signal. The effects on sensory processing "can be much more precise than just suppressing the whole thalamic region for one sensory modality, which is a rather blunt form of suppression," said Duje Tadin, a neuroscientist at the University of Rochester.

"We often neglect how we get rid of the things that are less important," he added. "And oftentimes, I think that's a more efficient way of dealing with information." If you're in a noisy room, you can try raising your voice to be heard - or you can try to eliminate the source of the noise. (Tadin studies this kind of background suppression in other processes that happen more quickly and automatically than selective attention.)

Halassa's findings indicate that the brain casts extraneous perceptions aside earlier than expected. "What's interesting," said Ian Fiebelkorn, a cognitive neuroscientist at Princeton University, is that "filtering is starting at that very first step, before the information even reaches the visual cortex."

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To Pay Attention, the Brain Uses Filters, Not a Spotlight | Quanta Magazine

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A brain circuit that suppresses distracting sensory information holds important clues about attention and other cognitive processes.

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Problem Library: 116

Crossed Circuits
Two roommates argue about each others use of energy. Which roommate should pay a utility premium? How much extra?

Watson, George

Physics and Astronomy

1 Hour or Less

Introductory (non-majors)

What Is the Cause of This Swelling and Why Am I Short of Breath When I Exercise?
"Joan is a corporate lawyer for a Fortune-500 company. She has been physically active her entire life.
Lately Joan has. . .

Tallitsch, Robert

Biological Sciences

1 Hour or Less

Intermediate (majors and non-majors)

The Fastest Man in the World
This problem introduces students to speed and acceleration.

Duch, Barbara

Physics and Astronomy

3-6 hours

Introductory (non-majors)

Pass the Buffer-in
A student needing to prepare a pH 7.5 buffer must decide whether an unlabeled recipe will do the job.

Groh, Susan

Chemistry

1-3 Hours

Introductory (majors and non-majors)

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DISCIPLINEAdd Filter "Collapse " Biological Sciences Biotechnology Chemistry Accounting Aviation Science Business Administration Chemistry and Bi...

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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 learning tool that utilizes principles from the science of learning and serious computer games. Students learn the skills of scientific reasoning by engaging in interactive dialogs with avatars. They are tutored by avatars with tutoring sessions that vary depending on how well students have responded to questions about the material they are learning. Students also play a jeopardy-like game against a feisty avatar to identify flaws in research and then generate their own questions to determine the quality of different types of research. The research examples are taken from psychology, biology, and chemistry to help students transfer the thinking skills across domains of knowledge. Early results show encouraging learning gains.

Highlights

► We designed a computerized learning game that teaches critical thinking/scientific reasoning using interactive natural language tutorials. ► The game was designed using the principles from the science of learning, such as active responding, an interesting story line, repeated testing, and engagement with real-life examples and from learning games. ► Early testing shows large learning gains for students at three different types of higher education-an open admissions community college, a state university, and a highly selective private college. ► Student response has been highly positive.

Fitness shoes with rounded soles and an orthopedic appearance promise "more shapely legs and a better butt" in addition to weight loss, reduced cellulite, and improved circulation (University of California Wellness Letter, 2012). Sound too good to be true? Not to consumers who spent $1.1 billion dollars on these shoes in 2010. (They have been on the market since 2000.) The United States Trade Commission investigated these unbelievable claims and because Reebok, one of the manufacturers, could not back up its claim that wearing these shoes would "result in more strength and tone in the buttocks muscles than traditional walking shoes," Reebok agreed to settle the case with the Trade Commission and refund $25 million to consumers (ElBoghdady, 2012).

Bogus claims about toning shoes may seem like a frivolous concern, but this example is one of countless similar scams that represents massive public disregard for the value of assessing claims, seeking evidence, and understanding scientific thinking. Millions of dollars are spent annually on products that are "packaged" as scientific, even though the "research" or evidence is highly suspect or absent. For example, millions of dollars are spent on homeopathic remedies that lack scientific evidence for their effectiveness. Scientific inquiry is important in the workplace, especially as jobs become increasingly technical, require specialized skills, and require domain-specific problem-solving, reasoning, and decision making (National Research Council, 2011). Often, the same techniques that are used to sell miraculous products are also used to create or enhance prejudice and hostilities toward other groups and to justify wars and policies that cause harm and sometimes, even death (Lilienfeld, Ammirati, & Landfield, 2009). Ideally, everyone should know how to critically evaluate the products of science and evidence-based claims, even when the topic seems distant from our usual notions of what constitutes science.

We want to educate our students and the general public to be wise consumers of research. We also want them to apply the principles of scientific thinking in their daily interactions and in contexts that bear little resemblance to scientific studies. This is a common goal for critical thinking instruction. To achieve this goal, we conceptualize science as a process, as a way of thinking about and obtaining information that informs the conclusions that we make. For example, if our students were embroiled in an argument over who was more influential to hip-hop, James Brown or Stevie Wonder, we would want them to respond that the argument can be resolved by using what scientists call an operational definition. If someone complains about a colleague who is always late, we hope that they will ask about the sample size (how often was the colleague late?) that supports this conclusion. These are examples in which the principles of scientific thinking are important in daily life.

