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DCフィールド | 値 | 言語 |
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dc.contributor.author | Flanagan, Brendan | en |
dc.contributor.author | Shimada, Atsushi | en |
dc.contributor.author | Yang, Stephen | en |
dc.contributor.author | Chen, Bae-Ling | en |
dc.contributor.author | Shih, Yang-Chia | en |
dc.contributor.author | Ogata, Hiroaki | en |
dc.contributor.alternative | 緒方, 広明 | ja |
dc.date.accessioned | 2019-08-07T07:39:51Z | - |
dc.date.available | 2019-08-07T07:39:51Z | - |
dc.date.issued | 2019-03 | - |
dc.identifier.uri | http://hdl.handle.net/2433/243265 | - |
dc.description.abstract | As the adoption of digital learning materials in modern education systems is increasing, the analysis of reading behavior and their effect on student performance gains attention. The main motivation of this workshop is to foster research into the analysis of students’ interaction with digital textbooks, and find new ways in which it can be used to inform and provide meaningful feedback to stakeholders, such as: teachers, students and researchers. In this workshop, participants analyzed the event logs from three different universities datasets with information on over 1000 students reading behaviors. Additional information on lecture schedules were also provided to enable the analysis of learning context for further insights into the preview, in-class, and review reading strategies that learners employ. Finally, workshop contributors were encouraged to implement their research results as a feature of an open LA dashboard. | en |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Society for Learning Analytics Research (SoLAR) | en |
dc.rights | This manuscript is distributed under the terms of the Creative Commons Attribution- Noncommercial-ShareAlike 3.0 Australia Licence. | en |
dc.rights | この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 | ja |
dc.rights | This is not the published version. Please cite only the published version. | en |
dc.subject | Student Performance Prediction | en |
dc.subject | Data Challenge | en |
dc.subject | Reading Behavior | en |
dc.title | Predicting Performance Based on the Analysis of Reading Behavior: A Data Challenge | en |
dc.type | conference paper | - |
dc.type.niitype | Conference Paper | - |
dc.identifier.jtitle | Companion Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19) | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 4 | - |
dc.textversion | author | - |
dc.address | Kyoto University | en |
dc.address | Kyushu University | en |
dc.address | National Central University | en |
dc.address | Asia University | en |
dc.address | Asia University | en |
dc.address | Kyoto University | en |
dc.relation.url | https://lak19.solaresearch.org/ | - |
dcterms.accessRights | open access | - |
datacite.awardNumber | 16H06304 | - |
jpcoar.funderName | 日本学術振興会 | ja |
jpcoar.funderName.alternative | Japan Society for the Promotion of Science (JSPS) | en |
出現コレクション: | 学術雑誌掲載論文等 |
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