Integration of personalized adaptive learning elements into the electronic educational content of a college mathematics course on the Stepik platform

Abstract

This study aims to evaluate the effectiveness of integrating elements of adaptive personalized learning into a college-level electronic mathematics course delivered via the Stepik platform for first-year students in technical fields. The research combined theoretical analysis of adaptive learning principles with experimental implementation. An electronic course was developed with integrated adaptive elements, and a pedagogical experiment was conducted with first-year college students, during which students' progress was monitored through automated settings in Stepik, and data were collected via diagnostic assessments, surveys, and observations. The findings demonstrate that the integration of adaptive personalization elements led to a noticeable improvement in students' mathematical competence, with an increase in the proportion of students achieving high and medium competence levels and a significant reduction in the number of students with a low competence level. The study concludes that incorporating adaptive personalized learning into electronic courses enhances the effectiveness of blended mathematics education, fosters student motivation, and supports the development of independent learning skills. The practical implications suggest that adaptive personalization strategies, implemented through platforms like Stepik, can effectively promote student-centered learning and improve educational outcomes in college mathematics courses.