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Shipley, Thomas F.; Tikoff, Basil – Journal of Geoscience Education, 2017
This manuscript addresses the potential role of geoscience education research in understanding geoscience expert practice. We note the similarity between the perception-action framework of Ulric Neisser (Neisser, 1976) and the observation-prediction framework used by geoscience practitioners. The consilience between these two approaches is that…
Descriptors: Earth Science, Cognitive Science, Models, Science Instruction
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Stringer, Steve; Tommerdahl, Jodi – Mind, Brain, and Education, 2015
As the field of Mind, Brain, and Education seeks new ways to credibly bridge the gap between neuroscience, the cognitive sciences, and education, various connections are being developed and tested. This article presents a framework and offers examples of one approach, predictive modeling within a virtual educational system that can include…
Descriptors: Cognitive Processes, Brain, Neurosciences, Cognitive Science
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Lau, Jey Han; Clark, Alexander; Lappin, Shalom – Cognitive Science, 2017
The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary…
Descriptors: Grammar, Probability, Sentences, Language Research
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Solway, Alec; Botvinick, Matthew M. – Psychological Review, 2012
Recent work has given rise to the view that reward-based decision making is governed by two key controllers: a habit system, which stores stimulus-response associations shaped by past reward, and a goal-oriented system that selects actions based on their anticipated outcomes. The current literature provides a rich body of computational theory…
Descriptors: Habit Formation, Brain, Decision Making, Rewards
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Howard-Jones, Paul; Demetriou, Skevi; Bogacz, Rafal; Yoo, Jee H.; Leonards, Ute – Mind, Brain, and Education, 2011
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…
Descriptors: Educational Games, Rewards, Positive Reinforcement, Psychoeducational Methods
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Shiffrin, Richard M.; Lee, Michael D.; Kim, Woojae; Wagenmakers, Eric-Jan – Cognitive Science, 2008
This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues…
Descriptors: Bayesian Statistics, Generalization, Sciences, Models
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers