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In service of the goal of examining how cognitive science can facilitate human-computer interactions in complex systems, we explore how cognitive psychology research might help educators better utilize artificial intelligence and AI supported tools as facilitatory to learning, rather than see these emerging technologies as a threat. We also aim to provide historical perspective, both on how automation and technology has generated unnecessary apprehension over time, and how generative AI technologies such as ChatGPT are a product of the discipline of cognitive science. We introduce a model for how higher education instruction can adapt to the age of AI by fully capitalizing on the role that metacognition knowledge and skills play in determining learning effectiveness. Finally, we urge educators to consider how AI can be seen as a critical collaborator to be utilized in our efforts to educate around the critical workforce skills of effective communication and collaboration., (© 2024. The Author(s).)

Finding better ways to implement effective teaching and learning strategies in higher education is urgently needed to help address student outcomes such as retention rates, graduation rates, and learning. Psychologists contribute to the science and art of teaching and learning in higher education under many flags, including cognitive psychology, science of learning, educational psychology, scholarship of teaching and learning in psychology, discipline-based educational research in psychology, design-based implementation research, and learning sciences. Productive, rigorous collaboration among researchers and instructors helps. However, translational research and practice-based research alone have not closed the translation gap between the research laboratory and the college classroom. Fortunately, scientists and university faculty can draw on the insights of decades of research on the analogous science-to-practice gap in medicine and public health. Health researchers now add to their toolbox of translational and practice-based research the systematic study of the process of "implementation" in real work settings directly. In this article, we define "implementation science" for cognitive psychologists as well as educational psychologists, learning scientists, and others with an interest in use-inspired basic cognitive research, propose a novel model incorporating implementation science for translating cognitive science to classroom practice in higher education, and provide concrete recommendations for how use-inspired basic cognitive science researchers can better understand those factors that affect the uptake of their work with implementation science.

How does the mind work--and especially how does it learn? Teachers' instructional decisions are based on a mix of theories learned in teacher education, trial and error, craft knowledge, and gut instinct. Such knowledge often serves us well, but is there anything sturdier to rely on? Cognitive science is an interdisciplinary field of researchers from psychology, neuroscience, linguistics, philosophy, computer science, and anthropology who seek to understand the mind. In this regular "American Educator" column, we consider findings from this field that are strong and clear enough to merit classroom application.

Cognition is not just 'in the head'; it extends well beyond the skull and the skin. Non-Cartesian Cognitive Science views cognition as being embodied, environmentally embedded, enacted, encultured, and socially distributed. The Douglas Fir Group (2016) likewise recognizes languages as emergent, social, integrated phenomena. Language is the quintessence of distributed cognition. Language cognition is shared across naturally occurring, culturally constituted, communicative activities. Usage affects learning and it affects languages, too. These are essential components of a theory of language cognition. This article summarizes these developments within cognitive science before considering implications for language research and teaching, especially as these concern usage-based language learning and cognition in second language and multilingual contexts. Here, I prioritize research involving corpus-, computational-, and psycho-linguistics, and cognitive psychological, complex adaptive system, and network science investigations of learner--language interactions. But there are many other implications. Looking at languages through any one single lens does not do the phenomena justice. Taking the social turn does not entail restricting our research focus to the social. Nor does it obviate more traditional approaches to second language acquisition. Instead it calls for greater transdisciplinarity, diversity, and collaborative work.

Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. (Contains 9 notes, 6 tables, and 1 figure.)

This paper examines the intersection between creativity, problem solving, cognitive psychology and neuroscience in a discussion surrounding the genesis of new ideas and innovative science. Three creative activities are considered. These are (a) the interaction between visual-spatial and analytical or verbal reasoning, (b) attending to feeling in listening to the "self", and (c) the interaction between conscious and non-conscious reasoning. Evidence for the importance of each of these activities to the creative process is drawn from (a) historical and introspective accounts of novel problem solving by noted scientists and mathematicians; (b) cognitive psychology and neuroscience; and (c) a recent empirical study of novel mathematics problem solving. An explanation of these activities is given in terms of cognitive neuroscience. A conceptual framework connecting each of these activities is presented and the implications for learning and teaching considered. (Contains 3 figures.)