Of course, we hope that we are also educating future scientists, helping them to "think like a scientist." Scientific thinking is needed for everyone-future scientists and future consumers of science-because we are all exposed to causal claims made by scientists and nonscientists on a daily basis. These claims are made on the Internet, television, news reports, advertisements, and the wide range of social media. Does wine really lower the risk of heart attacks? Are the screening devices at airports really safe? Can I teach my toddler to read? Will copper bracelets cure arthritis? The list of claims is endless. Operation ARA (Acquiring Research Acumen) was designed to teach students how to determine what and whom to believe.

We took up the challenge of creating the best tools for learning by applying what we know about the science of learning and adapting those principles for a generation of "digital natives," a term that describes today's young adults who have never known a world without computers and the internet. They are more likely to get their information from the vast array of nonprint media available to them than from textbooks. According to a report assembled by Frontline (Public Broadcast System, 2010), digital natives aged 13-17 average 1742 text messages a month, 91% use their profiles on social media websites to stay in touch with friends, and they spend an average of 4.5 h a day viewing screen media (internet, television, etc.), excluding games. Not surprisingly, less time is spent learning from books, and more of today's students are finding it difficult to learn from printed text. We can lament the loss of textbook skills and design educational interventions that help students achieve better learning from books, and we can also provide high quality learning experiences based on how students actually learn, including computerized learning games. There are benefits to learning from computerized games, which include improvements in visual attention and faster response times (Dye, Green, & Bavelier, 2009).

We developed a computerized learning game, Operation ARA that incorporates the best findings from the science of learning. Mayer (2008) reminded educators that no matter how advanced the technology is for educational content, if the fundamental principles of learning are not incorporated into the design of the materials, then quality learning is unlikely to occur. Here is a sampling of some of the learning principles we used in developing this program (Halpern & Hakel, 2003).

Meaningful learning of complex material is NOT a spectator sport. Deep learning requires that the learner be actively engaged with the material. Operation ARA requires that learners demonstrate their learning consistently throughout the program. There are three modules in Operation ARA: Basic Training in which students use an interactive e-book to learn basic principles of scientific thinking, such as the need for control groups and the difference between correlational and causal research designs; Proving Ground where students play a jeopardy-like game against an avatar who assumes the role of a competing student; and Active Duty in which students ask questions in order to determine whether a reported study is reliable or flawed. Early in the program, students respond to questions, but by the end of the program they are asking questions. Unlike a standard book, students cannot merely move their eyes across text or wipe a highlighter across a page. They cannot move through the program without demonstrating their learning at each step.

Recent research has shown that repeated testing, particularly when the test requires the generation of information, enhances learning. This practice produces gains in understanding and memory when the tests are aligned with important content (Karpicke and Roediger, 2007, Roediger et al., 2011). According to standard "memory trace" theories of how people remember, the act of remembering strengthens some memory traces and weakens, or perhaps fails to strengthen, others, a fact that should influence how we test students. There are complex mathematical models and functions that describe the course of remembering (or forgetting) over time (Anderson et al., 2004, Oberauer and Lewandowsky, 2011). When students practice retrieval, the strength of the memory trace is increased and the shape of the forgetting curve is altered to reflect the fact that the just-retrieved information is now more likely to be retrieved (i.e., less likely to be forgotten) in the future. In more common language, this principle is sometimes called the "testing effect," which refers to the finding that by responding to a question, the learner is practicing retrieval, thus making later retrieval of the same material more likely to be successful. As students progress through Operation ARA their understanding of the concepts and principles of science are repeatedly tested. In Basic Training, students answer a number of multiple choice questions at the end of each chapter and then participate in trialog discussions with avatars where the understanding of the material from the chapter is clarified and reinforced. Students evaluate 11 cases in the Proving Ground, and for each case they must apply their understanding of scientific concepts to determine whether the research is reliable or flawed. In Active Duty students generate their own questions about abbreviated research descriptions in order to determine whether the research is flawed. In this module, students actively recall the scientific concepts in order to generate questions, with little scaffolding at this point in the game.

Learning and retention occur over time, so it is not surprising that much of the research literature on these topics is concerned with time intervals-the time spent on the initial learning, the time between acquisition (initial learning) and recall, and the length of the time intervals between recall trials. One of the primary "laws" of learning is that spaced practice is generally superior to massed practice. Spaced schedules of studying and testing produce better long-term retention than single or few study sessions or tests (Karpicke & Bauernschmidt, 2011). Students work through Operation ARA over time and repeatedly practice and apply concepts in different contexts.

