A conceptual framework for analyzing students' feedback

• Main Authors: SHANKARARAMAN, Venky, GOTTIPATI, Swapna, GAN, Sandy
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Student feedback analysis; framework; learning analytics; topics; sentiments; text analytics; clustering; Higher Education; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/3836; https://ink.library.smu.edu.sg/context/sis_research/article/4838/viewcontent/Conceptual_Framework_Student_Feedback_FIE_2017.pdf
• Institution: Singapore Management University

In academic institutions it is normal practice that at the end of each term,students are required to complete a questionnaire that is designed to gather students’perceptions of the instructor and their learning experience in the course. This questionnaire comprises of Likert-scale questions and qualitative questions.One of the important goals of this exercise is to enable the instructor and the senior management to examine the feedback and then enhance students’ learning experience. In most universities, including our own, a lot of attention is paid to the quantitative feedback, which is summarized and statistical comparisons are computed, analysed and presented. However, the qualitative comments given by the students are not fully tapped. Capturing and analysing the qualitative feedback data, at the individual course, school and university-level, can provide valuable insights on teaching practices and curriculum. In this paper,we propose a conceptual framework for student feedback analysis that provides the necessary structure for implementing a prototype tool for mining student comments. We then discuss the application of the tool to analyse feedback from selected courses.