Optimization of Online Course Content According to Users Activity Statistics
https://doi.org/10.31992/0869-3617-2019-28-8-9-119-127
Abstract
Digitalization of modern education leads to a change in the style of the educational activities of students and professional work of higher school teachers. The professional standard of education workers oblige educators not only to develop educational content discipline, but also apply ICT to manage student’s training activity. The aim of the research was to study the capacity of the standard user statistics tool in LMS MOODLE for course optimization on three parameters – content presentation, temporary course structure and quality of educational measurement tools. These options, according to the authors, are the main factors for users’ motivation to consistent use of online courses during the semester. The study of statistical characteristics of student activity in e-course “Informatics” based on LMS MOODLE has been carried out during three years. The experiment covered the first-year students enrolled in the “Electricity and Electrical Equipment”. The results of the content optimization and presentation of the discipline have shown a positive change in the dynamics of the student’s activity during the semester. The findings of this study have a number of practical implications. Optimization of the learning process with the use of online course requires designing of a course with week module structure and singled out micro-targets. The learning material should be presented in various formats taking into account students’ preference for infographics. This contributes to raising the academic performance on the whole. Statistical analysis of test tasks differentiating capacity will substantially improve the quality of tools for educational measurement. It is shown that the use of a MOODLE statistics tool to estimate the user activity makes it possible the documented testing the effectiveness of innovations in pedagogical design of e-course.
About the Authors
V. A. StarodubtsevRussian Federation
Vyacheslav A. Starodubtsev – Dr. Sci. (Education), Prof.
30, Lenin prosp., Tomsk, 634050
О. В. Lobanenko
Russian Federation
Olga B. Lobanenko –Chief Programmer
30, Lenin prosp., Tomsk, 634050
О. V. Sitnikova
Russian Federation
Oksana V. Sitnikova – Cand. Sci. (Engineering), Assoc. Prof.
30, Lenin prosp., Tomsk, 634050
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