As students move through the interactive chapters during Basic Training, they receive computer-generated tutoring that varies depending on how well the student responds. The mixed-initiative dialogue used for tutoring is similar to Auto Tutor, which was designed by Art Graesser and numerous colleagues. Students using Auto Tutor have shown considerable learning gains comparable to one-on-one human tutoring (Graesser et al., 2004, VanLehn et al., 2007). The type of tutoring that students receive following each chapter is determined by the number of questions they answer correctly about the chapter they just read. Effective tutors need to both correctly gauge and adapt to the student's current level of understanding. A successful adaptive tutor chooses problems that specifically address the level of the student's prior knowledge and take previous test scores into consideration (Graesser, Conley, & Olney, 2012).

In compliance with these criteria, students are adaptively placed in one of three tutoring conditions based on their current level of knowledge, which is gauged by their scores on the previous multiple choice tests. If the human students demonstrate a low-level understanding of the concept, they receive the vicarious learning trialog in which they observe a virtual teacher tutoring a virtual student, with limited active participation. Vicarious learning conditions have shown significant learning gains specifically for low prior-knowledge students (Driscoll et al., 2003). In order to maintain engagement during vicarious learning, the students are asked to respond to questions about the tutoring situation. For example, the virtual teacher might ask the human student whether the virtual student understands the concept or whether the virtual student's answer was correct. If the learners demonstrate a moderate understanding of the concept, they receive the standard tutoring trialog, and they are tutored by the virtual teacher. For example, the virtual teacher might ask the human student to provide a definition of the concept and scaffold the student using hints, prompts, feedback, and misconception correction. If the learners demonstrate good understanding of the concept, they interact with the teachable agent trialog, and the human student tutors a virtual student. For example, virtual students might tell the human student that they do not really understand the concept and offer an incorrect explanation. The human student would then have to explain to the virtual students what the concept is and why they were incorrect.

Standard learning texts always emphasize the need for feedback or knowledge of results as an essential component for enhancing learning, but more recent reviews have shown that feedback is a complex variable that sometimes hinders learning and sometimes enhances it (Kluger and DeNisi, 1996, Kluger and DeNisi, 1998, van der Kleij et al., 2012). When data from many studies were combined in a meta-analysis, the overall effect size for feedback was a healthy d = .41, but this sizable effect masks the fact that over 1/3 of the studies showed that feedback had negative effects on learning and performance. Feedback is important in that it provides information to the learner about his or her own performance, but the learner still has to derive meaning from it and it may be that the way learners interpret feedback is what determines when it will be beneficial. What does feedback really mean to a learner? Is successful learning indicative of the intelligence or skill of the learner, the difficulty of the learning task, the way learning performance is assessed, or the amount of effort expended? Learning settings need to be designed so that the type of feedback is matched to the intended reason for the learning task. Even a formerly simple concept like feedback needs to be understood in terms of its intended use so that learners do not interpret feedback as punishment, which leads to resistance to the information provided by the feedback.

Most research reviews conclude that feedback should be given at appropriate intervals, probably with increasing length of the intervals as learning progresses (Winstein & Schmidt, 1990). Thus, early in the learning process, more frequent feedback is needed than later in the learning process. In this way, learners can become judges of their own performance and rely less upon external knowledge of results than they would with more constant feedback. We used this principle in the design of Operation ARA. As learners progress through the program, they receive feedback that is increasingly less frequent and less detailed.

Variability during learning has been shown to be important for improving long-term recall and enhancing knowledge transfer. The theme of variability during learning underscores the causal and sometimes contradictory relationship between what happens during learning and long-term retention. By using examples from different science domains-psychology, biology, and chemistry, students need to concentrate on the underlying scientific principles, which actually makes the learning more difficult. Learners need to expend more effort when learning conditions are variable, but the hard work of effortful learning pays large dividends when long-term retention is assessed.

Like practice at retrieval, varied learning conditions pay high dividends for the effort exerted. In the jargon of cognitive psychology, when learning occurs under varied conditions, key ideas have "multiple retrieval cues" and thus are more "available" in memory. For example, educational research suggests that significant learning gains can occur when different types of problems and solutions are mixed in the same lesson, even though the initial learning can take significantly longer (Perry, Samuelson, Malloy, & Schiffer, 2010).

In order to learn well, students need to be motivated and engaged in the process. According to a report from the Bureau for Labor Statistics (2011), time spent playing video games varies greatly with age. On an average weekend day, 15-19-year-old Americans read an average of 6 min and play video games 1 h and 6 min. At the time of this writing, the game Angry Birds has been downloaded tens of millions of times. There are numerous international gaming competitions with entries from most countries in the world. Thus, if we could harness only a small percentage of the energy and enthusiasm spent on computerized games so that game playing resulted in learning, we would have made great strides in creating quality learning environments. Here are some of the properties of the best selling games that we applied to Operation ARA.

