1,347
Views
22
CrossRef citations to date
0
Altmetric
Articles

Connecting the dots: using concept maps for interpreting student satisfaction

, &
Pages 225-247 | Published online: 26 Jun 2013
 

Abstract

This study utilised concept mapping software to aid interpretation of the qualitative data from student satisfaction surveys. The analysis revealed differences in student priorities and attitudes across the three years of an undergraduate degree. First-year students were more concerned with social and academic integration and demonstrated an emotional response to their engagement with higher education. Comments from second-year students indicated an emphasis on academic progress and development, while final-year students were focused on achievement-oriented learning. Critical aspects of the student experience hidden between survey questions were also revealed. The paper discusses the implications of the findings for understanding the changing interaction between different aspects of student experience and satisfaction. It concludes with suggestions on how this approach to analysis might benefit the work of quality assurance teams and academic developers in other institutions.

Acknowledgements

The authors are grateful to the two anonymous referees, the Editor and Professor Mantz Yorke for constructive comments on the earlier drafts of this paper. This work was supported by the HEFCE-funded National Teaching Fellowship Scheme project ‘The Forgotten Year: Tackling the Sophomore Slump’.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 480.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.