An Improved Phrase-Based Approach To Annotating And Summarizing Student Course Responses

Teaching large classes remains a great challenge, primarily because it is difficult to attend to all the student needs in a timely manner. Automatic text summarization systems can be leveraged to summarize the student feedback, submitted immediately after each lecture, but it is left to be discovered what makes a good summary for student responses. In this work we explore a new methodology that effectively extracts summary phrases from the student responses. Each phrase is tagged with the number of students who raise the issue. The phrases are evaluated along two dimensions: with respect to text content, they should be informative and well-formed, measured by the ROUGE metric; additionally, they shall attend to the most pressing student needs, measured by a newly proposed metric. This work is enabled by a phrase-based annotation and highlighting scheme, which is new to the summarization task. The phrase-based framework allows us to summarize the student responses into a set of bullet points and present to the instructor promptly

Teaching analytics and teacher dashboards to visualise SET data: Implication to theory and practice

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