Just as Operation ARA utilizes the best of what we know about how people learn, it also borrows from the growing literature on serious games. In Operation ARA learning is embedded in an intriguing story line. The game begins when players join the fictitious Federal Bureau of Science where they learn about an evil extraterrestrial plot. Apparently, the extraterrestrials are publishing poorly designed research in a variety of media outlets with the goal of confusing humans as to what constitutes good science. However, the aliens are disguised as human beings. Therefore, the player is given the task of learning the scientific method so that he can help the FBS identify the extraterrestrials. Along the way, an avatar protagonist learns that his brother is being held captive by Fuaths from the planet Thoth and apparently has broken under the stress. To complicate matters, our protagonist finds that he is falling in love with a Fuath, thus blending traditional action and romance scripts. But, all is not what it seems. We later learn that the extraterrestrials are stealing our natural resources. The plot has surprising twists and ultimately it is up to the learner to save the world by identifying the aliens among us. There are double-agents, humor, romance, political intrigue, and more all taking place within a "green" theme. Additional descriptions about Operation ARA (formerly known as Operation ARIES!) are available in Butler, Forsythe, Halpern, Graesser and Millis (2010) and Millis et al. (2011).

As students progress through the program, they receive incentives for responding correctly, which include earning points in a competition against a feisty and somewhat irritating student avatar. Later in the game, the learner has to decide if particular research is reliable or flawed, and if they are correct, human researchers are set free and alien researchers are sent to jail. Errors can be disastrous because they would allow dangerous aliens to be free and innocent humans would go to jail. Ultimately, good decisions will save the world, which we believe to be a motivating outcome.

There are yet other psychological principles that are built into the game to optimize motivation and engagement. These include giving the student control through choices, presenting problems that are at the optimal zone of challenge (not too easy and not too difficult), high amounts of interactivity between the game and the student, feedback on their contributions, and engaging media. All of the design decisions in developing ARA were motivated by scientific principles to enhance cognition or motivation.

Of course, we hope that readers are looking for evidence that students actually learn the skills of scientific thinking by playing Operation ARA. Although we have been working on this learning game for several years, data collection is still in its early stage, with initial results looking positive. This paper presents some early findings. Results from several other preliminary studies of the effectiveness of Operation ARA are available from the first author upon request. As the number of students with different sorts of backgrounds who use Operation ARA increases, we expect to have many more studies completed over the next several years.

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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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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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Learning & Memory | Aidan McDonagh | TEDxBangkokPatanaSchool

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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.

[music]
[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

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Students who have a deficit of 'thinking skills' are not only lacking sufficient grounding to embark upon undergraduate study, but also missing a vital skill essential for the 21st-century workforce.

Speaking at a Cambridge Assessment seminar on 11 February 2010 on Critical Thinking, Richard Wainer, Head of Education and Skills at CBI, said: "The ability to think, reason and make sound decisions is a vital skill for the workplace - and crucial for employees who want to do well and advance...yet many firms have expressed concerns about the lack of problem-solving skills they are seeing in school leavers."

The seminar was held to highlight how an explicit focus on Critical Thinking can enhance the attainment of pupils of all backgrounds and abilities, following recent research. Importantly, the research showed that pupils who study Critical Thinking as a discrete subject at AS level tend to do better in their other A level subjects, whether they are taking sciences, languages or humanities. Professor Steve Higgins of Durham University, agreed "there is consistent positive evidence of the benefits of teaching for thinking."

Dale Bassett, Senior Researcher at the think-tank Reform, claimed that today's curriculum is to blame. He commented that the teaching and learning of Critical Thinking has been "lost" in the curriculum through "prescriptive, restrictive exams".

The seminar brought together over 60 teachers, industry representatives and leading academics. There was much debate whether Critical Thinking should be treated as a specialist, stand-alone subject or 'embedded' and taught in other subjects. However, there was widespread agreement about the benefits of thinking skills in education and employment and a consensus that, whether delivered separately or embedded, it is important that the teaching of Critical Thinking be explicit.

Tim Oates, Group Director of Assessment Research & Development at Cambridge Assessment, said: "False oppositions are displayed in two common questions around Critical Thinking. They are: 'Should it be taught as a separate subject, or integrated into all subjects?' and 'Should it be part of the formal curriculum and assessed, or part of the informal curriculum and unassessed?' Research shows the answer to the first is: 'It should be reinforced through dedicated provision and then applied in all subjects'. The answer to the second is also clear: 'It doesn't matter, as long as it is based on a sound conception of Critical Thinking and delivered through robust pedagogy'."

Critical Thinking is still relatively new as a stand-alone qualification and understanding of the discipline is still being formed. Its early use was largely confined to university entrance tests but it is now widely available at upper secondary school level. In June 2009, students at around one in six schools took OCR's Critical Thinking AS level.

Oates added: "In developing qualifications in Critical Thinking, Cambridge Assessment isn't asserting that a qualification is the only way to enhance pupils' facility in Critical Thinking, but is offering schools a supportive, clear structure for both learning provision and recognition of attainment."

The films below capture the views of several Critical Thinking teachers as well as the presentations from the recent event. A podcast is also available further down this page.

To hear the whole event (all presentations and debate), please download the podcast below.

