This study presents a large-scale descriptive analysis of the use of an AI-based learning assistant (Syntea) in higher education. Based on objective log data from 77,543 students enrolled in distance studies, we examine usage patterns across gender, age group, study cluster, degree, and study mode.
Existing research on educational chatbots has largely relied on comparatively small samples and self-reported survey data, while large-scale evidence on actual usage behavior remains limited. Our findings show that Syntea is already embedded in the study routines of many learners, but that usage differs across demographic and structural contexts.
By identifying these patterns, our study provides an empirical basis for the further development of AI-based learning support and contributes a large-scale analysis of educational chatbot usage in higher education.
Blogger's Review: This research vividly illustrates the real-world application of AI learning assistants in higher education through large-scale data analysis, providing essential empirical support for the future development of educational technology. The in-depth exploration of usage differences among various demographics can help educators design more personalized learning experiences.