Senior management in tertiary institutions desires an efficient system that could help them assess and evaluate learning outcomes so that effective policies can be implemented to enhance teaching and learning. This gets intensified as broader issues arise and higher expectations are put on tertiary education—build a creative workforce and adapt to new technologies to analyze the large volume of teaching and learning data. Government and higher education policymakers have to rapidly adjust relevant policies to surmount the challenges from the pandemic and also to keep up with technological advancement. This demands a novel and efficient way for policymakers and senior management to see and gain insights from a large volume of data (e.g., student course and teacher evaluation). In this study, the researchers present such a system through various examples. The findings generated from this study contribute to the scholarship, and they provide a solution to senior management in tertiary institutions wanting to implement effective policies efficiently. The use of online analytical processing, virtual campus, online, and machine learning in education is growing. However, the use of these technology‐enhanced approaches is rare in performing arts education. There has been no in‐depth study, especially on technology‐enhanced learning that leads to the improvement of teaching. This study utilizes a multi‐dimensional analysis approach on the course student evaluation, a key aspect of the teaching and learning quality assurance for higher education. A novel analytical framework is developed and implemented at a leading performing arts university in Asia. It analyzes the course evaluation data of all courses (669 courses and 2664 responses) in the academic year 2018/2019 to make evidence‐based recommendations. Such a framework provides an easy and effective visualization for senior management to identify courses that need closer scrutiny to ascertain whether and what areas of course enhancement measures are warranted.