Surface and Deep Processing: Cognitive Behaviors of Aha! Moments (Part II)

Surface and Deep Processing: Cognitive Behaviors of Aha! Moments (Part II)

This article is a continuation of a research entry from the May 24, 2021 edition:

The spectrum of early research on insight ranges from observing changes in behavior and understanding psychological patterns that influence learning (Bühler, 1907; Duncker & Lee, 1945; Wallas, 1926), to the present and how insight is a unique form of learning. There are a number of theories on insight; at present, no one theory dominates interpretation (Kounios & Beeman, 2015; Sternberg 1996). In spite of differences between theories, they share two principles: (a) sudden, conscious change in a person’s representation of a stimulus, situation, event, or problem (Davidson, 1995; Kaplan & Simon, 1990), and (b) the change occurs unexpectedly (Jung-Beeman, et al., 2004; Kounios & Beeman, 2014; Metcalfe, 1986). Further, a strong correlation has been demonstrated between moments of insight and increased engagement in learning, positive boost in mood, and greater likelihood of more moments of insight (Kizilirmak, Da Silva, Imamoglu, & Richardson-Klavehn, 2016; Kounios & Beeman, 2014). Aha! moments have been shown to increase and enhance memory performance (Ash, Jee, & Wiley, 2012; Auble, Franks, & Soraci, 1979; Danek, Fraps, von Müller, Grothe, & Öllinger, 2013; Dominowski & Buyer, 2000; Kizilirmak, Da Silva, Imamoglu, & Richardson- Klavehn, 2016), reliably grounded on insight’s proven ability to, “comprise associative novelty, schema, congruency, and intrinsic reward” (Kizilirmak et al., 2016, p. 1).

The observation and categorization of these moments can also be a source of valuable information for theorists and educators. Crocker and Algina (1986) demonstrate this operationalization in order to, “establish some rule of correspondence between the theoretical construct and observable behaviors that are legitimate indicators” (p. 4). The suddenness of Aha! moments makes observing behavioral changes (and subsequent changes in understanding) more dramatic and pronounced, as opposed to more gradual and deductively reasoned outcomes. Baker, Goldstein, and Heffernan (2010) have observed this distinction by studying the precise moment when understanding changes – graphing the precise moment of learning in humans. Baker et al. (2010) diagram the shift in surface to deep processing by showing the, “differences between gradual learning (such as strengthening of a memory association) and learning given to ‘eureka’ moments, where a knowledge component is understood suddenly” (p. 13).

Figure 5. A Single Student’s Performance on a Specific Knowledge Concept (Baker et al., 2010, p. 13)

Baker et al. explain that, “entering a common multiple” (left, Figure 5) results in a “spiky” graph, indicating eureka learning, while “identifying the converted value in the problem statement of a scaling problem” (right, Figure 5) results in a relatively smooth graph, indicating more gradual learning (p. 14).

Another important implication to consider is that deep processing seems to create greater investment in learning, along with more positive outcomes for students. Dolmans, Loyens, Marcq, and Gijbels (2016) have reviewed 21 different studies that reported on surface and deep processing strategies in relation to problem-based learning, and concluded that students using deep processing strategies use, “the freedom to select their own resources to answer the learning issues, which gives them ownership over their learning” (p. 1097). This ownership suggests a strong link between intrinsic and autonomous motivation, resulting in stronger and longer-lasting outcomes. Dolmans et al. also report that surface learning strategies with problem-based learning had a similar negative effect, stating:

a high perceived workload will more likely result in surface approaches to studying and might be detrimental for deep learning. Students who perceive the workload as high in their learning environment are more likely to display a lack of interest in their studies as well as exhaustion. This is particularly true for beginning [problem-based learning] students. (p. 1097)

““If we get the deep processing, we almost always get the surface, but with much richer and rewarding outcomes!””

