Teaching Analytics (TA) is an emergent theoretical approach that combines teaching expertise, visual analytics, and design-based research to support teachers' diagnostic pedagogical ability to use data as evidence to improve teaching quality. The thesis is focused on designing dashboards to help teachers visualise Student Evaluation of Teaching (SET) data as a form of TA for improving the quality of teaching. The research examined the role of TA by deploying customisable dashboards to support teachers in using data to design and facilitate learning. The researcher carried out an integrated literature review to explore the notion of TA and SET data. Moreover, a Data Science Life Cycle model was proposed to guide teachers and researchers using SET data to improve learning and teaching quality. The research comprised several phases. In phase I, a simulated data technique was used to generate SET scores that informed the development of a preliminary teacher dashboard. Phase II surveyed teachers' use of SET data. The survey results indicated that more than half of the participants used SET for improving teaching practice. The research also showed that participants valued the free-text qualitative comments in SET data. Hence, phase III collected real free-text qualitative comments in SET data on students' perceptions of a previously tutored course. The survey results further indicated that although teachers were unaware of a dashboard's value in presenting data, they wanted to visualise SET data using dashboards. Phase IV redesigned the preliminary dashboards to present the real SET data and the simulated SET scores. Finally, phase V carried out usability testing to evaluate teachers' perceptions of usability and usefulness of the teacher's dashboards. Overall, the result of the usability study indicated the perceived value of the teacher's dashboards
