Micro learning adaptation in MOOC: A software as a service and a personalized learner model

Sun, G; Cui, T; Guo, W; Beydoun, G; Xu, D; Shen, J

Micro learning adaptation in MOOC: A software as a service and a personalized learner model

Sun, G Cui, T Guo, W Beydoun, G

Xu, D Shen, J

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 9412 pp. 174 - 184
Issue Date:: 2015-01-01

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Field	Value	Language
dc.contributor.author	Sun, G	en_US
dc.contributor.author	Cui, T	en_US
dc.contributor.author	Guo, W	en_US
dc.contributor.author	Beydoun, G https://orcid.org/0000-0001-8087-5445	en_US
dc.contributor.author	Xu, D	en_US
dc.contributor.author	Shen, J https://orcid.org/0000-0002-9403-7140	en_US
dc.date.issued	2015-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 9412 pp. 174 - 184	en_US
dc.identifier.isbn	9783319255149	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120765
dc.description.abstract	© Springer International Publishing Switzerland 2015. Micro learning is gradually becoming a common learning mode in massive open online course learning (MOOC). We illustrate a research strategy to formalize and customize micro learning resources in order to meet personal demands at the real time. This smart micro learning environment can be organized by a Software as a Service (SaaS) we newly designed, in which educational data mining technique is mainly employed to understand learners learning behaviors and recognize learning resource features in order to identify potential micro learning solutions. A learner model with regards to internal and external factors is also proposed for personalization in micro MOOC learning context.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-25515-6_16	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Micro learning adaptation in MOOC: A software as a service and a personalized learner model	en_US
dc.type	Conference Proceeding
utslib.citation.volume	9412	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	0806 Information Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
pubs.organisational-group	/University of Technology Sydney/Strength - PERSWADE - Centre on Persuasive Systems for Wise Adaptive Living
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	9412	en_US

Abstract:

© Springer International Publishing Switzerland 2015. Micro learning is gradually becoming a common learning mode in massive open online course learning (MOOC). We illustrate a research strategy to formalize and customize micro learning resources in order to meet personal demands at the real time. This smart micro learning environment can be organized by a Software as a Service (SaaS) we newly designed, in which educational data mining technique is mainly employed to understand learners learning behaviors and recognize learning resource features in order to identify potential micro learning solutions. A learner model with regards to internal and external factors is also proposed for personalization in micro MOOC learning context.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/120765