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dc.contributor.authorHSU, Chia-Yuen
dc.contributor.authorHORIKOSHI, Izumien
dc.contributor.authorLI, Huiyongen
dc.contributor.authorMAJUMDAR, Rwitajiten
dc.contributor.authorOGATA, Hiroakien
dc.contributor.alternative許, 嘉瑜ja
dc.contributor.alternative堀越, 泉ja
dc.contributor.alternative李, 慧勇ja
dc.contributor.alternative緒方, 広明ja
dc.date.accessioned2023-10-17T07:20:26Z-
dc.date.available2023-10-17T07:20:26Z-
dc.date.issued2023-03-04-
dc.identifier.urihttp://hdl.handle.net/2433/285538-
dc.description.abstractThe development of technology enables diverse learning experiences nowadays, which shows the importance of learners’ self-regulated skills at the same time. Particularly, the ability to allocate time properly becomes an issue for learners since time is a resource owned by all of them. However, they tend to struggle to manage their time well due to the lack of awareness of its existence. This study, hence, aims to reveal how learners allocate their time and evaluate the effectiveness of the time allocation by examining its effects on learners’ performance. We collect the learning logs of 116 seventh-graders from the online learning system implemented in a Japanese public junior high school. We look at the data in the time window of 34 days before the regular exam. Even though clustering techniques as a Learning Analytics method help identify different groups of learners, it is seldom applied to group students’ learning patterns with different levels of indicators extracted from their learning process data. In this study, we adopt the method to cluster students’ patterns of time allocation and find that better performance can result from the consistency of study time throughout the exam preparation period. Practical suggestions are then proposed for different roles involved in digital learning environments to facilitate students’ time management. Collectively, this study is expected to make contributions to smart learning environments supporting self-regulated learning in the digital era.en
dc.language.isoeng-
dc.publisherSpringer Natureen
dc.rights© The Author(s) 2023en
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/-
dc.subjectLearning analyticsen
dc.subjectTime awarenessen
dc.subjectTime allocationen
dc.subjectSelf-regulated learningen
dc.subjectTime managementen
dc.titleSupporting “time awareness” in self-regulated learning: How do students allocate time during exam preparation?en
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleSmart Learning Environmentsen
dc.identifier.volume10-
dc.relation.doi10.1186/s40561-023-00243-z-
dc.textversionpublisher-
dc.identifier.artnum21-
dcterms.accessRightsopen access-
datacite.awardNumber22H03902-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22H03902/-
dc.identifier.eissn2196-7091-
jpcoar.funderName日本学術振興会ja
jpcoar.awardTitleGOAL project: AI-supported self-directed learning lifestyle in data-rich educational ecosystemen
出現コレクション:学術雑誌掲載論文等

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