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Extracting Implicit Suggestions From Students’ Comments: A Text Analytics Approach, Venky Shankararaman, Swapna Gottipati, Jeff Rongsheng Lin, Sandy Gan
Extracting Implicit Suggestions From Students’ Comments: A Text Analytics Approach, Venky Shankararaman, Swapna Gottipati, Jeff Rongsheng Lin, Sandy Gan
Research Collection School Of Computing and Information Systems
At the end of each course, students are required to give feedback on the course and instructor. This feedback includes quantitative rating using Likert scale and qualitative feedback as comments. Such qualitative feedback can provide valuable insights in helping the instructor enhance the course content and teaching delivery. However, the main challenge in analysing the qualitative feedback is the perceived increase in time and effort needed to manually process the textual comments. In this paper, we provide an automated solution for analysing comments, specifically extracting implicit suggestions from the students’ qualitative feedback comments. The implemented solution leverages existing text mining …
A Conceptual Framework For Analyzing Students' Feedback, Venky Shankararaman, Swapna Gottipati, Sandy Gan
A Conceptual Framework For Analyzing Students' Feedback, Venky Shankararaman, Swapna Gottipati, Sandy Gan
Research Collection School Of Computing and Information Systems
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 …