— J. Littlejohn, Elementary School Math Instructor

The meta-analysis concluded by affirming these positive deep processing outcomes do not come at the cost of the various surface processing benefits (p. 1097). Deep processing strategies employed by learners have also been shown to boost long-term recall of information and wider conceptual understanding. Jensen, McDaniel, Woodard, and Kummer (2014) report that learners who utilized deep processing learning strategies while preparing for high-level assessments (i.e., problem solving, analysis, and evaluation) performed better than students that did not, and these students retained a, “deep conceptual understanding of the material and better memory for the course information” (p. 307). Jensen et al. (2014) have found that this higher level of cognitive processing and understanding also made transfer-appropriate processing more likely. This conclusion is supported by similar research conducted on learners using deep processing strategies and motivated by deeper conceptual understanding (Carpenter, 2012; Fisher & Craik, 1977; McDaniel, Friedman, & Bourne, 1978; McDaniel, Thomas, Agarwal, McDermott, & Roediger, 2013). Students using transfer-appropriate processing outcomes showed improved mastery and conceptual development greater than surface strategies and beyond the at-hand assessment; the gains were greater in current work and also in future assessments utilizing deep processing strategies. This developed processing strategy offers learners the greatest advantage in future outcomes. Studying Aha! moments in learning makes understanding surface processing and shifts into deep processing more probable, and the transfer-appropriate advantages more common, offering teachers a tremendous perspective into how to best develop pedagogy.

Now You See Me, Now You Don't: The Hidden Truth In Our Faces!

Facial Expression and Emotion (and the hidden truth of our faces)

Paul Ekman (1993) examines cross-cultural research on facial expression, seeking to elucidate further understanding about four key questions: (1) “What information does an expression typically convey? (2) Can there be emotion without facial expression? (3) Can there be a facial expression of emotion without emotion? (4) How do individuals differ in their facial expressions of emotion?” (p. 384) Ekman reaffirms the cross-cultural agreement on six primary areas of universal categorization of facial expression: fear, anger, disgust, sadness, and enjoyment. Ekman also makes clear that further research is necessary to explain, “the question of what the face can signal, not what information it typically does signal” (p. 387). Important to this research is Ekman’s assertion that, “facial expressions are more likely to occur when someone sees or hears a dynamic (moving) event and the beginning of the event is marked rather than very slow and gradual” (p. 388). Ekman claims that sometimes the only expression of emotion a person may exhibit might come from an area of the body other than the face, such as, “the voice, posture, or other bodily action” (p. 388). Ekman goes further by claiming that there is a possibility for an emotion to transpire without a facial or observable change in expression (p. 389). It may be that in situations where someone shows little or no observable change in expression that the emotional connection is weak, not present at all, or not entirely transferable to the person being observed. It is important to note that change may indeed be occurring, but these changes may be sub-visible, taking place at the micro-muscular level, indicating autonomic nervous system activity that is only detectable through sophisticated measurements with electromyography (EMG) sensors. Tomkins (1963) reports that facial activity is always part of an emotion, even when its appearance is inhibited. This could be based on cultural differences or any variety of other factors. The intensity of the emotional reception is somewhat correlated with the fidelity of the expression.

Ekman (1985/2009, 1992, 1993) reports that individuals can experience emotion without observable changes in facial expression. Sometimes a person will respond to a stimulus with a head nod, a clenched fist, change in posture, or by walking toward or away from a situation. Even more intriguing is the change in expression that can be communicated through spoken words and audible vocalizations (i.e., moans, screams, or sighs), without necessarily expressing a visible change in the face. Ekman (1993) shows that it is equally true that a person can fabricate an expression of emotion without actually feeling an emotion (p. 390). Ekman states that, “although false expressions are intended to mislead another person into thinking an emotion is felt when it is not, referential expressions are not intended to deceive” (p. 390). It is most common to use referential expressions when referring to previous emotional experiences, specifically not experiences being felt currently. Examples of false emotional expressions aside from referential expressions are generally understood to be examples of deception. Efforts to deceive can be harmful or beneficial. A lie can conceal an important truth that harms a person in some manner. However, a lie can also allow a comedian to deliver a punchline at the appropriate time to maximize the intended comical effect, or give someone the courage to push past their fears when facing the insurmountable task of asking someone else to be their Valentine. The key is to fabricate expressions without specific emotional impetus.

