Analyzing Educational Comments for Topics and Sentiments: A Text Analytics Approach

• Main Authors: NITIN, Gokran Ila, GOTTIPATI, Swapna, SHANKARARAMAN, Venky
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Student feedback; education data mining; topics; sentiments; text analytics; clustering; Computer Sciences; Higher Education
• Online Access: https://ink.library.smu.edu.sg/sis_research/2888; https://ink.library.smu.edu.sg/context/sis_research/article/3888/viewcontent/Analyzing_Edn_Comments_Sentiments_FIE_2015.pdf
• Institution: Singapore Management University

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 na...