Analysing qualitative feedback using CEQuery and SPSS Text

Beverley Oliver, Beatrice Tucker and Julie-Ann Pegden, Curtin University of Technology, Western Australia

Keywords: Student evaluation; qualitative feedback; CEQuery

Computer-aided text analysis is used to assist in the analysis of large data sets of qualitative information. Curtin's new online student evaluation system (eVALUate) comprises quantitative and qualitative data which is reported at unit, course, divisional and university level. This study examined the relationship between the student written comments and their level of satisfaction with the quantitative items in the unit level survey. CEQuery was used to sort qualitative comments into domains and subdomains, and SPSS text analysis for surveys was used to examine major themes and connections within each subdomain. Of the 25090 unit survey responses collected at the end of semester 1 2006, 67.4% contained comments in at least one item. More students commented on the item about 'Most helpful aspects' (59.6%) than 'How units might be improved' (58%). A higher number of surveys were submitted by female students (female=69.4%; male=64.6%), older students, Australian students (Australian=71.3%; International=57.5%), full-time students (full-time=68%; part-time=65.3%) and those who were enrolled externally (external=73.6%; internal=67.1%). On average, student comments were lengthier for the item on improving the unit (181 characters). Students commented most frequently about methods of teaching and learning in the item on 'Most helpful aspects' however this was also the second most frequent comment in the item on 'How the unit might be improved.' SPSS text analysis identified common themes that helped identify what methods of teaching and learning were helping students learn. This analysis was conducted for the university report and the divisional report so any differences could be determined.