Facial Action Coding System

Ekman and Friesen (1978/2002) published the Facial Action Coding System (FACS) manual, with a robust revision in 2002. This publication is a comprehensive guide for measuring facial expressions and behaviors. The manual includes the complete 527-page guide to various facial expressions, a 197-page investigator’s guide, a score checker protocol (included for the FACS test, published and sold separately), and a variety of example photos and videos are also included. The manual is a comprehensive system for describing all observable facial movements; it breaks down facial expressions into individual components of muscle movements that represent changes in behavior and emotional response to a given stimulus. Subsequent publications have featured subtle and microexpressions. Whether you can see them or not, there are a great many truths hidden in the expressions of our faces. Are you looking closely enough to find them?!

Historical Instances of Measurement and Intervention in U.S. Schools (Part II)

Historical Instances of Measurement and Intervention in U.S. Schools (Part II)

this article is a continuation of a research entry from the July 30, 2019 edition:

The last two decades of the twentieth century brought greater influence from the federal government, along with greater potential for teachers to become more involved in decisions that might positively affect student outcomes. The Coleman Report, A Nation at Risk, as well as subsequent federal interventions in schools have led to further reform and legislation, but not until Public Law 107 – 110, commonly referred to as No Child Left Behind, did the federal government establish such a dominant presence and focused concern with measurable outcomes. In 2001, the law was introduced to Congress as, “an act to close the achievement gap with accountability, flexibility, and choice, so that no child is left behind” (NCLB, 2002, p. 1). The legislation was in effect until a bipartisan congress stripped away the federal requirements in 2015. This law focused on standards- based reforms in education, based on the belief that by setting high standards, making outcomes for students ambitious and clear, creating and monitoring measurable goals, schools and the students within them would experience greater, more consistent achievement (NCLB, 2002). All of these improvements are based on an understanding that the role of teachers would be a primary driver for positive change. In fact, the bill requires schools to attract, retain, and develop, “highly qualified” teachers. This phrase is used more than 60 times throughout the document (NCLB, 2002).

What was most promising about this legislation was the intent to open pathways for creative, innovative, and inspired teacher practices to promote learning outcomes. Thoughtful critics of the law such as Darling-Hammond (2007) acknowledge the potential in NCLB:

While recent studies have found that teacher quality is a critical influence on student achievement, teachers are the most inequitably distributed school resource. This first-time-ever recognition of students’ right to qualified teachers is historically significant. (p. 2)

Highly qualified teachers were the intended change-agents of the hoped-for successes in NCLB, with districts being charged with,

teacher mentoring from exemplary teachers, [...] induction and support for teachers, [...] incentives, including financial incentives, [...] innovative professional development programs, [...] tenure reform, merit-based pay programs, and testing of elementary school and secondary school teachers in the academic subjects that the teachers teach. (p. 1632)

However, where federal measures aimed to reverse negative trends and improve student outcomes, the emphasis on quality teachers and teaching quality still did not receive the attention necessary to dramatically increase student achievement and narrow the achievement gap in American schools. Generally speaking, critics have pointed out that the implementation of the law was in many respects counterproductive because it (a) did not adequately account for accumulated effects of mismanaged or underfunded schools, (b) narrowed the curriculum, precisely the opposite of what sensitive and nimble teaching practices ought to do when adjusting to students in their particular situations, and (c) brought too much focus upon testing and other measurement mechanisms. The most explicit feature of the law were the unpopular standardized tests, along with tactics like “drill and kill” for test preparation, which displaced creative attempts to nurture student learning and cognitive potential (Darling-Hammond, 2007; Dee & Jacob, 201; Hanushek & Raymond, 2005; Ladd & Lauen, 2010; Rustique-Forrester, 2005; Sunderman, Tracey, Kim & Orfield 2004).

Instead of placing teachers at the center of processes for better informing learning outcomes, and placing greater emphasis on surface, deep, and transfer-appropriate thinking strategies, schools and the teachers within them succumbed to the symptoms of surface processing, short-term memorization prioritization, and the hostile environment of overtaxing students with tests (Darling-Hammond, 2007). Rather than removing barriers that continue to obstruct learning potential in schools and open more opportunities for creative thinking, more frequent Aha! experiences, as well as more holistic means of supporting the development of a child’s full potential, the American education system remained unchanged from its former industrial model of generalized goals accompanied by generalized processes.

