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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sun, G. Tingru Cui Jianming Yong Jun Shen Shiping Chen |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Manage. & Enterprise, Univ. of Southern Queensland, Toowoomba, QLD, Australia (Jianming Yong) || Sch. of Inf. Syst. & Technol., Univ. of Wollongong, Wollongong, NSW, Australia (Sun, G.; Tingru Cui; Jun Shen) || ICT Centre, CSIRO, Sydney, NSW, Australia (Shiping Chen) |
| Abstract | Recently the massive open online course (MOOC) is an emerging trend that attracts many educators' and researchers' attentions. Based on our pilot study focusing on the development and operation of MOOC in Australia, we found MOOC is featured with mastery learning and blended learning, but it suffers from low completion rates. Brining micro learning into MOOC can be a feasible solution to improve current MOOC delivery and learning experience. We design a system which aims to provide adaptive micro learning contents as well as learning path identifications customized for each individual learner. To investigate how micro learning can impact learning experience and knowledge acquisitions of learners participated in MOOC, we suggest a potential scheme including hypotheses to evaluate our proposed approach. |
| Starting Page | 308 |
| Ending Page | 313 |
| File Size | 880653 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479920020 |
| DOI | 10.1109/CSCWD.2015.7230977 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-06 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Education Lead World Wide Web Australia Data mining Resource Adaptation MOOC Mastery Learning Blended Learning Micro Learning |
| Content Type | Text |
| Resource Type | Article |
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