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.
|Title of host publication||CSEDU 2013 - Proceedings of the 5th International Conference on Computer Supported Education|
|Publication status||Published - 2013|
|Event||5th International Conference on Computer Supported Education (CSEDU 2013) - Aachen, Germany|
Duration: 6 May 2013 → 8 May 2013
|Conference||5th International Conference on Computer Supported Education (CSEDU 2013)|
|Period||06/05/2013 → 08/05/2013|
- Data mining
- Factor analysis
- Multivariant analysis
- Regression analysis
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.