Personalised Learning on MOOCs
Song, Yiyun (2017)
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The aim of this thesis is to investigate the elements for realizing personalised learning and to figure out whether they have been applied on MOOCs. A web questionnaire was distributed to different MOOCs learning communities and individual learners during the spring of 2017. Thirty answer sheets have been selected and analyzed. The results show that there is no correlation between learners’ model (personal data and information) and different presentations of the contents and different experiences of navigation on MOOCs. Findings also support the idea that personal traits (learning styles, cognitive styles, etc.) are difficult to be inserted for adaptive hypermedia systems which are the technical foundation for realizing personalised learning. However, the collected data also suggest that course design strategies for MOOCs cater to individual needs and preferences. In other words, the adaptive instructions which serve for personalised learning have been adopted on MOOCs. This research provided an insight of how personalised learning could be realized on e-learning platforms from the educational view. However, the researcher recommends further research on depth study of individual cases and updated issues concerning this field.
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