Aha! in Action: Mr. McLaughlin (#1)

Mr. McLaughlin has 25 years of professional teaching experience in public and private high schools, beginning in a rural northern city in Texas, and now in Houston, Texas. Mr. McLaughlin describes Aha! moments as, “an exclamation point” that happens when teaching, coaching, and directing reach their fullest potential. Mr. McLaughlin recalled having many throughout his career, but offered a remarkable story of a particular student that changed the course of her life (and Mr. McLaughlin’s), based on an intense Aha! experience:

Virginia, who came [with] a reputation of being an average student, with marginal athletic ability, and quite reserved. As the years progressed, she became known as a plodder in the classroom, a good teammate in softball, and her personality began to blossom. In the spring of her senior year, however, one event seemed to have an everlasting impact on who she was and the timing was perfect. In the conference championship game, we were behind by one run in the top of the seventh inning with two outs and runners on first and second. Virginia, who always batted ninth in the batting order, looked overmatched facing a pitcher who would eventually play for the University of Arkansas. Another strike and the count was now 3 and 2. From the third base coaching box, I started moving toward Virginia and started to motion for her to meet me halfway up the baseline, but before I got my hand up to my waist, she put her hand up, palm out and mouthed the words, “I got this, coach.” She confidently repositioned herself into the batter's box . . . windup and the pitch, and the ball left her bat with a crack, a line drive perfectly over the second base bag. The first run scored and the throw to home plate dribbled away from the catcher, and before the pitcher could retrieve the ball, the second run scored. We held on in the bottom of the inning and won the championship!

Mr. McLaughlin noted that this seminal moment in his career formed the basis of a belief (his own Aha!) that, “sometimes it is the most unlikely member of a team who makes the most important contribution.” This noticeable change in Virginia’s behavior is a testimony to the extreme effect of her Aha! experience. McLaughlin describes Virginia at first as someone who was reserved, marginal athletic ability, and most notably, “a plodder in the classroom.” Over the course of their career, every teacher has this student. In fact, teachers might often dismiss a student who is both average in ability and does not seem to express a great disposition for future achievement, but that is exactly where McLaughlin’s relationship with this student, understanding how to push and pull with her abilities, became the necessary ingredient for igniting her potential, and for Mr. McLaughlin to revise his assessments. In this way, Virginia’s Aha! moment became a turning point for the teacher as well.

The Aha! moment allowed Mr. McLaughlin to understand that Virginia’s thinking had changed. But more than this, the shared Aha! experiences of Mr. McLaughlin and Virginia combine to create a life-changing moment that set a new foundation for them both to flourish now at new, previously unanticipated levels. In fact, McLaughlin changed his entire belief about what is possible with students from this experience, subsequently benefiting thousands of students over his nearly 25 years of teaching. In this situation, the winning moment can be seen as a manifestation of the Aha!, but it is also in understanding the subtle nuance between the coach and the athlete where one can fully see how the learning transcended the game. “I got this,” was perhaps an even greater breakthrough because it signified a shift in relationship, not just forms of the thinking and understanding within an individual. Virginia now connected with Mr. McLaughlin in a way previously unattainable and in a way that could not have been deduced from previous experience. This Aha! is one of enlightened human interconnectivity. Congratulations, coach!

What’s your Aha!?!

Structure of the Observed Learning Outcomes (SOLO): A Taxonomical Bridge

Structure of the Observed Learning Outcomes: A Taxonomical Bridge

Teaching practice is better informed with the knowledge of surface and deep processing, its role in learning, and the transfer-appropriate potential for student achievement in schools. However, these subsurface processes represent styles of thinking and learning – not necessarily physical behavior. In order for teachers to more fully utilize this information and synthesize strategies that support developing these processes, a correlated taxonomy will be useful. The Structure of the Observed Learning Outcome (SOLO) taxonomy is a widely recognized and accepted tool for showing changes in complexity of understanding. McMahon and Garrett (2016) report that,

SOLO is a useful contemporary tool that incorporates ... aspects of former taxonomies (Bloom, Engelhart, Furst, Hill, & Krathwohl, 1956; Merrill, 1971; Gagne, 1977/1984) in that it studies the cognitive complexities of a learner’s response to a given learning stimulus... [SOLO] emphasizing the observation of student learning cycles to describe the structural complexity of a particular response to a learning situation through five different levels: prestructural, unistructural, multistructural, relational, and extended abstract. (p. 422)

This approach more thoroughly examines changes in thinking by addressing changes in observed behavior. Just as Aha! moments represent sudden and unexpected cognitive illumination when a solution is found, along with their observable correlates, SOLO taxonomy represents a classification tool for the physiological behavior in learners as it changes over the complete cognitive continuum. This rubric for progression is a practical framework for teachers to evaluate achievement, “in a language that is generally applicable across the curriculum” (Biggs & Collis, 1989, p. 151). SOLO taxonomy is a form of measuring students’ understanding of subjects, from the introduction of a concept to a student’s expertise with it.

