Key elements of e-learning course design that provides high-quality prediction of student learning success
Abstract
Statement of the problem. The task of predicting student learning success is one of the most developed in educational analytics. At the same time, experience in the field of pedagogical design of e-learning courses, which are the main sources of students’ digital footprint data, is extremely limited. In these conditions, understanding what it should be like and what design elements are most important for it is becoming relevant. The purpose of the study is to determine the design elements of an e-learning course for effective prediction of educational results and to develop its generalized criteria-content model. Methodology . A comparative analysis of scientific, pedagogical, and methodological sources was applied. Verbal and communicative methods, comparative and statistical analysis of empirical data using a generative model of artificial intelligence were used. Results . The paper substantiates the need to develop high-precision e-learning courses for effective forecasting of students’ learning success based on such design elements as: content availability, structuring, discipline study schedule, assessment system, timely feedback, relevance and completeness of information, aesthetics and ergonomics. A generalized criteria-content model for constructing a high-precision e-learning course is proposed. Conclusion . The prospects for further development of the research and development of methodological recommendations for the design of pedagogical design of high-precision e-learning courses are outlined.