Patterns in students’ usage of lecture recordings: a cluster analysis of self-report data

Abstract

Students’ usage of lecture recordings can be characterised by usage frequency, repetitiveness and selectivity in watching, lecture attendance, and social context and location in which students watch the lecture recordings. At the University of Münster (Germany), the lecture recording service was evaluated over three semesters. The data were combined and used for a cluster analysis with the aim of being able to describe the students’ distinct usage patterns. The cluster analysis was performed using partitioning around medoids with Gower distance. Five clusters of students were identified, which differed mainly on the amount of lecture recordings watched, whether the lecture recordings were watched completely or partially, whether the recordings were watched once or multiple times, and the number of lectures the students missed. The five clusters are interpreted as representing different ways of utilising lecture recordings. The clustering provides a basis for investigating the usage of lecture recordings in the context of different approaches to learning and learning strategies.

Publication
Research in Learning Technology
Daniel Ebbert
Daniel Ebbert
PhD candidate at the University of South Australia

I am a PhD candidate at the University of South Australia’s Centre for Change and Complexity in Learning. Prior to my doctoral studies, I worked as a Research Associate and Systems Administrator supporting university lecturers with educational technology in Germany. My doctoral research explores the intersection of self-regulated learning and mind wandering during video-based learning, specifically examining how learners adapt their learning processes after recognizing mind wandering episodes. This research aims to develop evidence-based recommendations for effective responses to mind wandering during learning. Following my PhD, I plan to expand my research beyond video-based contexts to investigate the conditions under which self-regulated learners engage in task-level, ad-hoc adaptation of their learning processes.