Posttraumatic stress disorder (PTSD) was first included in the American Psychiatric Association's "Diagnostic and statistical manual of mental disorders" in 1980. Long used to describe the reactions of soldiers affected by stress in combat situations, PTSD is now recognised as a disorder affecting abused and neglected infants and children, survivors of assault and domestic violence, and disaster victims of all ages. How did a construct so distinctly associated with the experiences of adult combat veterans come to describe behaviours seen in children, and even infants? This transformation can be understood by examining the way clinical researchers have applied the "developmental sciences" (child and adolescent development, neuroscience, and cognitive science) to the study of trauma. Each of the developmental sciences has contributed to our understanding of children's reactions to traumatic situations, and each plays an integral part in the effort to understand PTSD as a disorder of children as well as adults.

Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation of something false or nonexistent. Pearl refers to Bayes nets as oracles for intervention, and interventions can tell us what the effect of action will be or what the effect of counterfactual possibilities would be. Counterfactuals turn out to be necessary to understand thought, perception, and language. This selection of papers tells us why, sometimes in ways that support the Bayes net framework and sometimes in ways that challenge it.

In this article we focus on the concept of concept in conceptual change. We argue that (1) theories of higher learning must often employ two different notions of concept that should not be conflated: psychological and scientific concepts. The usages for these two notions are partly distinct and thus straightforward identification between them is unwarranted. Hence, the strong analogy between scientific theory change and individual learning should be approached with caution. In addition, we argue that (2) research in psychology and cognitive science provides a promising theoretical basis for developing explanatory mechanistic models of conceptual change. Moreover, we argue that (3) arguments against deeper integration between the fields of psychology and conceptual change are not convincing, and that recent theoretical developments in the cognitive sciences might prove indispensable in filling in the details in mechanisms of conceptual change.

Schizophrenia and high functioning autism-spectrum disorders (ASD) are neurodevelopmental conditions that mainly impair social competence, while general intelligence (IQ) is spared. Both disorders have a strong ancillary role in theoretical research on social cognition. Recently the debate has started to be inflected by embodied and phenomenological approaches, which claim that the standard portrayal of all social understanding as so-called "mindreading", i.e. the attribution of mental states to others in the service of explaining and predicting their behavior, is misguided. Instead it is emphasized that we normally perceive others directly as conscious and goal-directed persons, without requiring any theorizing and/or simulation. This paper evaluates some of the implications of abnormal experiences reported by people with schizophrenia and ASD for the current debate in cognitive science. For these people the practice of explicit mindreading seems to be a compensatory strategy that ultimately fails to compensate for--and may even exacerbate--their impairment of intuitive and interactive social understanding. Phenomenological psychopathology thereby supports the emerging view that "mindreading" is not the principal form of normal social understanding. (Contains 1 table.)

Purpose: The concept of a mental model has been described by theorists from diverse disciplines. The purpose of this paper is to offer a robust definition of an individual mental model for use in organisational management. Design/methodology/approach: The approach adopted involves an interdisciplinary literature review of disciplines, including system dynamics, psychology, cognitive science and organisational learning. Findings: Critical reflection on the published individual mental model definitions revealed similarities and shortcomings. It is argued that here the literature presents some consensus in the concept being internally held and having the capacity to affect how a person acts. The proposed definition of an individual mental model was found to be robust through a complexity based inquiry conducted in an organisation within the hospitality industry. Research limitations/implications: The application of the model has only been tested in one case study with a small staff sample in the hospitality industry. Thus generalisation is limited pending further testing. Practical implications: The pilot study demonstrated the usefulness of the definition of an individual mental model in making the conceptualisations of work practices explicit at various levels within organisations. Originality/value: This paper produces a definition that is lucid, inclusive, and specific for mental model research and knowledge management in organisations. The paper provides added value for academics and organisational practitioners interested in a robust definition for understanding the concept and the implications of mental models on an individual's actions.

The concept of innateness appears in systematic research within cognitive science, but it also appears in less systematic modes of thought that long predate the scientific study of the mind. The present studies therefore explore the relationship between the properly scientific uses of this concept and its role in ordinary folk understanding. Studies 1-4 examined the judgments of people with no specific training in cognitive science. Results showed (a) that judgments about whether a trait was innate were not affected by whether or not the trait was learned, but (b) such judgments were impacted by "moral" considerations. Study 5 looked at the judgments of both non-scientists and scientists, in conditions that encouraged either thinking about individual cases or thinking about certain general principles. In the case-based condition, both non-scientists and scientists showed an impact of moral considerations but little impact of learning. In the principled condition, both non-scientists and scientists showed an impact of learning but little impact of moral considerations. These results suggest that both non-scientists and scientists are drawn to a conception of innateness that differs from the one at work in contemporary scientific research but that they are also both capable of "filtering out" their initial intuitions and using a more scientific approach. (Contains 1 table and 3 figures.)

