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タイトル: Learning Analytics to Share and Reuse Authentic Learning Experiences in a Seamless Learning Environment
著者: Hasnine, Mohammad Nehal
Ogata, Hiroaki  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0001-5216-1576 (unconfirmed)
Akçapınar, Gökhan
Mouri, Kousuke
Uosaki, Noriko
著者名の別形: 緒方, 広明
キーワード: Authentic learning experiences
informal learning
learning analytics
seamless learning
share and reuse
ubiquitous logs
vocabulary learning
発行日: Mar-2019
出版者: Society for Learning Analytics Research (SoLAR)
誌名: Companion Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19)
開始ページ: 398
終了ページ: 407
抄録: [The 9th International Learning Analytics and Knowledge (LAK) Conference] March 4-8, 2019, Tempe, Arizona, USA
記述: Authentic learning experiences are considered to be a rich source for learning foreign vocabulary. Prevalent learning theories support the idea of learning from others’ authentic experiences. This study aims at developing a learning analytics solution to deliver the right authentic learning contents created by one learner to others in a seamless learning environment. Therefore, a conceptual framework is proposed to close the loops in the missing components of the current learning analytics framework. Data is captured and recorded centrally via a context-aware ubiquitous learning system which is a key component of a learning analytics framework. k-Nearest Neighbor (kNN) based profiling is used to measure the similarity of learners’ profiles. Authentic learning contents are shared and reused through re-logging function. This paper also discusses how two previously developed tools, namely learning log navigator and a three-layer architecture for mapping learners’ knowledge-level, are adapted to enhance the performance of the conceptual framework.
著作権等: This work is published under the terms of the Creative Commons Attribution- Noncommercial-ShareAlike 3.0 Australia Licence.
URI: http://hdl.handle.net/2433/243239
関連リンク: https://lak19.solaresearch.org/
出現コレクション:学術雑誌掲載論文等

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