A Text Analytics Evaluation of a First-Year Engineering Project-Based Unit

摘要

In the undergraduate engineering program at Griffith University in Australia, the unit 1006ENG Design and ProfessionalSkills aims to provide an introduction to engineering design and professional practice through a project-based learning(PBL) approach to problem solving. It provides students with an experience of PBL in the first-year of their programme.The unit comprises an underpinning lecture series, design work including group project activities, an individual computeraideddrawing exercise/s and an oral presentation. Griffith University employs a ‘Student Experience of Course’ (SEC) onlinesurvey as part of its student evaluation of teaching, quality improvement and staff performance management processes.As well as numerical response scale items, it includes the following two questions inviting open-ended text responses fromstudents: i) What did you find particularly good about this course? and ii) How could this course be improved? Thecollection of textual data in in student surveys is commonplace, due to the rich descriptions of respondent experiencesthey can provide at relatively low cost. However, historically these data have been underutilised because they are timeconsuming to analyse manually, and there has been a lack of automated tools to exploit such data efficiently. Text analyticsapproaches offer analysis methods that result in visual representations of comment data that highlight key individualthemes in these data and the relationships between those themes. We present a text analytics-based evaluation of theSEC open-ended comments received in the first two years of offer of the PBL unit 1006ENG. We discuss the results obtainedin detail. The method developed and documented here is a practical and useful approach to analysing/visualising openendedcomment data that could be applied by others with similar comment data sets.