Nonlinear principal components analysis: introduction and application.
Like other universities, RMIT recognises the significance of graduates’ ratings of their experience and has had a long-term commitment to improving student learning. As at other universities, RMIT’s standard subject-level survey (the Course Experience Survey [CES]) incorporates items from the national Course Experience Questionnaire, with the aim of eliciting student views and prompting improvements that will take effect before the students graduate. The university has been seeking strategies to make the results of these surveys more accessible to academic staff, so that staff can use them as a starting point for change. The current project is part of this work. The starting point is discipline-based analysis of the university’s CES data. Surveys were stratified into fifty disciplines, and categorical factor analysis applied to ascertain common interpretable factors. The results have been presented to staff for discussion in the context of planning for improvement. This article explores the results of the factor analysis and its potential for providing academics with useful information on students’ experiences.