Connecting Levels of Analysis in Educational Neuroscience: A Review of Multi-level Structure of Educational Neuroscience with Concrete Examples

In its origins educational neuroscience has started as an endeavor to discuss implications of neuroscience studies for education. However, it is now on its way to become a transdisciplinary field, incorporating findings, theoretical frameworks and methodologies from education, and cognitive and brain sciences. Given the differences and diversity in the originating disciplines, it has been a challenge for educational neuroscience to integrate both theoretical and methodological perspective in education and neuroscience in a coherent way. We present a multi-level framework for educational neuroscience, which argues for integration of multiple levels of analysis, some originating in brain and cognitive sciences, others in education, as a roadmap for the future of educational neuroscience with concrete examples in moral education

Different Methods of Embodied Cognition in Pedagogy and its Effectiveness in Student Learning

The Mathematical Ideas Analysis hypothesizes that abstract mathematical reasoning is unconsciously organized and integrated with sensory-motor experience. Basic research testing movement, language, and perception during math problem solving supports this hypothesis. Applied research primarily measures students’ performance on math tests after they engage in analogous sensory-motor tasks, but findings show mixed results. Sensory-motor tasks are dependent on several moderators (e.g., instructional guidance, developmental stage) known to help students learn, and studies vary in how each moderator is implemented. There is little research on the effectiveness of sensory-motor tasks without these moderators. This study compares different approaches to working with an interactive application designed to emulate how people intrinsically solve algebraic equations. A total of 130 participants (84 females, 54 males) were drawn from a pool of Introductory Psychology students attending San Jose State University. Participants were placed in three different learning environments, and their performance was measured by comparing improvement between a pre-test and a post-test. We found no difference between participants who worked alone with the application, were instructed by the experimenter while using the application, or who instructed the experimenter on how to solve equations using the application. Further research is needed to examine how and whether analogous sensory-motor interfaces are a useful learning tool, and if so, what circumstances are ideal for sensory-motor interfaces to be used

Evaluating weaknesses of "perceptual-cognitive training" and "brain training" methods in sport: An ecological dynamics critique

The recent upsurge in "brain training and perceptual-cognitive training," proposing to improve isolated processes, such as brain function, visual perception, and decision-making, has created significant interest in elite sports practitioners, seeking to create an "edge" for athletes. The claims of these related "performance-enhancing industries" can be considered together as part of a process training approach proposing enhanced cognitive and perceptual skills and brain capacity to support performance in everyday life activities, including sport. For example, the "process training industry" promotes the idea that playing games not only makes you a better player but also makes you smarter, more alert, and a faster learner. In this position paper, we critically evaluate the effectiveness of both types of process training programmes in generalizing transfer to sport performance. These issues are addressed in three stages. First, we evaluate empirical evidence in support of perceptual-cognitive process training and its application to enhancing sport performance. Second, we critically review putative modularized mechanisms underpinning this kind of training, addressing limitations and subsequent problems. Specifically, we consider merits of this highly specific form of training, which focuses on training of isolated processes such as cognitive processes (attention, memory, thinking) and visual perception processes, separately from performance behaviors and actions. We conclude that these approaches may, at best, provide some "general transfer" of underlying processes to specific sport environments, but lack "specificity of transfer" to contextualize actual performance behaviors. A major weakness of process training methods is their focus on enhancing the performance in body "modules" (e.g., eye, brain, memory, anticipatory sub-systems). What is lacking is evidence on how these isolated components are modified and subsequently interact with other process "modules," which are considered to underlie sport performance. Finally, we propose how an ecological dynamics approach, aligned with an embodied framework of cognition undermines the rationale that modularized processes can enhance performance in competitive sport. An ecological dynamics perspective proposes that the body is a complex adaptive system, interacting with performance environments in a functionally integrated manner, emphasizing that the inter-relation between motor processes, cognitive and perceptual functions, and the constraints of a sport task is best understood at the performer-environment scale of analysis

Rethinking theories of change in the light of enactive cognitive science: Contributions to community-scale local sustainability initiatives.

open access articleSocial innovation projects commonly refer to operationalized theories of change to inform strategy and to deliver intended outcomes. Community based sustainability campaigns, as one example, emphasize the elicitation of pro-environmental activities and decision-making among members of a host community, drawing on mainstream psychological theories of behaviour, motivation and cognitive (mental) processes. Locating an argument within the neurobiological base of structure determinism, this paper explores how theories of change for sustainability campaigns might be reimagined through the lens of enactive theory. Following a brief introduction to the enactive model of embodied cognition, implications associated with trying to operationalize the model to inform how theories of change are mapped out and used in sustainability initiatives are discussed. The paper concludes by drawing on insights from approaches to psychotherapy, which also endeavoured to apply this model of mind, and considers these within the strategic context of sustainability initiatives and public engagement

Building machines that learn and think about morality

Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also discuss how work in embodied and situated cognition could provide a valu- able perspective on future research

Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings