Identification of effective learning behaviors

Paul Salvador Inventado, Roberto Legaspi, Rafael Cabredo, Koichi Moriyama, Ken Ichi Fukui, Satoshi Kurihara, Masayuki Numao

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルArtificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings
出版社Springer Verlag
ページ670-673
ページ数4
ISBN(印刷版)9783642391118
DOI
出版ステータスPublished - 2013
外部発表はい
イベント16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, TN, United States
継続期間: 2013 7 92013 7 13

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7926 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other16th International Conference on Artificial Intelligence in Education, AIED 2013
CountryUnited States
CityMemphis, TN
Period13/7/913/7/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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