According to Biggs and Collis (1982/2014), who first introduced this taxonomy, SOLO is, “based on the observation that, over a large variety of tasks and particularly school based tasks, learners display a consistent sequence, or ‘learning cycle,’ in the way they go about learning them” (p. 152). In essence, as a learner moves from a superficial understanding of the components of a concept towards a deeper processing of the concept’s features, the taxonomy accurately shows these progressions in a manner that makes learning more easily observed by teachers. The final mode in the SOLO taxonomy suggests learners’ ability to extend comprehension into a final transfer-application understanding. The SOLO spectrum from prestructural to extended abstract is also analogous to the cognitive change represented when introducing a stimulus to a learner through to the development of an Aha! moment. Biggs and Collis (1989) discuss congruency among similar theories that support neo-Piagetian models (Case, Hayward, Lewis, & Hurst, 1988; Fischer, 1980; Fischer & Pipp, 1984; Halford, 1982), distinguishing, “between learning and development in a way similar to that suggested here [SOLO] with their terms ‘optimal level’ (the last mode reached) and ‘skill acquisition’” (p. 157).

Hunt, Walton, Martin, Haigh, and Irving (2015) studied the implications of school-wide adoption and application of the SOLO taxonomy to inform teaching and learning in a secondary environment. Hattie and Purdie (1994) were among the first to show that SOLO taxonomy is useful and effective for training teachers on how to structure questions, design activities, and to matriculate through modes of learning along the SOLO hierarchy in multiple curricular areas. Hattie and Purdie also showed that teachers indicated using SOLO taxonomy for accomplishing learning objectives, surface and deep processing, and found it much easier and more effective to use. Hattie, Clinton, Thompson, and Schmidt-Davis (1997) indicate in their research that,

expert teachers are more likely to lead students to deep rather than surface learning. These teachers will structure lessons to allow the opportunity for deep processing, set tasks that encourage the development of deep processing, and provide feedback and challenge for students to attain deep processing. (p. 54)

SOLO seems to promote stronger deep processing effects for teachers and with students, likely due to a reliable and understandable hierarchy for witnessing change in a learner’s thinking and cognition. In all of these studies, it is clear that surface and deep processing strategies are embedded into practices that are reflected through SOLO, and opportunities to inform and improve teaching practice are present.

What's the Difference Between Teacher Quality and Quality Teaching?

Contemporary researchers have published quantitative and qualitative research which examine learning in classrooms, particularly emphasizing learning outcomes and the effects of teacher quality and quality teaching in classrooms (Biggs, 2012; Gardner, 2011; Hattie 2016; Marzano, Frontier & Livingston, 2011; Nuthall, 2007). These two categories have specific influences and observable outcomes. Quality teaching and teacher quality both have tremendous impact on positive outcomes for students, particularly with regard to creating opportunities for moving learning objectives between surface processing and deep processing – at times into transfer-appropriate strategies for learning.

Recent arguments have been made that help to differentiate between quality of teachers and quality of teaching (or teaching efficacy) (Hanushek, 2011; Harris & Sass, 2011; Taylor, Roehrig, Hensler, Connor, & Schatschneider, 2010). Darling-Hammond and Jaquith (2012) posit that teacher quality and quality of teaching should be considered independently, but as equally important. Darling-Hammond and Jaquith argue that the talents, personal mannerisms, and paradigms each teacher draws from in order to inform their teaching should not be evaluated independently of factors that enable, “a wide range of students to learn” (p. i), asserting that teaching efficacy,

is also strongly influenced by the context of instruction: the curriculum and assessment system; the “fit” between teachers’ qualifications and what they are asked to teach; and teaching conditions, such as time, class size, facilities, and materials. If teaching is to be effective, policymakers must address the teaching and learning environment as well as the capacity of individual teachers. (p. i)

It is crucial to understand these distinctions while exploring the potential for introducing insight learning opportunities into learning environments. Teachers may be effective at implementing pedagogy, but lack the requisite training to maximize Aha! moments in learning. Similarly, an expert pedagogue may be inducing preconditions for Aha! moments but may lack the effectiveness to maximize their effect in learning, especially for moving from superficial information acquisition to deeper thinking strategies and transfer-appropriate opportunities.

