IDEAS home Printed from https://ideas.repec.org/a/eee/ireced/v24y2017icp18-27.html
   My bibliography  Save this article

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

Author

Listed:
  • Meginnis, Keila
  • Campbell, Danny

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.

Suggested Citation

  • Meginnis, Keila & Campbell, Danny, 2017. "Students’ preferences for attributes of postgraduate economics modules: Evidence from a multi-profile best-worst scaling survey," International Review of Economics Education, Elsevier, vol. 24(C), pages 18-27.
  • Handle: RePEc:eee:ireced:v:24:y:2017:i:c:p:18-27
    DOI: 10.1016/j.iree.2016.11.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1477388016300329
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iree.2016.11.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hess, S. & Bierlaire, Michel & Polak, J.W., 2007. "A systematic comparison of continuous and discrete mixture models," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 37, pages 35-61.
    2. Mohammed Alemu & Morten Mørkbak & Søren Olsen & Carsten Jensen, 2013. "Attending to the Reasons for Attribute Non-attendance in Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 54(3), pages 333-359, March.
    3. Danny Campbell & David A. Hensher & Riccardo Scarpa, 2011. "Non-attendance to attributes in environmental choice analysis: a latent class specification," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 54(8), pages 1061-1076, December.
    4. Stephane Hess & Amanda Stathopoulos & Danny Campbell & Vikki O’Neill & Sebastian Caussade, 2013. "It’s not that I don’t care, I just don’t care very much: confounding between attribute non-attendance and taste heterogeneity," Transportation, Springer, vol. 40(3), pages 583-607, May.
    5. Thomas Lemieux, 2006. "Postsecondary Education and Increasing Wage Inequality," American Economic Review, American Economic Association, vol. 96(2), pages 195-199, May.
    6. Maureen J. Lage & Glenn J. Platt & Michael Treglia, 2000. "Inverting the Classroom: A Gateway to Creating an Inclusive Learning Environment," The Journal of Economic Education, Taylor & Francis Journals, vol. 31(1), pages 30-43, December.
    7. Danny Campbell & W. Hutchinson & Riccardo Scarpa, 2008. "Incorporating Discontinuous Preferences into the Analysis of Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 41(3), pages 401-417, November.
    8. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
    9. Danny Campbell & Edel Doherty, 2013. "Combining discrete and continuous mixing distributions to identify niche markets for food," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 40(2), pages 287-312, March.
    10. Stephane Hess & David Hensher, 2013. "Making use of respondent reported processing information to understand attribute importance: a latent variable scaling approach," Transportation, Springer, vol. 40(2), pages 397-412, February.
    11. David Hensher & John Rose & William Greene, 2005. "The implications on willingness to pay of respondents ignoring specific attributes," Transportation, Springer, vol. 32(3), pages 203-222, May.
    12. David Hensher & John Rose & William Greene, 2012. "Inferring attribute non-attendance from stated choice data: implications for willingness to pay estimates and a warning for stated choice experiment design," Transportation, Springer, vol. 39(2), pages 235-245, March.
    13. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    14. Campbell, Danny & Hensher, David A. & Scarpa, Riccardo, 2012. "Cost thresholds, cut-offs and sensitivities in stated choice analysis: Identification and implications," Resource and Energy Economics, Elsevier, vol. 34(3), pages 396-411.
    15. Flannery, Darragh & Kennelly, Brendan & Doherty, Edel & Hynes, Stephen & Considine, John, 2013. "Of mice and pens: A discrete choice experiment on student preferences for assignment systems in economics," International Review of Economics Education, Elsevier, vol. 14(C), pages 57-70.
    16. Riccardo Scarpa & Raffaele Zanoli & Viola Bruschi & Simona Naspetti, 2013. "Inferred and Stated Attribute Non-attendance in Food Choice Experiments," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 165-180.
    17. Riccardo Scarpa & Timothy J. Gilbride & Danny Campbell & David A. Hensher, 2009. "Modelling attribute non-attendance in choice experiments for rural landscape valuation," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 36(2), pages 151-174, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sandorf, Erlend Dancke & Campbell, Danny & Hanley, Nick, 2017. "Disentangling the influence of knowledge on attribute non-attendance," Journal of choice modelling, Elsevier, vol. 24(C), pages 36-50.
    2. Collins, Andrew T. & Rose, John M. & Hensher, David A., 2013. "Specification issues in a generalised random parameters attribute nonattendance model," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 234-253.