While the average teenager's conversation may seem inundated with the word "like", in the mathematics classroom, teenagers use it with purpose. Linguists study the word "like" to understand and categorize comparative statements. By overlapping linguistics and mathematics education within the frame of cognitive science, this study found that high school students do not use the word "like" arbitrarily. Its use within conceptual-metaphor analysis (Lakoff, & Johnson, 2003; 1980) suggests a specific purpose within mathematical problem solving. This interdisciplinary study identifies distinctions in high school students' use of the word "like." Specifically, students predominantly used the word "like" in a concrete manner to aid in conceptualization. This article offers practical indicators for teachers to improve students' ability to solve mathematics problems. (Contains 5 tables and 1 figure.)

A key aim in biology and psychology is to identify fundamental principles underpinning the behavior of animals, including humans. Analyses of human language and the behavior of a range of non-human animal species have provided evidence for a common pattern underlying diverse behavioral phenomena: Words follow Zipf's law of brevity (the tendency of more frequently used words to be shorter), and conformity to this general pattern has been seen in the behavior of a number of other animals. It has been argued that the presence of this law is a sign of efficient coding in the information theoretic sense. However, no strong direct connection has been demonstrated between the law and compression, the information theoretic principle of minimizing the expected length of a code. Here, we show that minimizing the expected code length implies that the length of a word cannot increase as its frequency increases. Furthermore, we show that the mean code length or duration is significantly small in human language, and also in the behavior of other species in all cases where agreement with the law of brevity has been found. We argue that compression is a general principle of animal behavior that reflects selection for efficiency of coding.

Pedagogical considerations should be guided by empirical, brain-based research on the human information processing system. People build and organize knowledge into a network-like system that connects related information. As learning occurs, learners expand the network to accommodate new information. Instructional strategies can be used to maximize the development of the information-processing network. The authors review classic research investigating how information is encoded, stored, and retrieved; discuss instructor expertise and how it may influence the learning environment; and consider the benefits of peer-to-peer interaction from both the theoretical perspective and through application of these principles in multiple psychology courses.

Bruer advocated connecting neuroscience and education indirectly through the intermediate discipline of psychology. We argue for a parallel route: The neurobiology of learning, and in particular the core concept of "plasticity," have the potential to directly transform teacher preparation and professional development, and ultimately to affect how students think about their own learning. We present a case study of how the core concepts of neuroscience can be brought to in-service teachers--the BrainU workshops. We then discuss how neuroscience can be meaningfully integrated into pre-service teacher preparation, focusing on institutional and cultural barriers.

This article presents 10 research-based principles of instruction, along with suggestions for classroom practice. The principles come from (a) research in cognitive science, (b) research on master teachers, and (c) research on cognitive supports. The instructional principles are: (1) Begin a lesson with a short review of previous learning to strengthen previous learning and lead to fluent recall; (2) Present new material in small steps with student practice after each step; (3) Ask a large number of questions and check the responses of all students; (4) Provide models to help students learn to solve problems faster; (5) Guide student practice of new material; (6) Checking for student understanding at each point can help students learn the material with fewer errors; (7) It is important for students to achieve a high success rate during classroom instruction; (8) The teacher should provide students with temporary supports and scaffolds to assist them when they learn difficult tasks; (9) Students need extensive, successful, independent practice in order for skills and knowledge to become automatic; and (10) Engage students in weekly and monthly review to develop well-connected and automatic knowledge.

This paper provides a critical examination of the current state and future possibility of formal cognitive theory for insight problem solving and its associated "aha!" experience. Insight problems are contrasted with move problems, which have been formally defined and studied extensively by cognitive psychologists since the pioneering work of Alan Newell and Herbert Simon. To facilitate our discussion, a number of classical brainteasers are presented along with their solutions and some conclusions derived from observing the behavior of many students trying to solve them. Some of these problems are interesting in their own right, and many of them have not been discussed before in the psychological literature. The main purpose of presenting the brainteasers is to assist in discussing the status of formal cognitive theory for insight problem solving, which is argued to be considerably weaker than that found in other areas of higher cognition such as human memory, decision-making, categorization, and perception. We discuss theoretical barriers that have plagued the development of successful formal theory for insight problem solving. A few suggestions are made that might serve to advance the field.

