|Appears in Collections:||Economics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Students’ preferences for attributes of postgraduate economics modules: Evidence from a multi-profile best-worst scaling survey|
multi-profile best-worst scaling
discrete mixtures model
|Citation:||Meginnis K & Campbell D (2017) Students’ preferences for attributes of postgraduate economics modules: Evidence from a multi-profile best-worst scaling survey, International Review of Economics Education, 24, pp. 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.|
|Rights:||This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Meginnis K & Campbell D (2017) Students’ preferences for attributes of postgraduate economics modules: Evidence from a multi-profile best-worst scaling survey, International Review of Economics Education, 24, pp. 18-27. DOI: 10.1016/j.iree.2016.11.001 © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/|
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.