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Research on learning has previously focused on changes in knowledge and behavior occurring over long periods of time, such as over a period of hours, weeks, months and years. However, there is no doubt that learning-contingent changes in knowledge and behavior are mediated by neural processes occurring at much shorter timeframes (e.g., milliseconds), including the time between a single observable behavioral event, that help determine whether learning occurs. In addition, current applied research in education requires experimentation and assessment in authentic contexts within which learning and performance take place in order to provide ecologically valid results with respect to contemporary contexts that involve social interaction. We argue that it is now time for the field of neuroeducation to relate psychophysiological and behavioral data across time scales. Globally, a better understanding of the underlying cognitive processes occurring during different components of learning. This should lead to novel learning environments, greater and more efficient interactivity between teacher and learner(s), better assessment tools leading to qualitatively and quantitatively better development of knowledge and skills in key domains such as teaching, business, health professions, engineering as well as other domains targeting human development and well-being. Along these lines, this paper presents a research program oriented towards the modeling of learning trajectories and performance at psychophysiological, cognitive and social levels. The projected research findings should allow for more significant understandings of the implication of cognitive neuroscience in education by linking results with more authentic learning and performance situations.

An agenda for neuroeducation: relating psychophysiological and behavioral data across time scales of learning