Bunge's writings on the mind-body problem provide a rigorous, analytical antidote to the persistent anti-materialist tendency that has characterized the history of philosophy and science. Bunge gives special attention to dualism and its shortcomings, and this attention is welcome in view of the resurgence of the doctrine today. However, I focus my comments selectively on Bunge's more controversial, provocative claims, not to dismiss them, but to engage with them seriously. For example, a difficulty arising from Bunge's rhetorical style and its undoubted virtues is that not all the targets of his self-confessed "bashings" ("2010", xi) are equally deserving. For example, Bunge suggests "most contemporary philosophers of mind are indifferent to psychology, or are remarkably uninformed about it". This charge cannot be sustained today in light of the work of foremost philosophers today.

The assumption that bodies have little to do with thinking--other than to be the vehicle that gets a mind to a classroom--deeply underpins the traditional model of schooling. Lessons and seminars are designed on the premise that thinking happens best when people are pretty still, their bodies are quiet and undemanding of attention, and they are writing or talking. Unless it is interfering, the physical body has little to do with cognition. This paper offers an overview of the emerging field of "embodied cognition" that profoundly challenges this model of the mind, and therefore undermines many of the assumptions that underlie the dominant sedentary and disembodied approach to the high-status bits of education.

Historically, cognitive researchers have largely ignored the domain of sport in their quest to understand how the mind works. This neglect is due, in part, to the limitations of the information processing paradigm that dominated cognitive psychology in its formative years. With the emergence of the embodiment approach to cognition, however, sport has become a dynamic natural laboratory in which to investigate the relationship between thinking and skilled action. Therefore, the purpose of this paper is to explore some insights into the relationship between thinking and action that have emerged from recent research on exceptional performance states (e.g., "flow" and "choking" in athletes. The paper begins by explaining why cognitive psychologists' traditional indifference to sport has been replaced by a more enthusiastic attitude in recent years. The next section provides some insights into the relationship between thinking and skilled action that have emerged from research on "flow" (or peak performance) and "choking" (or impaired performance) experiences in athletes. The third section of the paper explores some practical issues that arise when athletes seek to exert conscious control over their thoughts in competitive situations. The final part of the paper considers the implications of research on thinking in action in sport for practical attempts to improve thinking skills in domains such as business organizations and schools.

How recurrent typological patterns, or universals, emerge from the extensive diversity found across the world's languages constitutes a central question for linguistics and cognitive science. Recent challenges to a fundamental assumption of generative linguistics--that universal properties of the human language acquisition faculty constrain the types of grammatical systems which can occur--suggest the need for new types of empirical evidence connecting typology to biases of learners. Using an artificial language learning paradigm in which adult subjects are exposed to a mix of grammatical systems (similar to a period of linguistic change), we show that learners' biases mirror a word-order universal, first proposed by Joseph Greenberg, which constrains typological patterns of adjective, numeral, and noun ordering. We briefly summarize the results of a probabilistic model of the hypothesized biases and their effect on learning, and discuss the broader implications of the results for current theories of the origins of cross-linguistic word-order preferences. (Contains 7 figures and 8 tables.)

Over the past 10 to 15 years the twin fields of neuroscience and cognitive psychology have exploded. Through a number of new imaging technologies, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) scans, scientists have been able to look into the living brain in ways never before possible. What they have discovered, some of which is discussed in this paper, may help to inspire new approaches to the practice and teaching of drawing. The process of thinking through drawing shares characteristics common to many domains in the arts and sciences. Improvisation, analogy and metaphor, exploration and invention all have their place in a variety of creative pursuits. Yet the simplicity of marks on paper as a direct externalization of thought makes drawing a particularly good case study of the human imagination at work. The act of drawing can be understood as the creation of a physical space to play with one's thoughts outside the confines of one's minds, to see and manipulate one's ideas and perceptions in visible form. Drawing is exactly the kind of external cognitive support that can enhance metacognition. It is a powerful tool for nonverbal inquiry, for thinking through problems and analyzing experiences. Beginning to draw, one immediately discovers that he or she understands far less about what he or she sees than he or she had assumed and that there is much more there than he or she had imagined. Drawing enables the drawer to see and comprehend that which is beyond words. Training the brain to draw, to engage with eye and hand, is to learn to be open to surprise, to perceive underlying structures and make unexpected connections and discoveries. In moving beyond automatic, superficial, and stereotyped responses and developing metacognitive skills like constructive perception, it is possible for those who draw to become deeper and more creative thinkers who are better equipped to solve problems across disciplines. (Contains 49 notes.)

