Evaluation of a learning analytics application in Korea : framework analysis프레임워크 분석을 통한 한국 learning analytics 어플리케이션에 대한 평가

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dc.contributor.advisorKim, Minki-
dc.contributor.advisor김민기-
dc.contributor.authorChung, Ha Eun-
dc.date.accessioned2021-05-13T19:35:32Z-
dc.date.available2021-05-13T19:35:32Z-
dc.date.issued2020-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=911515&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/284843-
dc.description학위논문(석사) - 한국과학기술원 : 경영공학부, 2020.2,[iii, 34 p. :]-
dc.description.abstractConcurrent with the development of the fields of Learning Analytics (LA) and Educational Data Mining (EDM), the monitoring of student behavior is now considered critical in improving student learning and offering personalized learning. In this paper, two learning analytics frameworks are presented as fundamental guides in designing and evaluating LA applications. The frameworks are evaluated both in theory and from the perspective of a real-life LA application that has been implemented in Korea. Distinct from the general trend of analyzing LA in secondary or tertiary educational level, this paper demonstrates that the frameworks need to be adjusted and extended to include areas and issues specific to primary education.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectLearning Analytics▼aStudent Learning Experience▼aPrimary Education▼aEducational Data Mining▼aPersonalized Learning-
dc.subject학습분석▼a학습경험▼a초등교육▼a교육데이터마이닝▼a맞춤형학습-
dc.titleEvaluation of a learning analytics application in Korea-
dc.title.alternative프레임워크 분석을 통한 한국 learning analytics 어플리케이션에 대한 평가-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :경영공학부,-
dc.contributor.alternativeauthor정하은-
dc.title.subtitleframework analysis-
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