Related materials

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Critical Thinking - its role, value and impact upon driving attainment

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Students who have a deficit of 'thinking skills' are not only lacking sufficient grounding to embark upon undergraduate study, but also missing a vital skill essential for the 21st-century workforce.

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The Extraordinary Teaching Project: Developing Critical Thinking through Peer Review

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We are cognitive psychological scientists interested in research on education. Our main research focus is on the science of learning. (Hence, "The Learning Scientists"!). Our Vision is to make scientific research on learning more accessible to students, teachers, and other educators.

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Abstract

The past few years have been marked by a large number of discoveries about the learning brain. Those insights have the potential to support teachers in designing even better classroom environments to help you learn better. While understanding the brain can be helpful for teachers, this knowledge can also be beneficial for you as a student. For instance, it can encourage you to believe in your capacity to improve your own skills. Such beliefs make it more likely for you to make an effort and to make better use of supportive learning strategies []. In this article, we briefly present some core principles of the learning brain and suggest learning strategies inspired by neuroscience for you to try at school or at home.

What Happens in My Brain When I Am Learning?

Your brain is primarily composed of about 85 billion neurons, which is more than the number of stars you can see with the naked eye in the night sky. A neuron is a cell which acts as a messenger, sending information in the form of nerve impulses (like electrical signals) to other neurons (see Figure 1). For example, when you are writing, some neurons in your brain send the "move fingers" message to other neurons and this message then travels through the nerves (like cables) all the way to your fingers. The electrical signals that are communicated from one neuron to another are therefore what allows you to do everything you do: write, think, see, jump, talk, compute, and so on. Each neuron can be connected with up to 10,000 other neurons, leading to a large number of connections in your brain [], which looks like a very dense spider web (see Figure 2).

Figure 1 - Figure illustrating two neurons that are connected.

Figure 2 - Figure illustrating the very large number of connections between neurons.

When you are learning, important changes take place in your brain, including the creation of new connections between your neurons. This phenomenon is called . The more you practice, the stronger these connections become. As your connections strengthen, the messages (nerve impulses) are transmitted increasingly faster, making them more efficient []. That is how you become better at anything you learn whether it is playing football, reading, drawing, etc. We can compare the connections between your neurons to trails in a forest (see Figure 3). Walking through a forest without a trail is difficult, because you have to compact and push the vegetation and branches out of the way to carve your way through. But the more you use the same trail, the easier and more practicable it becomes. Conversely, when you stop using the trail, the vegetation grows back, and the trail slowly disappears. This is very similar to what happens in your brain-when you stop practicing something, the connections between your neurons weaken and can ultimately be dismantled or pruned. That is why it may seem so difficult to start reading again when school starts if you have not read all summer. However, it is possible for some neural networks to become so strong that the trails or connections never completely disappear.

Figure 3 - Figure illustrating the analogy of the trail in the forest.

The fact that learning rewires your neurons shows how dynamic (plastic) your brain is-that the brain changes and does not remain fixed. Practicing or rehearsing repeatedly activates your neurons and makes you learn. These changes happen as early as when a baby is in their mother's womb and continues throughout a person's life. So, the question is, how can you help your neurons to create and strengthen their connections? Here, we present two strategies that appear to be more compatible with how your brain works and could help you learn better.

Which Learning Strategies Are More Compatible With Your Brain?

Because the connections between your neurons need to be activated multiple times to become stronger and more efficient, a first and crucial strategy is to repeatedly activate them. This means that to learn arithmetic tables for instance, you have to practice it repeatedly, to establish the "trail" between your neurons. As a baby, you were not able to speak and walk within 1 day: you practiced a lot. However, it is important to note that only reading or glancing at your arithmetic tables will not be that helpful in connecting your neurons. You might also find it quite disengaging and boring. To create the connections between your neurons, you need to retrieve the arithmetic tables from your memory. In other words, you have to try recall the answer yourself to activate your connections. We are not saying that this is easy to do! However, scientists think that this "struggle" improves learning because the challenge is an indication that you are building new connections. Remember, learning something new is like hiking in a bush with no designated trail, you will probably walk slowly at first, but if you keep hiking, trails will start forming and eventually you will be walking on well-beaten tracks. Besides, when you do try to recall what you have learned and make a mistake, it can help you identify gaps in your learning and give you an indication of which trail still needs to be worked on.

Scientists have also noted that performing tests or exams can help you remember information better than studying alone []. For example, if you study your arithmetic tables interspersed with test periods, you will probably perform better on your final test than if you had only studied. Why? The tests require that you retrieve the information from the neurons in which the information is stored, thus activating your connections and contributing to their strengthening. The point is thus to practice retrieval in an engaging way. There are different strategies that you could try at home, for example answering practice questions or using flashcards. These should improve learning more than re-reading or listening to lectures (as long as you do not flip the flashcard over before recalling the answer!). Other strategies include preparing questions to ask to a classmate or a parent as well as redoing tests or exercises. Use your imagination! What you need to remember is that first, for your neurons to strengthen their connections, you need to retrieve the information and avoid just reading or listening to the answer. Second, you should plan a way to get feedback to know whether you got something correct or incorrect. Do not be discouraged if you face challenges, this is a natural step of the learning process taking place in your brain!

