Tapping into the student voice
Student evaluations of teaching and courses (SETs) are part of the fabric of tertiary education. Quantitative ratings yield valuable results for tertiary institutions, but students' comments can be richer and give more insight. They are unfortunately also more time-consuming to analyse.
Adon Moskal, Principal Lecturer in Information Technology, worked with Jenny McDonald, Allen Goodchild, Sarah Stein and Stuart Terry to survey tertiary students at two institutions about their perceptions of SETs. One of the common reasons why students were reluctant to complete SETs was that they could see no point - they do not understand how their feedback is used. To address this it is desirable to use students' feedback to benefit their own cohort, so that the SETs are valuable for them as well as for their lecturers.
The team also ran a proof-of-concept study using the Quantext text analysis software which Jenny and Adon had developed. This study worked with 648 and 389 student comments answering two questions about why students do not complete SETs. They found that the text analytic tools in Quantext can have an important role in assisting teaching staff with the rigorous analysis and interpretation of SETs. For example, Quantext can identify word frequency to help identify suitable codes to use, and can automatically identify semantically similar responses. Automated text analysis can help lecturers to more easily analyse and hence use student feedback to improve their teaching practice.