LEARNERS’ INTERACTIONS IN MASSIVE OPEN ONLINE COURSES: ANALYSIS AND INTERPRETATION

Anna Shurtina, Andrey Lyamin, Elena Cherepovskaya

Abstract


The research is devoted to the study of data on learners’ interactions in massive open online courses. Based on the logs of online-learning platforms, the following research was made: a comparison of the behaviour of motivated and unmotivated learners regarding of video lectures, identification of the most valuable for the successful completion of the course activities of learners, creating a model of going through time-limited assignments and identification of cheating approach based on this model. The following conclusions were made: motivated and unmotivated learners watch video lectures in different ways, motivated learners appeared to be 14 times more active, the most interesting and most viewable videos were revealed. When identifying the most valuable theoretical materials influencing the successful completion of the course, the following results were obtained: some of the videos have a strong influence on the successful completion of the final assignment. Some of the videos appeared to have weak effect, they can be interpreted as non-obligatory. Ungraded tests have a positive but moderate effect on learners’ success, while communication via discussion forum has no effect at all. In addition, a model of going through time-limited assignments was built using the average passing time of reliable learners, the approach for identifying cheating with examples is presented in the study.

Keywords


learning analytics; MOOC

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References


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DOI: http://dx.doi.org/10.17770/etr2019vol2.4047

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