Project dates: 01/01/2023 - 01/05/2023
At QUT, HiQ is the first point of contact for enquiries from students, staff and the wider community. They receive a range of enquiries that include general enquiries about ID cards, student administration processes, such as admission, enrolment, fees and advanced standing, technology support, study and library support. As a result, HiQ collects a large volume of enquiry data from QUT students and staff. A total of 120 categories and sub-categories are used to classify and group enquiry types (e.g. class registration, campus transport, student welfare, ID Card, student enrolment, etc.). Currently, HiQ can report on the volume of enquiries per category, but without significant effort, useful insight into these enquiries cannot be provided as the details are captured in the free text within the enquiry record. This was an exploratory study using AI technology (i.e. text mining techniques) to extract key, actionable insights from the free-text enquiry data to identify top-level groups to enable HiQ staff to drill down in the groupings to identify potential problem areas.
Chief Investigators
Other Team Members
