2021年7月
Mining mathematics learning strategies of high and low performing students using log data
Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021
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- 開始ページ
- 229
- 終了ページ
- 230
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/ICALT52272.2021.00074
- 出版者・発行元
- IEEE COMPUTER SOC
Self-regulation in learning involves planning and utilizing different shared resources. This study investigates learning strategies of different student groups when they are accessing course materials in digital medium - one group is the students with high academic performance, the other is the students with low academic performance. We analyze data of 116 students from a mathematics course in a junior high school. Using the differential pattern mining technique, we highlight underlying course content accessing patterns from the learning log collected by an e-book system, BookRoll.
- リンク情報
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- DOI
- https://doi.org/10.1109/ICALT52272.2021.00074
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000719352000067&DestApp=WOS_CPL
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85114853127&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85114853127&origin=inward
- ID情報
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- DOI : 10.1109/ICALT52272.2021.00074
- ISSN : 2161-3761
- ISBN : 9781665441063
- SCOPUS ID : 85114853127
- Web of Science ID : WOS:000719352000067