What Learning Analytics Reveals About Adult Students in Online Higher Education

Author Information

Päivi Hurri, South-Eastern Finland University of Applied Sciences, Finland
Heli Bergström, South-Eastern Finland University of Applied Sciences, Finland
Jarkko Ansamäki, South-Eastern Finland University of Applied Sciences, Finland
Katariina Palmu, South-Eastern Finland University of Applied Sciences, Finland
Maisa Räsänen, South-Eastern Finland University of Applied Sciences, Finland

Abstract

Online learning has become an established part of higher education, offering flexible study opportunities that are particularly relevant for adult learners combining studies with work and family responsibilities. At the same time, digital learning environments generate detailed data that can be used to better understand student behaviour. This study examines adult students’ learning in an online higher education course by combining learning analytics with survey-based self-assessments. The dataset includes pre- and post-course surveys, video viewing data, learning platform activity logs, and course performance data from 23 students. The study explores how adult learners engage with course materials, how they assess their competence before and after the course, and how activity patterns relate to performance. The results show considerable variation in study behaviour, with activity concentrated around deadlines and weekends. Students initially assessed their competence critically, particularly in data analytics, but reported clear improvement by the end of the course. Initial self-assessments did not appear to clearly predict course success. The findings suggest that learning analytics can provide useful insights into adult learners’ engagement and progression, but its interpretive value depends on course design, assessment practices, and the technical implementation of the learning environment.

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