The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology – namely, Behaviorism and evolutionary psychology – that set aside mechanistic explanations or make use of optimality assumptions. Through (...) these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls that have plagued previous theoretical movements. (shrink)

In recent years there have been growing calls for forging greater connections between education and cognitive neuroscience. As a consequence great hopes for the application of empirical research on the human brain to educational problems have been raised. In this article we contend that the expectation that results from cognitive neuroscience research will have a direct and immediate impact on educational practice are shortsighted and unrealistic. Instead, we argue that an infrastructure needs to be created, principally through interdisciplinary training, funding (...) and research programs that allow for bidirectional collaborations between cognitive neuroscientists, educators and educational researchers to grow. We outline several pathways for scaffolding such a basis for the emerging field of ‘Mind, Brain and Education’ to flourish as well as the obstacles that are likely to be encountered along the path. (shrink)

Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about (...) fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions. (shrink)

Cognitive neuroscience aims to improve our understanding of aspects of human learning and performance by combining data acquired with the new brain imaging technologies with data acquired in cognitive psychology paradigms. Both neuroscience and psychology use the philosophical assumptions underpinning the natural sciences, namely the scientific method, whereby hypotheses are proposed and tested using quantitative approaches. The relevance of 'brain science' for the classroom has proved controversial with some educators, perhaps because of distrust of the applicability of so-called 'medical models' (...) to education. Nevertheless, the brain is the main organ of learning, and so a deeper understanding of the brain would appear highly relevant to education. Modern science is revealing the crucial role of biology in every aspect of human experience and performance. This does not mean that biology determines outcomes. Rather, there is a complex interplay between biology and environments. Improved knowledge about how the brain learns should assist educators in creating optimal learning environments. Neuroscience can also identify 'biomarkers' of educational risk, and provide new methodologies to test the effects of educational interventions. (shrink)

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In this review essay, Francis Schrag focuses on two recent anthologies dealing completely or in part with the role of neuroscience in learning and education: The Jossey-Bass Reader on the Brain and Learning, edited by Jossey-Bass Publishers, and New Philosophies of Learning, edited by Ruth Cigman and Andrew Davis. Schrag argues that philosophers of education do have a distinctive role in the conversation about neuroscience. He contends that the impact of neuroscience is likely to be substantial, though not in the (...) way its advocates imagine. It has the potential to enhance education by way of interventions that successfully alter the fundamental neural mechanisms of learning, but neuroscience is unlikely to affect classroom teaching substantially. (shrink)