Identification of effective learning behaviors
College
College of Computer Studies
Department/Unit
Advance Research Institute for Informatics, Computing and Networking
Document Type
Conference Proceeding
Source Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
7926 LNAI
First Page
670
Last Page
673
Publication Date
7-16-2013
Abstract
Self-regulated learners have been shown to learn more effectively. However, it is not easy to become self-regulated because learners have to be capable of observing and evaluating their thoughts, actions and behaviors while learning. In this work, we used Q-learning to reveal the effectiveness or ineffectiveness of a learning behavior that carries over learning episodes. We also showed different types of effective learning behavior discovered and how they were differentiated. Providing learners with knowledge about learning behavior effectiveness can help them observe how strategy selection affects their performance and will help them select more appropriate strategies in succeeding learning episodes for better future performance. © 2013 Springer-Verlag Berlin Heidelberg.
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Digitial Object Identifier (DOI)
10.1007/978-3-642-39112-5-85
Recommended Citation
Inventado, P. B., Legaspi, R. S., Cabredo, R., Moriyama, K., Fukui, K., Kurihara, S., & Numao, M. (2013). Identification of effective learning behaviors. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7926 LNAI, 670-673. https://doi.org/10.1007/978-3-642-39112-5-85
Disciplines
Computer Sciences | Education | Educational Psychology
Keywords
Learning, Psychology of; Learning strategies; Independent study; Reinforcement learning
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