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Students’ preferences for attributes of postgraduate economics modules: Evidence from a multi-profile best-worst scaling survey

Keila Meginnis and Danny Campbell ()

International Review of Economics Education, 2017, vol. 24, issue C, 18-27

Abstract: In this study, we investigate Scottish postgraduate economics students’ preferences for module design. Using a multi-profile best-worst scaling survey, we find that students have clear preferences on how they wish their modules to be delivered, taught and assessed. Furthermore, using a discrete mixtures modelling approach we explain the heterogeneous nature of preferences for the module attributes and the students’ lexicographic preference orderings. We show how failing to address this leads to erroneous results and limits the ability to derive reliable prediction. The findings in this study should appeal to university staff involved in the design of postgraduate (as well as undergraduate) courses as it should help them better establish a coherent learning experience for students, through which students can attain their full academic potential.

Keywords: Taught postgraduate; Module choice; Student's preferences; Multi-profile best-worst scaling; Discrete mixtures model; Attribute non-attendance (search for similar items in EconPapers)
JEL-codes: C25 I21 I23 (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1016/j.iree.2016.11.001

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