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dc.contributor.authorGiannakos, M.
dc.contributor.authorSampson, Demetrios
dc.contributor.authorKidzinski, L.
dc.date.accessioned2017-03-15T22:23:28Z
dc.date.available2017-03-15T22:23:28Z
dc.date.created2017-03-08T06:39:34Z
dc.date.issued2016
dc.identifier.citationGiannakos, M. and Sampson, D. and Kidzinski, L. 2016. Introduction to Smart Learning Analytics: Foundations and Developments in Video-Based Learning. Smart Learning Environments. 3: Article 12.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/50246
dc.description.abstract

Smart learning has become a new term to describe technological and social developments (e.g., Big and Open Data, Internet of Things, RFID, and NFC) enable effective, efficient, engaging and personalized learning. Collecting and combining learning analytics coming from different channels can clearly provide valuable information in designing and developing smart learning. Although, the potential of learning analytics to enable smart learning is very promising area, it remains non-investigated and even ill-defined concept. The paper defines the subset of learning analytics that focuses on supporting the features and the processes of smart learning, under the term Smart Learning Analytics. This is followed by a brief discussion on the prospects and drawbacks of Smart Learning Analytics and their recent foundations and developments in the area of Video-Based Learning. Drawing from our experience with the recent international workshops in Smart Environments and Analytics in Video-Based Learning, we present the state-of-the-art developments as well as the four selected contributions. The paper further draws attention to the great potential and need for research in the area of Smart Learning Analytics.

dc.titleIntroduction to Smart Learning Analytics: Foundations and Developments in Video-Based Learning
dc.typeJournal Article
dcterms.source.volume3
dcterms.source.titleSmart Learning Environments
curtin.departmentSchool of Education
curtin.accessStatusFulltext not available


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