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@article{ART002591998},
author={Byung-Hak Leem and 강현주 and Seong-Won Eum and SRIJAN KUMAR},
title={Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions},
journal={Studies in Humanities and Social Sciences},
issn={1598-4230},
year={2020},
volume={63},
number={2},
pages={55-64},
doi={10.17939/hushss.2020.63.2.004}

TY - JOUR
AU - Byung-Hak Leem
AU - 강현주
AU - Seong-Won Eum
AU - SRIJAN KUMAR
TI - Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions
JO - Studies in Humanities and Social Sciences
PY - 2020
VL - 63
IS - 2
PB - Institute of Humanities and Social Sciences
SP - 55
EP - 64
SN - 1598-4230
AB - This study measures students’ preferences by analyzing their feedback about the lectures they have been attending based on open-ended questions on the course evaluation using the sentiment analysis method, one of the text mining methods. Based on this analysis, the quality of lectures was measured to suggest future changes made for improving teaching methods, directions for improving lecture quality, and its contents. This study aims to analyze qualitatively the feedback of student evaluation to examine student’s perceptions about the lecture more directly and comprehensively. To this end, answers of open-ended questions were collected and classified with positive, neutral, negative opinions or polarity. As a result of sentiment analysis 422 words are extracted. Among them 327 words (82.2%) were positive as opposed to 44. To measure our model’s accuracy, recall and precision and all of them are over 0.96 which indicates that machine learning model using NBC method successfully classified the data. This study could contribute to the course evaluation because it shows how to utilize students’ feedback of open-ended questions using text mining and sentiment analysis. It also gives solid measurement of the subjective point of view of students.
KW - Text Mining;Sentiment Analysis;Student Feedback;Course Evaluation;open-ended question
DO - 10.17939/hushss.2020.63.2.004
ER -

Byung-Hak Leem, 강현주, Seong-Won Eum and SRIJAN KUMAR. (2020). Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions. Studies in Humanities and Social Sciences, 63(2), 55-64.

Byung-Hak Leem, 강현주, Seong-Won Eum and SRIJAN KUMAR. 2020, "Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions", Studies in Humanities and Social Sciences, vol.63, no.2 pp.55-64. Available from: doi:10.17939/hushss.2020.63.2.004

Byung-Hak Leem, 강현주, Seong-Won Eum, SRIJAN KUMAR "Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions" Studies in Humanities and Social Sciences 63.2 pp.55-64 (2020) : 55.

Byung-Hak Leem, 강현주, Seong-Won Eum, SRIJAN KUMAR. Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions. 2020; 63(2), 55-64. Available from: doi:10.17939/hushss.2020.63.2.004

Byung-Hak Leem, 강현주, Seong-Won Eum and SRIJAN KUMAR. "Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions" Studies in Humanities and Social Sciences 63, no.2 (2020) : 55-64.doi: 10.17939/hushss.2020.63.2.004

Byung-Hak Leem; 강현주; Seong-Won Eum; SRIJAN KUMAR. Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions. Studies in Humanities and Social Sciences, 63(2), 55-64. doi: 10.17939/hushss.2020.63.2.004

Byung-Hak Leem; 강현주; Seong-Won Eum; SRIJAN KUMAR. Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions. Studies in Humanities and Social Sciences. 2020; 63(2) 55-64. doi: 10.17939/hushss.2020.63.2.004

Byung-Hak Leem, 강현주, Seong-Won Eum, SRIJAN KUMAR. Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions. 2020; 63(2), 55-64. Available from: doi:10.17939/hushss.2020.63.2.004

Byung-Hak Leem, 강현주, Seong-Won Eum and SRIJAN KUMAR. "Using Sentiment Analysis to Analyze the Feedback of Students with Open-ended Questions" Studies in Humanities and Social Sciences 63, no.2 (2020) : 55-64.doi: 10.17939/hushss.2020.63.2.004