Alternative data-analysis techniques in research on student learning: illustrations of a person-oriented and developmental perspectives

Gert Vanthournout, Vincent Donche, David Gijbels, Peter Van Petegem


Studies on student learning in higher education from a student approaches to a learning tradition have yielded valuable insights, although research remains inconclusive on how to incite a deep approach in students. To broaden our insights into student learning, two alternative research perspectives are explored: 1) a person-oriented approach to data analysis aimed at identifying subgroups of students with similar learning profiles, and 2) a developmental approach interested in the stability and variability of students?ǨѢ approaches to learning. The usefulness and value of combining these perspectives is illustrated using research findings from two recent studies in a Flemish context. The first study investigated the development of learning profiles in a specific course using the Revised Two Factor Study Process Questionnaire (R-SPQ-2F), based on the model of John Biggs (2001). The second study explored the evolution in learning patterns throughout a whole teacher-education programme using Jan Vermunt?ǨѢs Inventory of Learning Styles (ILS) (Vermunt, 1996). Both studies identified the existence of sub-groups of students with similar learning profiles and point towards different developmental trends for these profiles. Moreover, the second study showed that some parts of students?ǨѢ learning patterns are more prone to changes than others. For educational practice, the exploration of these profiles and the monitoring of their development might prove an interesting diagnostic tool for choosing, designing and implementing adaptive instructional methods and remedial trajectories in an evidence-based way.

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Editor-in-Chief: Prof Norbert Pachler
UCL Institute of Education, University College London
ISSN 1746-9082