Purpose: The purpose of this paper is to examine existing learning innovation systems and propose a systematic methodology of delivering educational innovations in the right amount, in the right place and at the right time. Design/methodology/approach: Higher education is not effectively incorporating new discoveries in cognitive science and human learning into effective teaching strategies. In this paper, the authors explore the various impediments to change. To partially overcome these barriers, Drexel University, in collaboration with Untra Academic Management Solutions, LLC, has embarked on the development of a knowledge management system to assist instructors in obtaining, implementing, evaluating and disseminating new educational innovations. The system as envisioned would be capable of adapting to various educational environments and evolving with changes in curricula, faculty expectations, learning outcomes and student characteristics. Findings: The SocraticNet as a learning environment is stimulated, based on Socratic inquiry among teachers and learners. It is an interactive social network system utilising Web 2.0-based emerging technologies fostering communication and sharing among faculty, students and others (e.g. librarians) engaged in a particular course or other educational experience. Students learn by sharing what they know, by asking questions, judging and evaluating the retrieved information, and using this information efficiently in completing their assignments or research papers. This approach results in multidimensional information flow: instructor to instructor, instructor to student, student to instructor, student to student: which adds a new richness to the interactions between faculty and students providing the framework for a true learning community. Research limitations/implications: The present work has been conducted at one institution. This can be extended to include more institutions and tried with different disciplines. There are implications for changes in relation to teaching and learning approached adopted in higher education and also for development of technology tailored to address issues emanating from the scenario. Practical implications: The research work presented has the potential to stimulate debate to further develop and refine thinking on the role and use of technology directed at improving teaching and learning in higher education. Originality/value: This paper examines learning and teaching styles in higher education taking cognizance of conditions and factors impeding new innovations in practice. Details discussions are presented and unique suggestions are made.

We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive development. Our goal is to provide an intuitive and accessible guide to the "what", the "how", and the "why" of the Bayesian approach: what sorts of problems and data the framework is most relevant for, and how and why it may be useful for developmentalists. We emphasize a qualitative understanding of Bayesian inference, but also include information about additional resources for those interested in the cognitive science applications, mathematical foundations, or machine learning details in more depth. In addition, we discuss some important interpretation issues that often arise when evaluating Bayesian models in cognitive science. (Contains 6 figures.)

Cognitive science principles should have implications for the design of effective learning environments. The self-explanation principle was chosen for the current work because it has developed significantly over the last 20 years. Early formulations hypothesized that self-explanation facilitated inference generation to supply missing information about a concept or target skill, whereas later work hypothesized that self-explanation facilitated mental-model revision (Chi, "Handbook of research on conceptual change," 2000). To better understand the complex relationship between prior knowledge, cognitive processing, and changes to a learner's representation, two classes of self-explanation prompts (gap-filling and mental-model revision) were tested in the domain of physics problem solving. Prompts designed to focus the learner on gap-filling led to greater learning and a reduction in the amount of tutoring assistance required to solve physics problems. The results are interpreted as support for the "instructional fit hypothesis"--the idea that the efficacy of instruction is contingent on the match between the cognitive processing that the instruction elicits, how those processes modify the underlying knowledge representations for the task, and the utility of those representations for the task or problem.

Advocates of the arts agree that the K-12 curriculum should include dedicated time for arts instruction. Some have argued further that knowledge and skills acquired through the arts transfer to nonarts domains. Others claim that evidence of this kind of transfer is limited and instead argue that the arts cultivate valuable dispositions that help students succeed both in and outside of school. Another potential benefit of the arts has received little attention, however. Arts integration--the use of the arts as a teaching methodology throughout the curriculum--may improve long-term retention of content. A variety of long-term memory effects well known in cognitive psychology are reviewed, and it is argued that arts integration naturally takes advantage of these effects while promoting student motivation. This review of findings and applications provides an example of how existing research from neuroscience and cognitive science can inform the work of practicing educators.

