06 SES 03, E-Participation in Higher Education
Massive open online courses (MOOCs) are becoming increasingly popular: there are growth in the number of offered online courses, growth in the number of organizations, joining online course creation. MOOCs are popular at both international and national levels (there are some national online platforms, for example, Chinese online learning platform, Russian online platform based on OpenEdx, created by leading Russian universities). However, the dropout rate in MOOCs remains high, reaching 95% among the registered participants and 85% among participants, who plan to reach the end of the course. High dropout rate in many respects arouses criticism of this format of translating knowledge among the general public because the level of dropout is related to the course efficacy [Schmid et al., 2015]. However MOOCs are specific format of online course and not every registered participant has intention of completing the course. Studies, conducted in the context of MOOCs, show that, firstly, every registered participant does not visit the website of online course at least once [Xing, 2016]. Secondly, each student chooses his educational track, which may not be connected with completing the course [Kizilcec et al. 2013]. Therefore we can determine the efficacy of MOOCs and its successful completion as a function of the level of achievement desired by participant. In our research we define successful completion of MOOCs as obtaining required number of points to get a certificate by participant, who has an intention of completing the course (because such intention is amenable to direct operationalization).
We mark out two aggregative factors, which have an impact on the successful completion of MOOCs: 1) individual level, which includes characteristics of participants (for instance, educational background, socio-demographic parameters); 2) contextual level, which includes characteristics of online course (for instance, its duration, academic load). The “survival” process is influenced by both individual characteristics of online course participants and contextual parameters of the course [see for example, Semenova, Rudakova, 2015; Adamopoulos, 2013; Dillahunt et al., 2014]. However works aimed at studying the effect of both individual and contextual factors are usually limited by small set of indicators due to the lack of data about the characteristics of the online course participants or by the small sample [Gütl et al., 2014; Alraimi et al., 2015]. In this research, we show the cumulative effect of individual and contextual factors on the dropout rate in MOOCs, analyzing not only socio-demographic characteristics of participants, but also their educational background, online learning experience, purpose for which the course has been chosen. Since our database includes information about participants of 20 different MOOCs, the analysis result does not depend on the specific of online course.
1. Schmid L., Manturuk K., Simpkins I., Goldwasser M., Whitfield K. E. Fulfilling the promise: do MOOCs reach the educationally underserved? //Educational Media International. 2015. Vol. 52. № 2. Pp. 116-128. 2. Xing W., Chen X., Stein J., Marcinkowski M. Temporal predication of dropouts in MOOCs: Reaching the low hanging fruit through stacking generalization //Computers in Human Behavior. 2016. Vol. 58. Pp. 119-129. 3. Kizilcec R. F., Piech C., Schneider E. Deconstructing disengagement: analyzing learner subpopulations in massive open online courses. In Proceedings of the third international conference on learning analytics and knowledge. 2013, April. Pp. 170-179. 4. Semenova T.V., Rudakova L.M. Barriers when taking massive open online courses (MOOCs) //Monitoring of Public Opinion: Economic and Social Changes. 2015. № 3. Pp. 35-48. 5. Adamopoulos P. What makes a great MOOC? An interdisciplinary analysis of student retention in online courses. Thirty Fourth International Conference on Information Systems. Milan. 2013. 6. Dillahunt T. R., Wang B. Z., Teasley S. Democratizing higher education: Exploring MOOC use among those who cannot afford a formal education //The International Review of Research in Open and Distributed Learning. 2014. Vol. 15. №. 5. 7. Gütl C., Rizzardini R. H., Chang V., Morales M. Attrition in MOOC: Lessons learned from drop-out students //In Learning Technology for Education in Cloud. 2014. MOOC and Big Data Springer International Publishing. Pp. 37-48. 8. Alraimi K. M., Zo H., Ciganek A. P. Understanding the MOOCs continuance: The role of openness and reputation //Computers & Education, 2015. Vol. 80. Pp. 28-38.
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