Student rating instruments are recognised to be valid indicators of effective instruction, providing a valuable tool to improve teaching. However, free-form text comments obtained from the open-ended question component of such surveys are only infrequently analysed comprehensively. We employed an innovative, systematic approach to the analysis of text-based feedback relating to student perceptions of and experiences with a recently developed university program. The automated nature of the semantic analysis tool "Leximancer" enabled a critical interrogation across units of study, mining the cumulative text for common themes and recurring core concepts. The results of this analysis facilitated the identification of issues that were not apparent from the purely quantitative data, thus providing a deeper understanding of the curriculum and teaching effectiveness that was constructive and detailed.