Neuroaesthetics is a burgeoning new interdisciplinary research space in which cognitive science, psychology, neuroscience, and philosophy intersect in order to better inform our understanding of aesthetic experience. The purpose of this study is to analyze high-profile work in neuroaesthetics in the light of recent research into interdisciplinary epistemology, asking "Do current attempts to use neuroscience to explore art meet rigorous interdisciplinary quality criteria?" I suggest that current approaches in neuroaesthetics frequently fail in a number of ways: they fail to meet disciplinary standards in either aesthetics or neuroscience, they fail to blend disciplines in a generative way, and they add little new that could not be investigated more fruitfully at other levels of analysis. In response to these potential pitfalls, I recommend that future researchers embrace a form of "problem-focused epistemological pluralism" in their neuroaesthetic endeavors. I end with a consideration of the educational implications of these issues. (Contains 3 notes.)

Reinforcement learning involves a tight coupling of reward-associated behavior and a type of learning that is very different from that promoted by education. However, the emerging understanding of its underlying processes may help derive principles for effective learning games that have, until now, been elusive. This article first reviews findings from cognitive neuroscience and psychology to provide insight into the motivating role of uncertain reward in games, including educational games. Then, a short experiment is reported to illustrate the potential of reward-based neurocomputational models of behavior in the understanding and development of effective learning games. In this study, a reward-based model of behavior is shown to predict recall of newly learned information during a simple learning game. (Contains 4 figures and 1 table.)

The past decade has seen major advances in cognitive, affective and social neuroscience that have the potential to revolutionize educational theories about learning. The importance of emotion and social learning has long been recognized in education, but due to technological limitations in neuroscience research techniques, treatment of these topics in educational theory has largely not had the benefit of biological evidence to date. In this article, I lay out two general, complementary findings that have emerged from the past decade of neuroscience research on emotion and social processing, with a view to beginning a dialogue about the meaning of these findings for educational theory. First, emotion and cognition are intertwined, and involve interplay between the body and mind. Second, social processing and learning happen by internalizing our subjective interpretations of other people's beliefs, goals, feelings and actions, and vicariously experiencing aspects of these as if they were our own. Together, these two results from neuroscience could have important implications for the design of learning environments; to discover these will require reconciling established educational learning theories with the current neurobiological evidence.

Many educators are already knowledgeable about and skilled in best practices. And much of what is happening in developmentally appropriate programs exemplifies "brain compatible" practices. Being educated in the connections between best practices and brain compatibility is an important part of the knowledge base of early childhood educators. Just as the profession has learned of the remarkable impact of the social and cognitive sciences, educators can now recognize the important educational implications of the neurosciences. When they connect these with what they already know about developmentally appropriate practices their effectiveness increases.

This article offers a conceptualization of media literacy pedagogy in light of National Education Technology Plan efforts, which name teaching as one of five essential areas to build an education system that can increase as well as sustain the United States' economic growth and prosperity in the global economy. In particular, two distinct forms--critical media literacy, with origins in the Frankfurt and cultural studies tradition, and new/twenty-first-century literacies instruction, the result of socio-linguistic and ethnographic traditions--can be evaluated from Fenstermacher & Richardson's quality in teaching model that includes assessment based on the process-product paradigm, cognitive science, and constructivism. This article concludes that, while all three of these research programs may help to gauge media literacy models of pedagogy in general, constructivism, and to a lesser extent cognitive science, may be the most appropriate paradigms. (Contains 2 figures.)

This is the first in a series of two articles examining the current status of instructional design (ID) scholarship and theory in four different cultures or traditions. In this article, the focus is on, first, ID models based on traditional behavioral theories of learning and, second, on models based on cognitive science and the learning sciences. While models from these two cultures are different, until recently the development of ID models was evolutionary. That is, the increasing influence of cognitively-based theories on ID work tended to be incorporated into behaviorally-based ID models without a great deal of difficulty. However , in the past 15 years, work in cognitive science and learning sciences has led to radically different forms of pedagogy that cannot be easily integrated into ID models that are firmly based on traditional ADDIE and Instructional Systems Design (ISD) models. The best known of the "new" cognitive ID models is Design-Based Research (DBR). (Contains 3 figures.)

