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Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin
Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin
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. Students’ feedback includes numerical answers to Likert scale questions and textual comments to open-ended questions. Within the textual comments given by the students are embedded suggestions. A suggestion can be explicit or implicit. Any suggestion provides useful pointers on how the instructor can further enhance the student learning experience. However, it is tedious to manually go through all the qualitative comments and …
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 …
Analyzing Educational Comments For Topics And Sentiments: A Text Analytics Approach, Gokran Ila Nitin, Swapna Gottipati, Venky Shankararaman
Analyzing Educational Comments For Topics And Sentiments: A Text Analytics Approach, Gokran Ila Nitin, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Universities collect qualitative and quantitative feedback from students upon course completion in order to improve course quality and students’ learning experience. Combining program-wide and module-specific questions, universities collect feedback from students on three main aspects of a course namely, teaching style, content, and learning experience. The feedback is collected through both qualitative comments and quantitative scores. Current methods for analyzing the student course evaluations are manual and majorly focus on quantitative feedback and fall short of an in-depth exploration of qualitative feedback. In this paper, we develop student feedback mining system (SFMS) which applies text analytics and opinion mining approach …