Goe (2007) outlines a comprehensive framework for better understanding teacher quality in terms of its effect upon student success, following on from the concern with measurable and broad impacts upon the widest range of students. The graphic representation in Figure 2 presents teacher quality as a combination of inputs and processes, and student outcomes as measurable effects of teacher quality. These inputs and processes include teacher certification, beliefs, instructional delivery, interactions with students, teacher test scores and experience, and classroom management. Student achievement is both an input and output, often part of teacher evaluations and other forms of feedback influencing practice. Inputs, processes, and feedback from outcomes (generally in the forms of grades from student assessment) all inform the basis for teacher quality.

Figure 1. Graphic representation of a framework for teacher quality (Goe, 2007, p. 9).

Teacher as Architect of Learning and Designer of Experiences

Teaching efficacy is among the most significant determinants of student outcomes in classrooms (Hattie, 2008). As wide as the variety of teaching styles are, so are the variations of curricula, curricular delivery systems, factors affecting schools, and the quality of teachers and the training they receive. Laurillard (2013) sums up nicely the importance of teachers and their role as architects of learning and designers of experiences that optimize surface to deep thinking:

What it takes to teach cannot be determined directly from what it takes to learn, which means that teachers must be willing to treat the process as essentially problematic, iterative, and always improvable; we must stop assuming that teaching can be theorized like a natural science and treat it as a design science. (p. 82)

Indeed, teaching can and should be a designed process that encourages vibrant and dynamic growth in student outcomes. Aha! moments in learning are an important and special part of that design. These moments in learning should be captured and cultivated – and produced regularly. Teachers can positively transform learning experiences for students using strategies that promote the increased frequency of Aha! moments in their classrooms, the benefits of which connect to all areas of learning growth and potential (Kounios & Beeman, 2014). The opportunity for students to find deeper meaning in their work, extend ideas, and become more actively interested in their personal development in all areas of learning, becomes a powerful lever in education and learning overall, and one that teachers and school leaders must embrace and nurture.

Experienced teachers are able to contextualize learning and meet the needs of their students within various curricula, regardless of personality differences, and remain focused on mastery of content and transfer across subjects (Hattie, 2003). Further, as teachers develop their practice over time, the potential for greater positive impact in classrooms increases. Hattie (2011) states:

Expert teachers and experienced teachers do not differ in the amount of knowledge that they have about curriculum matters or knowledge about teaching strategies – but expert teachers do differ in how they organize and use this content knowledge. Experts possess knowledge that is more integrated, in that they combine the introduction of new subject knowledge with students’ prior knowledge; they can relate current lesson content to other subjects in the curriculum; and they make lessons uniquely their own by changing, combining and adding to the lessons according to their students’ needs and their own teaching goals. (p. 261)

The focus must therefore be on providing opportunities to develop expertise within teachers to cultivate and capture insight and discovery throughout their curriculum and course lessons. If one of the primary objectives in increasing teacher efficacy is helping students move from surface to deep thinking (Hattie, 2003), and if it is hoped that this change in thinking will produce transfer across different areas of learning, Aha! moments in learning provide an excellent opportunity for this type of teacher training. Hence, an understanding of surface and deep learning, the differences between them, the place of both in the learning, and developing Aha! moments to enact the transition from surface to deep could be most valuable in teacher development programs. These teaching strategies can be aimed at manifesting greater numbers of Aha! moments and a more robust and engaging learning environment. Teachers can be trained on how to maximize the number and magnitude of these moments and further impact learning, achievement, and observable outcomes of students.

