A Study of the Effectiveness of Massive Open Online Courses Support Models

The study aims to identify, test, and evaluate the effectiveness of current learner support models of online courses based on the analysis of online courses from the leading platforms, and to identify relevant support tools both built into online learning platforms and outside platforms. The study is based on the hypothesis that it is possible to increase students' engagement rate in online learning using the platform data, the patterns of student behavior on MOOCs, and various user support tools. The study employed the following methods: questionnaire survey, data analysis, descriptive statistics, cluster analysis, visualization, and comparative analysis. The study was carried out in four stages. At the first stage, the authors of the article subscribed to MOOCs on 9 platforms and observed the tools used to support listeners. Using the collected data, they constructed a matrix of correspondence of courses and used support tools and made a list of the most common listener support tools in MOOCs. At the second stage, the authors conducted a survey to identify students' perceptions of and expectations from various support tools in the MOOC on the Coursera and Lectorium platforms. The confidence level was 97%, the confidence interval was 8%. The authors learned that there was a request from learners for new tools that would make communication more efficient and support more individualized. At the third stage, the authors used the principles of electronic moderation by Gilly Salmon and the result of the analysis of the most frequently used and most demanded support tools on platforms with a view to design three models of MOOC listener support. The platform, off-platform and mixed models were developed. At the fourth stage, the authors conducted a pedagogical experiment to test the developed support models. The cluster analysis method revealed patterns of listeners' behavior before using the three support models (control group) and during the application of these models (experimental group). The behavior patterns of students of each of the six MOOCs were considered in the context of one of the support models. The emphasis was on the behavior of students in completing assignments and in viewing video lectures as key characteristics of the educational activities of students of online courses. The experiment showed the non-viability of the off-platform tracking model, the low efficiency of the platform model. A comparative analysis of the behavior patterns of the control and experimental groups showed that maximum efficiency was achieved with a mixed support model: the engagement rate of students increased, which is manifested in the number of students who completed more than 10% of the tasks and/or completed the course. The increase averaged over 2%. It is necessary to build learner support on a mixed basis, combining the resources of online platforms and ecosystem agents that can be integrated into online platforms.

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