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dc.contributor.authorChen, Weiqin
dc.date.accessioned2021-01-26T19:06:04Z
dc.date.accessioned2021-03-04T08:26:23Z
dc.date.available2021-01-26T19:06:04Z
dc.date.available2021-03-04T08:26:23Z
dc.date.issued2020-11-23
dc.identifier.citationChen W: Learning Analytics for Inclusive Higher Education. In: So H, Rodrigo, Mason J, MITROVIC A. Proceedings 28th International Conference on Computers in Education , 2020. Asia-Pacific Society for Computers in Education (APSCE) p. 113-118en
dc.identifier.isbn978-986-97214-6-2
dc.identifier.urihttps://apsce.net/icce/icce2020/index.html@p=2159.html
dc.identifier.urihttps://hdl.handle.net/10642/9851
dc.description.abstractLearning analytics is gaining attention and increasingly being adopted in higher educational institutions. Research have shown that learning analytics is promising in addressing high priority issues in education such as prediction of student retention, enrolments, and learning gains. However, learning analytics also presents barriers and challenges for students with disabilities which could prevent them from fully benefiting from learning analytics, hence create inequality in education. This position paper discusses the opportunities and challenges in learning analytics for inclusive higher education, focusing on students with disabilities.en
dc.language.isoenen
dc.publisherAsia-Pacific Society for Computers in Educationen
dc.relation.ispartofseries28th International Conference on Computers in Education;Workshop Proceedings Volume II
dc.subjectLearning analyticsen
dc.subjectDisabled studentsen
dc.subjectHigher educationen
dc.subjectInclusionen
dc.titleLearning Analytics for Inclusive Higher Educationen
dc.typeConference objecten
dc.date.updated2021-01-26T19:06:04Z
dc.description.versionacceptedVersionen
dc.identifier.cristin1873511
dc.source.isbn9789869721462


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