Now that you know that neurons need to be activated repeatedly for learning to occur (and that it means retrieving information), you probably wonder how often you should practice. Scientists who study the learning brain observed that breaks and sleep between learning periods enhance learning and minimize forgetting []. It therefore seems better to retrieve often within spaced practice sessions, as opposed to a massed practice (practicing a task continuously without rest). For instance, instead of studying or doing homework for 3 h, after which you would probably feel exhausted anyway, you could separate this learning period into three 1-h periods or even into six half-an-hour periods. In short, when spacing your retrieval practice, you allow your brain to make the connections that you strengthened during your practice sessions more efficient. When you take a quick break from practicing, let us say a 20 min recess, you allow for the maintenance or replacement of the receptors on the surface of the neurons. The receptors are like electric outlets that receive the nerve impulse (electrical signals) from other neurons. Taking a break helps them work better: your neurons can thus transmit their nerve impulses more easily to other neurons. Finally, when you get a night of sleep between practice sessions, you actually benefit from a free retrieval practice session because while you sleep, your brain reactivates the connections between the neurons that you activated during the day. You could also get similar benefits from a nap. Next time you find yourself sleepy in class, you could tell your teacher that you are in fact trying to do retrieval practice! In brief, when spacing out learning, and especially retrieval practice, your brain is more activated than when you mass learn in one long session.

At this point, you are probably asking yourself how to space out learning in your day-to-day life. The good news is that there are a number of ways to do it and it can be easily adapted to different skills, such as solving mathematical problems or memorizing definitions. The most obvious change you can make to your study schedule is to break up sessions into smaller sessions. You could also ask your teacher to set daily or weekly review quizzes and other assignments. Finally, spacing can be done by doing interleaved practice. This consists of a set of problems arranged so that consecutive problems cannot be solved by the same strategy. For example, you could mix your math problems so that geometry questions, algebra, or inequality problems are randomly sequenced. The added benefit of interleaving is that you engage in different activities in-between two sessions, making good use of your time. In brief, one thing to keep in mind is that information that was previously learned will require less effort to re-learn because the spacing gives your brain time to consolidate-meaning your brain produces the building blocks required for the connections between your neurons.

Conclusion

Your brain is where learning occurs and you therefore need to keep your neurons active to optimize the use of class or study time. The two learning strategies proposed in this article have the potential to help you learn better by creating optimal conditions to strengthen and consolidate the connections between your neurons. You now know that you can get better by repeatedly using the "trails" in your brain and by spacing out your practice. This greater understanding of how your brain learns and the use of supportive learning strategies can now allow you to help your brain learn better!

Glossary

Neuroplasticity: ↑ The ability of your brain to change, that is to create, strenghten, weaken or dismantle connections between your neurons.

Repeatedly Activating Your Neurons: ↑ Practicing a lot, trying to retrieve information from your memory, for example by explaining a concept to a friend or answering quiz questions.

Spacing the Activation of Neurons: ↑ Practicing more often but for a shorter period. For example, instead of studying for 2 h in a row, studying 4 periods of 30 min over a few days allows your brain to take breaks and sleep which helps you remember better in the long run.

Conflict of Interest

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

Acknowledgments

We would like to wholeheartedly thank those who assisted in the translation of the articles in this Collection to make them more accessible to kids outside English-speaking countries, and for the Jacobs Foundation for providing the funds necessary to translate the articles. For this article, we would especially like to thank Nienke van Atteveldt and Sabine Peters for the Dutch translation.

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Understanding Your Brain to Help You Learn Better

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The past few years have been marked by a large number of discoveries about the learning brain. Those insights have the potential to support teachers in designing even better classroom environments to help you learn better. While understanding the brain can be helpful for teachers, this knowledge can also be beneficial for you as a student.

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Every student deserves a great teacher. So how do we develop as many expert teachers as possible? This would help every child. To truly address equity in education, to address disparities in learning outcomes for millions of students in the United States, many of whom are Black, Indigenous, and people of color, developing expert teachers is an imperative.

"The strongest education research finding in the last 20 years is that the quality of a teacher is the single greatest in-school determinate of student outcomes," writes David Steiner, executive director of the Johns Hopkins Institute for Education Policy and former commissioner of education for New York state, in a 2018 policy brief. It impacts job prospects, lifetime earnings, social skills, reduced risk of adverse life events, as well as academic outcomes-and these impacts are greater for students of color. At The Center for Transformative Teaching and Learning (CTTL) at St. Andrew's Episcopal School (MD), we believe that any plan for addressing equity in education needs to include ways to increase teacher effectiveness.