There is a growing body of neurological research that proves cognition is highly plastic and that complex mental activity improves cognition, brain function, and structure (Chapman et al., 2015). The tools that are becoming available to enhance and increase retention of learning are becoming easier to access and more widely used, and there is growing interest from teachers and professionals in implementing techniques that increase achievement in students. School administrators must discover and invest in teaching development programs where current research about learning is at the center of informing practice. Teachers need to spend more time harvesting from the available research literature, perhaps even adding to it, in order to garner the fullness of its potential to inform behaviors, and to enhance their professional work in schools. This may be best accomplished by placing a greater premium on the observable behaviors and patterns surrounding learning in classrooms. As Laurillard (2013) suggests, we should transfer energies away from teaching teachers how to teach and toward training them in methods to become leaders of learning. Teachers cannot practically observe what is happening in the mind when learning occurs (or easily, even with various measurement apparatus – e.g., fMRI), but if the observable correlates of the Aha! moment reflect the plasticity and growth happening when students’ do learn, this breakthrough in research will open tremendous opportunities for teachers and students alike.

Aha!

Archimedes’ discovery of water displacement as a method for measuring the volume of an object was among the first recorded instances of the Aha! moment (Kounios & Beeman, 2015). The account of Archimedes’ transcendent moment can be summed up briefly: King Heiro II challenged Archimedes to determine whether a votive crown that had been made for him was made of pure gold, as represented to him, or if the goldsmith had adulterated it with some other metal. Archimedes grappled for some time with the problem of how to authenticate the crown without damaging it until one day, as he was lowering himself into his bath, he observed the correlative rise of the water level and had a flash of inspiration. He is said to have shouted Eureka! (“I’ve found it!”). His observation of displacement led to a profound insight – his Aha! moment, which was the breakthrough that allowed him to solve this problem. His Aha! moment enabled his thinking to move from surface to deep, thereby producing a theory for the measurement of the volume of an object without damaging it. More important than what Archimedes was attempting to accomplish, was how his mind now managed the exact same set of observations that most humans have when wrestling with a problem. His thinking exhibited the capacity to take seemingly disconnected ideas (i.e., the water rising in the bath, the volume of gold, and finding a way to determine legitimacy without damaging the artifact) and combine specific factual knowledge in order to provoke an Aha!, a breakthrough that created a sudden and unanticipated solution. This indicates an ability to compare and manipulate concepts, which is further up the taxonomy on the SOLO scale, not to mention the Piagetian scale of conceptual facility (1950). From the point of view of an observer, the expressive exuberance of Archimedes’ eureka made it possible to actually see him exhibiting a new level of facility with the concepts available to him. If that observational mechanism can be brought into any learning environment, along with a rich understanding of how and when human beings achieve milestones along the path to greater conceptual facility, then our instructional practice will be that much more powerful and effective.

An insight is a quantum leap in thinking. There is a distinct before and after, and history is filled with similar stories of men and women, young and old, and their Aha! moments. Whether these moments are connected to monumental or to less consequential but still important moments of insight, they are part of the fabric of the human journey because they are a universal form of human learning. Galileo looked to the heavens and observed the orbit of the Earth (Kounios & Beeman, 2015), suddenly forming theories about orbital eccentricity; Sir Isaac Newton had an Aha! moment when he saw the apple fall from the tree (Gleick & Alexanderson, 2005), later going on to describe universal gravitation; Einstein worked through a thought experiment when a sudden breakthrough allowed him to conceive what became his theory of relativity (Einstein, 1922/2003); and Sir Paul McCartney woke up one morning, after a long series of shows, and in his Aha! moment he crafted (“Yesterday”), a song that has since gone on to become the most- recorded song in history (McCartney, 2009). In each of these examples, the sudden realization could not have been predicted. The significance of these moments generally causes the learner to refer back to the moment in a sort of before-and-after manner – a life moment.

The practice of seeking these moments of insight, their subsequent outcomes, and the transformation in learning that takes place as a result can be of great value in pedagogy. My research has collected, documented, and analyzed the observable instances of these Aha! moments, and used the term “correlates” to signify both a possible pattern to observation and a taxonomy of insight that occurs for individual students in complex ways. The goal is not only to identify these moments, but also to produce a template for techniques, methods, and practices that learning leaders may adopt or implement in their curricula in the hope of creating the fertile preconditions that facilitate production of these moments.