Micro Learning Adaptation in MOOC: A Software as a Service and a Personalized Learner Model

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. Disciplines Engineering | Science and Technology Studies Publication Details 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," Lecture Notes in Computer Science, vol. 9412, pp. 174-184, 2015. Authors Geng Sun, Tingru Cui, William Guo, Ghassan Beydoun, Dongming Xu, and Jun Shen This journal article is available at Research Online: http://ro.uow.edu.au/eispapers/5198 Micro Learning Adaptation in MOOC: a Software as a Service and a Personalized Learner Model Geng Sun, Tingru Cui, William Guo, Ghassan Beydoun, Dongming Xu, Jun Shen 1. School of Information Systems and Technology, University of Wollongong, Australia 2. School of Engineering and Technology, Central Queensland University, Australia 3. UQ Business School, the University of Queensland, Australia Abstract. 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 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.