Research suggests that years of experience does not correlate with expertise or effectiveness. While this might at first seem depressing, there is a plus side. We don't have to wait years to develop expert teachers-there are strategies, knowledge, and attitudes we can target in professional development to make teachers more effective atany stage of their career. In professor John Hattie's research on the difference between experienced and expert teachers, he found that the main distinguishing factor was the ability to come up with a good strategy in the moment to help a child or group-and to do so with an automaticity and enough mental resources to handle everything else happening in their class at the same time.

Developing each teacher's toolkit of strategies and helping them learn to use the right strategy at the right time is critical. And must include strategies grounded in diversity, equity, and belonging (DEB), as well as the science of teaching and learning or mind, brain, and education (MBE). Together, DEB and MBE are a powerful combination for great teaching and make learning more equitable-and better forevery student, not just people of color, not just students with learning differences. Though students of color and students in other marginalized groups are impacted even more and often in different ways.
Belonging Together
It would be timely to illustrate this DEB + MBE approach by looking at belonging, which is starting to move center stage in educational discourse right now. Research on fostering a sense of belonging suggests it has tremendous potential for improving school performance and outcomes for students of color and first-generation students, but we are just beginning to scratch the surface of what this really looks like in schools.

One key element is setting high expectations and communicating to students-verbally and nonverbally-that we believe in their potential to meet these expectations over time-and then following through as a teacher to help make this happen. What does this take? Part of it is creating a classroom environment where each student feels safe, heard, known, respected, appropriately challenged, and that their voice, experiences, and culture matter. Supporting identity validation and eliminating identity threat are part of it as well. And so is knowing the research on metacognition, feedback, cognitive load, effective and efficient study strategies, assessment, and homework-and then translating it into everyday classroom actions. DEB provides one useful lens and toolkit of strategies to help us do this; MBE provides another. Neither DEB or MBE are sufficient on their own; together, they can help us create school and class environments that support each student on their learning journey. Another way of looking at it is that MBE can be used in support of DEB goals.

We are talking about a holistic science of teaching and learning that helps each child first feel they belong and then feel they can flourish. We need to start seeing DEB and MBE as intersecting, complementary fields, and to shift teacher training accordingly. DEB + MBE gives teachers the best possible knowledge, language, and strategies to deal with the hundreds of decisions they will make each day.

Teachers and school leaders must consider the everyday life of a student at their school:

Do they feel safe in every space at school?

Do they feel valued and that their experiences, culture, and unique story matter?

Do they feel like they can bring their full self to each class? Do they feel known? Do they feel like they belong?

Do teachers have high expectations for every student? Do teachers believe in every student's capacity to meet these expectations over time with their help? Do they communicate these beliefs to students regularly? And do teachers believe themselves when they say it?

In class, how does the teacher speak to students? Are all students given the benefit of equally long wait time when asked a question?

Is classroom instruction engaging, accessible, and relevant? Is it presented in alignment with what we know from cognitive science about how the human brain learns?

What does practice look like-does it help students develop effective and efficient strategies?

Does the feedback they receive help or hurt-and take the emotional experience of receiving feedback into account? What about homework?

Is there formative assessment before summative assessment, and do teachers tweak their plans based on what they learn from it?

The first part of this list is more connected to DEB; the second part is more connected to MBE. But in the child's reality of their day, all these pieces combine to create powerful, deep-seated feelings about school and a perception of whether school is a place for them and a valuable part of their life journey, and whether they will bring their full self to school. In teacher training and professional development, DEB and MBE are separated; in practice they are intermixed.

There are many interwoven pieces in each child's story, and many things can make learning challenging. Neither DEB nor MBE alone gives us the complete picture or the full set of strategies to help support them to move forward. Dedicated DEB practitioners and professional development are vital for every school and every teacher-we desperately need to invest in and deepen this work. When we do this, and then combine it with the best of what we know about pedagogy, assessment, metacognition, and the like, we end up with something more powerful.
The Intersection of DEB and MBE
There are many ways that DEB and MBE interconnect. We illustrate some of the ways in a Venn diagram (see "At the Intersection" below). We chose a Venn diagram because it is not hierarchical-the middle section is not better than the outside sections; it is just where they intersect. DEB and MBE are both research-driven fields-one is not "more scientific" than the other. Equitable teaching includes all of the bullet points listed and many more. There isn't space to include everything that is important.

What does this intersection look like in practice? As a first step, standalone DEB work needs to be firmly embedded in the core of our schools to eliminate inequitable practices and policies and to train all educators to deepen their practice in culturally responsive teaching. But what next? Many needs, challenges, and opportunities in schools can be better addressed by applying a DEB + MBE toolkit. For example:
When faculty are training to deliver beloved content knowledge in ways that make it more durable, usable, and flexible, we need to consider MBE principles like spaced practice, retrieval practice, and knowledge transfer. But we also need to consider DEB principles, such as a sense of belonging, what it means to make learning relevant, and equitable access to knowledge, resources, and support during project-based learning.

We must learn best practices for giving students feedback and pay particular attention to the emotional climate of how it is received, which determines whether the feedback will have a positive or negative impact. This starts with making it a priority to know each child and deliberately working to build strong relationships and a safe, calm, predictable classroom climate.