    3. Klaus Glenk & Julia Martin-Ortega & Manuel Pulido-Velazquez & Jacqueline Potts, 2015. "Inferring Attribute Non-attendance from Discrete Choice Experiments: Implications for Benefit Transfer," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 60(4), pages 497-520, April.
    4. Logar, Ivana & Brouwer, Roy & Campbell, Danny, 2020. "Does attribute order influence attribute-information processing in discrete choice experiments?," Resource and Energy Economics, Elsevier, vol. 60(C).
    5. Sandorf, Erlend Dancke & Crastes dit Sourd, Romain & Mahieu, Pierre-Alexandre, 2018. "The effect of attribute-alternative matrix displays on preferences and processing strategies," Journal of choice modelling, Elsevier, vol. 29(C), pages 113-132.
    6. Seda Erdem & Danny Campbell & Arne Risa Hole, 2015. "Accounting for Attribute‐Level Non‐Attendance in a Health Choice Experiment: Does it Matter?," Health Economics, John Wiley & Sons, Ltd., vol. 24(7), pages 773-789, July.
    7. Glenk, Klaus & Meyerhoff, Jürgen & Akaichi, Faical & Martin-Ortega, Julia, 2019. "Revisiting cost vector effects in discrete choice experiments," Resource and Energy Economics, Elsevier, vol. 57(C), pages 135-155.
    8. David Hensher, 2014. "Attribute processing as a behavioural strategy in choice making," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 12, pages 268-289, Edward Elgar Publishing.
    9. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 46(1), pages 133-162.
    10. Caputo, Vincenzina & Loo, Ellen J. Van & Scarpa, Riccardo & Nayga, Rodolfo M. Jr & Verbeke, Wim, 2014. "“Using Experiments to Address Attribute Non-attendance in Consumer Food Choices”," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 177173, Agricultural and Applied Economics Association.
    11. Gonçalves, Tânia & Pinto, Lígia M. Costa & Lourenço-Gomes, Lina, 2020. "Attribute non-attendance in wine choice: Contrasts between stated and inferred approaches," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 262-275.
    12. Colombo, Sergio & Christie, Michael & Hanley, Nick, 2013. "What are the consequences of ignoring attributes in choice experiments? Implications for ecosystem service valuation," Ecological Economics, Elsevier, vol. 96(C), pages 25-35.
    13. Hole, Arne Risa & Kolstad, Julie Riise & Gyrd-Hansen, Dorte, 2013. "Inferred vs. stated attribute non-attendance in choice experiments: A study of doctors’ prescription behaviour," Journal of Economic Behavior & Organization, Elsevier, vol. 96(C), pages 21-31.
    14. Erdem, Seda & Campbell, Danny & Thompson, Carl, 2014. "Elimination and selection by aspects in health choice experiments: Prioritising health service innovations," Journal of Health Economics, Elsevier, vol. 38(C), pages 10-22.
    15. Nguyen, Thanh Cong & Robinson, Jackie & Whitty, Jennifer A. & Kaneko, Shinji & Nguyen, The Chinh, 2015. "Attribute non-attendance in discrete choice experiments: A case study in a developing country," Economic Analysis and Policy, Elsevier, vol. 47(C), pages 22-33.
    16. Erdem, Seda & Campbell, Danny & Thompson, Carl, 2014. "Addressing elimination and selection by aspects decision rules in discrete choice experiments: does it matter?," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169839, Agricultural and Applied Economics Association.
    17. Weller, Priska & Oehlmann, Malte & Mariel, Petr & Meyerhoff, Jürgen, 2014. "Stated and inferred attribute non-attendance in a design of designs approach," Journal of choice modelling, Elsevier, vol. 11(C), pages 43-56.
    18. Gonçalves, Tânia & Lourenço-Gomes, Lina & Pinto, Lígia M. Costa, 2020. "Dealing with ignored attributes through an inferred approach in wine choice experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 87(C).
    19. Grammatikopoulou, Ioanna & Pouta, Eija & Artell, Janne, 2019. "Heterogeneity and attribute non-attendance in preferences for peatland conservation," Forest Policy and Economics, Elsevier, vol. 104(C), pages 45-55.
    20. Yegoryan, Narine & Guhl, Daniel & Klapper, Daniel, 2018. "Inferring Attribute Non-Attendance Using Eye Tracking in Choice-Based Conjoint Analysis," Rationality and Competition Discussion Paper Series 111, CRC TRR 190 Rationality and Competition.

    More about this item

    Keywords

    Taught postgraduate; Module choice; Student's preferences; Multi-profile best-worst scaling; Discrete mixtures model; Attribute non-attendance;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ireced:v:24:y:2017:i:c:p:18-27. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.journals.elsevier.com/international-review-of-economics-education .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/international-review-of-economics-education .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.