What determines student satisfaction with university subjects? A choice-based approach

• Published in: Journal of choice modelling Vol. 17; pp. 52 - 65
• Main Authors: Huybers, Twan, Louviere, Jordan, Islam, Towhidul
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2015
• Subjects: Choice experiment; Methodology; Student evaluation of university teaching; Student satisfaction; Student satisfaction; Methodology; Student evaluation of university teaching; Choice experiment
• ISSN: 1755-5345; 1755-5345
• DOI: 10.1016/j.jocm.2015.10.001

In this paper, we report on a study of student satisfaction with university subjects and teaching. Quantitative analysis of student perceptions of university subjects traditionally has been based on instruments containing a list of items (statements) to which students respond in an item-by-item manner using Likert-type rating scales. The main purpose of this paper is methodological: we propose and apply a novel application of a discrete choice experiment (DCE) to evaluate and measure the individual contributions of various subject and teaching attributes on student satisfaction with higher education teaching experiences. We are not proposing the use of a DCE approach as an alternative to regular classroom evaluation exercises. Rather, we see the approach as complementary, especially because DCEs are an attempt to deal with rating scale related issues such as response styles and inter-item correlation. A representative Australia-wide sample of university students completed an evaluation ratings task (the “instrument”) and/or an evaluation DCE task (the “experiment”). Our results compare the findings of the instrument and experiment model estimations in terms of their ability to identify the relative importance of various evaluation items that drive student satisfaction. We also use a latent class analysis to explore differences in effects for sub-groups of students. •We propose a novel application of a choice experiment to model student satisfaction.•We compare and combine ratings and choice experiment data.•Choice data better discriminate individual contributions of attributes.