Improving students' learning approaches through intervention in an information systems learning environment

Abstract

A study is reported which aimed to improve the proportion of students using aspects of deep learning approaches in an undergraduate information systems (IS) subject. Underlying the study was relational learning research, which identified learning environment factors more likely to be perceived by students who adopted deep learning approaches. These factors were used to design, and refine over five years, small‐scale interventions to the IS subject’s learning environment. To investigate the impact of the interventions students’ learning approaches were evaluated each year on the basis of responses to short written answer and Likert‐scale questionnaire items. In the fifth year of the study a statistically significant increase in the proportion of students using aspects of deep learning approaches was identified. Among a number of important learning environment factors, perception of workload appeared to be a key to encouraging the use of deep learning approaches. Through gradually decreasing the workload in the subject each year, a point was reached where enough educationally critical content was covered to satisfy the subject aims, but significantly more students perceived they had enough time to apply deep learning approaches.

Acknowledgements

This teaching initiative was supported financially by a Teaching Development Fellowship grant from the La Trobe University, Bendigo Teaching Committee and by the School of Management, Technology and Environment Research Advisory Group. Thanks are extended to Dr Graeme Byrne, Division of Mathematics, La Trobe University, Bendigo, for assistance with the statistics in the project.