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ICCE2020.1_289.pdf896.88 kBAdobe PDF見る/開く
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dc.contributor.authorYANG, Alberten
dc.contributor.authorCHEN, Y.L. Ireneen
dc.contributor.authorFLANAGAN, Brendanen
dc.contributor.authorOGATA, Hiroakien
dc.contributor.alternative緒方, 広明ja
dc.date.accessioned2020-12-15T05:58:57Z-
dc.date.available2020-12-15T05:58:57Z-
dc.date.issued2020-11-23-
dc.identifier.isbn9789869721455-
dc.identifier.urihttp://hdl.handle.net/2433/259795-
dc.description28th International Conference on Computers in Education, 23-27 November 2020, Web conference.en
dc.description.abstractMeasuring a student’s highlight quality is a way to understand how well a student understands the learning materials. In general, students highlight the words or sentences they consider as important concepts during their learning process. An often way to measure students’ highlight quality is to let graders give a highlight score after reading their highlights. However, when graders do not reach agreement on the quality of highlights and give different scores due to different background knowledge, the influence of highlight quality on learning performance may decrease. In this study, we explore the marker function on BookRoll and propose another way to grade students’ highlight quality in terms of its similarity to the reference answer. Students can add highlights as markers when reading learning materials. The instructor will highlight the important concepts in the learning materials as a reference answer. Graders will use this reference answer to grade students’ highlights. The average of students’ quiz scores will be used to denote their learning performance. The results indicate that the highlight quality has a larger influence on students’ learning performance than that of highlight frequency when graders evaluate the highlights along with a reference answer. Next, we divided students into two groups and performed a one-way ANOVA test to evaluate the influence of highlight quality on learning performance, and found that students who achieve high learning performance are also likely to achieve a high highlight score. We further compared the highlight quality and highlight frequency to see which indicator is more correlated with learning performance and found that highlight quality outperforms highlight frequency.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherAsia-Pacific Society for Computers in Education (APSCE)en
dc.rightsCopyright 2020 Asia-Pacific Society for Computers in Education.en
dc.rights許諾条件に基づいて掲載しています。ja
dc.subjecte-Book readingen
dc.subjectlearning analyticsen
dc.subjectlearning performanceen
dc.titleHow Does The Quality of Students’ Highlights Affect Their Learning Performance in e-Book Readingen
dc.typeconference paper-
dc.type.niitypeConference Paper-
dc.identifier.jtitle28th International Conference on Computers in Education Conference Proceedingsen
dc.identifier.volume1-
dc.identifier.spage289-
dc.identifier.epage294-
dc.textversionpublisher-
dc.addressGraduate School of Informatics, Kyoto Universityen
dc.addressDepartment of Accounting, National Changhua University of Educationen
dc.addressAcademic Center for Computing and Media Studies, Kyoto Universityen
dc.addressAcademic Center for Computing and Media Studies, Kyoto Universityen
dc.relation.urlHow Does The Quality of Students’ Highlights Affect Their Learning Performance in e-Book Reading-
dcterms.accessRightsopen access-
datacite.awardNumber16H06304-
jpcoar.funderName日本学術振興会ja
jpcoar.funderName.alternativeJapan 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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