Abstract:

In the fall of 2015, after the first launch of the online courses by al-Farabi Kazakh National University, we began to look for a methodology for evaluating the quality of the developed courses. Usually after the completion of the course, an online survey of students is conducted with the help of which you can get an initial picture of the external evaluation. In addition, review and feedback from active listeners about the course are also important when assessing components of the online course: video, activities, assessments, forum, and i.e. But analyzing learning activities data from MOOCs and comparison with the external evaluation allows to obtain more adequate results for the course evaluation.

While MOOCs offer educational data on a new scale, many educators find great potential of the big data including detailed activity records of every learner. This data can be used for educational research, learners behaviour prediction, detection and prevention of various cheating in MOOCs, and also for revising course content.

In this work, we describe how we were able to use students’ learning data in the evaluation of the online courses and revising course content.

Keywords:

MOOCs, Course Quality, Instructional Design, Data Analysis.