Text mining in students' course evaluations: Relationships between open-ended comments and quantitative scores

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Abstract

Extensive research has been done on student evaluations of teachers and courses based on quantitative data from evaluation questionnaires, but little research has examined students' written responses to open-ended questions and their relationships with quantitative scores. This paper analyzes such kind of relationship of a well established course at the Technical University of Denmark using statistical methods. Keyphrase extraction tool was used to find the main topics of students' comments, based on which the qualitative feedback was transformed into quantitative data for further statistical analysis. Application of factor analysis helped to reveal the important issues and the structure of the data hidden in the students' written comments, while regression analysis showed that some of the revealed factors have a significant impact on how students rate a course.
Original languageEnglish
Title of host publicationCSEDU 2013 - Proceedings of the 5th International Conference on Computer Supported Education
PublisherSciTePress
Publication date2013
Pages564-573
ISBN (Print)9789898565532
Publication statusPublished - 2013
Event5th International Conference on Computer Supported Education (CSEDU 2013) - Aachen, Germany
Duration: 6 May 20138 May 2013
http://www.csedu.org/?y=2013

Conference

Conference5th International Conference on Computer Supported Education (CSEDU 2013)
CountryGermany
CityAachen
Period06/05/201308/05/2013
Internet address

Keywords

  • Data mining
  • Extraction
  • Factor analysis
  • Multivariant analysis
  • Regression analysis
  • Surveys
  • Teaching
  • Students

Cite this

Sliusarenko, T., Clemmensen, L. K. H., & Ersbøll, B. K. (2013). Text mining in students' course evaluations: Relationships between open-ended comments and quantitative scores. In CSEDU 2013 - Proceedings of the 5th International Conference on Computer Supported Education (pp. 564-573). SciTePress.