Drawing from sources in gesture studies, cognitive science, the anthropology of religion and art/architecture history, this article explores cultural, bodily and cosmological resonances carried (unintentionally) by mathematical graphs on Cartesian coordinates. Concepts of asymmetric bodily spaces, grids, orthogonality, mapping and sacred spaces are discussed. The article argues that learners relate graphs to their own bodies through gesture, and this relationship extends to cultural associations with actual, imagined and built spaces. It is suggested that a more culturally-engaged mathematics pedagogy would benefit learners by acknowledging ancestral resonances already present in mathematical graphs and allowing for deeper learner participation in mathematics.

The term "recursion" is used in at least four distinct theoretical senses within cognitive science. Some of these senses in turn relate to the different levels of analysis described by David Marr some 20 years ago; namely, the underlying competence capacity (the "computational" level), the performance operations used in real-time processing (the "algorithmic" level), and the neural implementation (the "hardware" level). It is demonstrated here that the current focus of the artificial grammar learning literature on recursion blurs the different levels, resulting in three main corollaries: (1) the literature cannot tell us anything about the first level, as the explanation for the role of recursion therein lies elsewhere; (2) it has not studied the possible recursive processing of artificial strings properly, as studies have so far focused on the correct processing of the internal hierarchy of recursive structures, but none have attempted to probe the underlying processing operations; and (3) as a consequence, much cannot in fact be known about the neural basis of recursion. It is furthermore argued that, in general, these studies can actually tell us very little about the language faculty, and some programmatic remarks are described and defended towards a more coherent study. (Contains 2 figures, 1 table and 16 footnotes.)

There are at least three powerful insights for educational technology researchers and designers from recent neuroscience studies of the brain and from cognitive science research findings: First, our brains learn and process two very different types of knowledge; non-conscious, automated, procedural, or implicit knowledge, and conscious, controllable, declarative knowledge. Evidence also suggests that we believe we control our own learning by conscious choice, when in fact nearly all mental operations are highly automated, including learning and problem solving. Thus, first, educational technology designers must focus more on the teaching of procedural (application) knowledge. Second, human beings have a very limited capacity to think during learning and problem solving, and when that capacity is exceeded, thinking and learning stop without us being aware. Thus, designers must strive to avoid cognitive overload by focusing all presentations on essential information to be learned. Third, nearly all of our instructional design and learning theories and models fail to account for the influence of non-conscious cognitive processes and therefore are inadequate to deal with complex learning and performance. Evidence for these points is described and their implications for instruction and the learning of problem-solving and higher order thinking skills are discussed. Models of learning and instruction that appear to help overcome some of these biological and cognitive barriers are described. In addition, suggestions for new research questions on interactive technology-based learning environments that take account of the three insights are also described. (Contains 1 table.)

This article is the second in a series (see Willis, 2011) that looks at the current status of instructional design scholarship and theory. In this concluding article, the focus is on two cultures of ID work, one based on constructivist and interpretivist theory and the other based on critical theory and critical pedagogy. There are distinct advantages and disadvantages to ID models based on these two foundations, and the same is true of models based on traditional behavioral theory and contemporary cognitive science/learning sciences. A desirable approach to making decisions about what foundation to base ID practice on may be to borrow ideas, concepts, and practices across different theoretical and conceptual foundations rather than adopting a fundamentalist perspective. (Contains 2 figures.) [For Part One, see EJ917283.]

An educational assessment embodies an argument from a handful of observations of what students say, do or make in a handful of particular circumstances, to what they know or can do in what kinds of situations more broadly. This article discusses ways in which research into the nature and development of expertise can help assessment designers create tasks that address key aspects of targeted learning. Four themes from expertise are presented: organisation of knowledge, social aspects of expertise, knowledge representations and interaction. Ways to develop assessment tasks around these themes are illustrated with examples from applied projects. (Contains 10 figures.)

The primary goal of the emerging field of educational neuroscience and the broader movement called Mind, Brain, and Education is to join biology with cognitive science, development, and education so that education can be grounded more solidly in research on learning and teaching. To avoid misdirection, the growing worldwide movement needs to avoid the many myths and distortions in popular conceptions of brain and genetics. It should instead focus on integrating research with practice to create useful evidence that illuminates the brain and genetic bases as well as social and cultural influences on learning and teaching. Scientists and educators need to collaborate to build a strong research foundation for analyzing the "black box" of biological and cognitive processes that underpin learning.

