Toward a Novel Neuroscience-Based System Approach Integrating Cognitive and Implicit Learning in Education

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Date

2023

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Springer Science and Business Media Deutschland GmbH

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Green Open Access

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Abstract

Emotional-enhanced learning is a meaningful driver of engagement leading to long-term memory retention in learners, however, traditional approaches such as problem-based learning, and project-based learning, among others, do not consider brain-based learning guidelines concerning learner’s emotional experience design. The Neuroscience-based Learning (NBL) technique is a novel neuro-educational approach that applies the implicit neuro-physiological mechanisms underlying vivid and highly-arousal emotion-al experiences leading to long-term memory retention. The NBL is devised from a cybernetic system point of view, by explaining the novel neuro-physiological learning scheme describing the relation among the environment and the learner’s internal mental processes ranging from perceptions, comparison with previous experiences and memories, immediate sensations and reactions, emotions, desires, intentions, higher order cognitive functions, and controlled actions towards the environment. While explaining biological processes, the scheme also relates the types of memory systems with their non-associative and associative learning mechanisms, and the variables that modulate learning. NBL proposes the triggers for a vivid and highly-arousal emotional learning, which are novelty, unpredictability, sense of low control, threat to ego, avoidance (aversion-mediated learning), and reward (reward-based learning). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Keywords

Emotional-enhanced learning, Neuroscience, Learning, Implicit learning, Long-term memory, Neuroeducation

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Citation

Dorantes-Gonzalez, D. J., Tsvetkova, N., Veledinskaya, S., Babanskaya, O., & Çakar, T. (2023). Toward a Novel Neuroscience-Based System Approach Integrating Cognitive and Implicit Learning in Education. In International Conference Cyber-Physical Systems and Control (pp. 661-673). Cham: Springer International Publishing.

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460 LNNS

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661

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673
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