When we are working to build each student's sense of self-esteem, belonging, and self-efficacy, we need to make sure that we are teaching them the best possible study strategies and building their metacognitive ability to use the right strategy at the right time. These strategies tend to feel harder, especially at first, so they must be incentivized and embedded in each course, alongside discussions about belonging.

When we work to revise curriculum through a culturally responsive lens, we need to remember how memory is formed. New knowledge is always learned in the context of existing knowledge; what we know already is crucial in helping us learn what we need to know next. Be aware of the knowledge that your students and families bring to the school. At times we may have to "unlearn" things we have absorbed about history, race, gender, and so on before we can learn the more complete story.

We also need to plan curriculum backwards. Start with learning goals or competencies for the year, then, moving backward, plan the sequence of knowledge- and skill-building steps that have to happen in order to reach these goals.

We must address gaps in literacy-it's an equity priority-by choosing programs and training with a research-informed lens. "The reading war" about the best way to teach literacy is phony; general consensus exists on core principles, such as the role of decoding, fluency, and comprehension and the importance of structured phonics and a knowledge-rich curriculum.

When we apply both MBE and DEB strategies, we need to have an approach of "do no harm, assume nothing, and include student input." The right to get that input has to be earned through relationship-building-which is done patiently, over time, involving all teachers who share the same core mission. We cannot get students to buy into a DEB or an MBE strategy or approach without a sense of belonging or trust.

Where to Begin

Although belonging is becoming more of a prominent idea in our schools, but it is neither the starting point nor the ultimate goal. Positive social and academic identity formation, which for every student includes many constantly evolving strands, is the goal. This is what we celebrate when the student walks across the stage on graduation day-all the ways we've seen them grow in the time we've known them and all the possibilities of who they are becoming.

In our work at the CTTL, we've developed one possible guide that we think offers a promising path for DEB+MBE growth (see "A Guide for DEB + MBE"). It starts with the foundational work of teachers examining their own identities, inviting and creating space to learn about the identities of their students, and working to build a climate of safety and trust. Once this work is under way, teachers must keep at it and also work purposefully at building a sense of belonging in their class or school (which at times will involve cycling back to the steps below it). At every level, it's crucial pull in research-informed strategies from both DEB and MBE to help. For example, to help build a sense of belonging, casting a critical lens on pervasive narratives by exploring "whose voice is missing?" (a classic DEB strategy) and giving time in class for students to understand and act on feedback they have just received (a classic MBE strategy) are both helpful-and there are many others.

The challenges facing students and schools are complex and multifaceted, and benefit from multifaceted approaches to finding solutions. We need teachers and school leaders who can look at the Venn diagram and see how all the pieces fit together, how they all work in conjunction to help shape each student's experience at school. Great educators can do this-and do it in a way that leaves them with enough mental resources to deal with everything else that is happening in a busy school at the same time. By taking a DEB + MBE approach, we are more likely to create policies, practices, and places that better serve the needs of all students. It is a more robust approach to fight for equity in schools.

Readings and Resources

"The Secret of Effective Feedback" by Dylan Wiliam in Educational Leadership, April 2016

How to Give Effective Feedback to Your Students by Susan Brookhart

Belonging Through a Culture of Dignity: The Keys to Successful Equity Implementation, Floyd Cobb and John Krownapple

"Implications for Educational Practice of the Science of Learning and Development," Applied Developmental Science, Linda Darling-Hammond, Lisa Flook, Chann Cook-Harvey, Brigid Barron, and David Osher

Culturally Responsive Teaching and The Brain: Promoting Authentic Engagement and Rigor Among Culturally and Linguistically Diverse Students, Zaretta Hammond

"Teachers Make a Difference: What is the Research Evidence?," John Hattie

"Can Professional Environments in Schools Promote Teacher Development? Explaining Heterogeneity in Returns to Teaching Experience," Educational Evaluation and Policy Analysis, Matthew A. Kraft and John P. Papay

"Stereotype Threat and the Intellectual Test Performance of African Americans," Journal of Personality and Social Psychology, Claude M. Steele and Joshua Aronson

"Cognitive Ability and Teacher Efficacy," David Steiner

"Breaking The Cycle Of Mistrust: Wise Interventions To Provide Critical Feedback Across The Racial Divide," Journal of Experimental Psychology: General, David Scott Yeager, Valeria Purdie-Vaughns, Julio Garcia, Nancy Apfel, Patti Brzustoski, Allison Master, William T. Hessert, Matthew E. Williams, and Geoffrey L. Cohen

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A Powerful Combo: Diversity, Equity, and Belonging and Mind, Brain, and Education

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Every student deserves a great teacher. So how do we develop as many expert teachers as possible? This would help every child. To truly address equity in education, to address disparities in learning outcomes for millions of students in the United States, many of whom are Black, Indigenous, and people of color, developing expert teachers is an imperative.