This is a series of short cases useful for a variety of courses, including physiological psychology, neuroscience, cognitive psychology, cognitive science, and cognitive neuropsychology/neuroscience. Each of these cases depicts a breakdown in language that may be traced to damage in an area or areas that are related to language processing, and each is based on an actual case or cases reported in the literature. These cases were originally written for use in a problem-based learning format, but they may also be used as individual assignments. Please note: These cases focus on disruptions of spoken communication and reading. Additional disruptions of writing may also occur with damage to the brain areas associated with language (particularly Broca's area). (Contains 1 figure, 1 note, 4 resources, and 4 online resources.)

A large body of research in the conceptual change tradition has shown the difficulty of learning fundamental science concepts, yet conceptual change schemes have failed to convincingly demonstrate improvements in supporting significant student learning. Recent work in cognitive science has challenged this purely conceptual view of learning, emphasising the role of language, and the importance of personal and contextual aspects of understanding science. The research described in this paper is designed around the notion that learning involves the recognition and development of students' representational resources. In particular, we argue that conceptual difficulties with the concept of force are fundamentally representational in nature. This paper describes a classroom sequence in force that focuses on representations and their negotiation, and reports on the effectiveness of this perspective in guiding teaching, and in providing insight into student learning. Classroom sequences involving three teachers were videotaped using a combined focus on the teacher and groups of students. Video analysis software was used to capture the variety of representations used, and sequences of representational negotiation. Stimulated recall interviews were conducted with teachers and students. The paper reports on the nature of the pedagogies developed as part of this representational focus, its effectiveness in supporting student learning, and on the pedagogical and epistemological challenges negotiated by teachers in implementing this approach.

The subject of this essay is NBIC convergence (nanotechnology, biotechnology, information technology and cognitive science convergence). NBIC convergence is a recurring trope that is dominated by the paradigm of integration of the sciences. It is largely influenced by the considerations of social and economic impact, and it assumes positivism in the name of technological progress. The culture of NBIC convergence, including NBIC discourses, is ensconced on the borders between modernity/postmodernity, ambition/restraint, unity/fragmentation, and rational intellect/creativity. Both the rhetoric of ambition and visionary development, and its responding calls for some level of restraint and caution, make contrasting assumptions that, however unintentionally, further polarize the debate concerning NBIC technologies. Those engaged in producing the culture, including scientists, engineers, and ethicists of convergence, consider the ramifications of these technologies for subjectivity and identity in ways that do not fully account for the diversity of human experience, or the ambiguity of human nature. NBIC convergence, such as artificial intelligence, is a "projection of the normative self, unaware of its own specificity;" in other words, that converging technologies offer negligible insight into human corporeality or experience and, in their theoretical frameworks, are hardly conscious of the necessity of effectively mobilizing the diversity within society and of social existence in bringing about nanotechnology's "maximum benefit to humanity," and are part and parcel of creating a "nanoself," bereft of uniqueness. (Contains 4 notes.)

Two experiments investigated the processing and appreciation of double grounding, a form of intentional ambiguity often used in the construction of headlines. For example, in "Russia takes the froth off Carlsberg results," the key element, "takes the froth off," is significant both metaphorically, where it refers to the detrimental impact of Russia, and metonymically via a contextual link between the company Carlsberg and beer, its best-known product. This study predicted that double-grounded metaphors would be more cognitively demanding than comparable single-grounded metaphors (where there is no such contextual link) and that, consequently, they would result in greater cognitive effects. Experiment 1 found longer reading times for headlines that employed double-grounded metaphors than for headlines that employed single-grounded metaphors with a similar meaning. Results suggested the re-profiling of the literal interpretation in double-grounded metaphors is cognitively demanding. Experiment 2 found that double-grounded metaphors were rated higher on a wittiness scale than single-grounded ones, revealing the aesthetic effect of double grounding. Results of Experiment 2 also suggest that participants in Experiment 1 were aware of the local ambiguity, ruling out the possibility that increased reading times observed in that experiment indexed failure of comprehension. Results of both experiments are discussed in terms of ideas from cognitive semantics. (Contains 3 tables, 1 figure and 7 footnotes.)