Browse > Article
http://dx.doi.org/10.4275/KSLIS.2021.55.4.267

Analyzing Students' Non-face-to-face Course Evaluation by Topic Modeling and Developing Deep Learning-based Classification Model  

Han, Ji Yeong (연세대학교 문헌정보학과)
Heo, Go Eun (연세대학교 문헌정보학과)
Publication Information
Journal of the Korean Society for Library and Information Science / v.55, no.4, 2021 , pp. 267-291 More about this Journal
Abstract
Due to the global pandemic caused by COVID-19 in 2020, there have been major changes in the education sites. Universities have fully introduced remote learning, which was considered as an auxiliary education, and non-face-to-face classes have become commonplace, and professors and students are making great efforts to adapt to the new educational environment. In order to improve the quality of non-face-to-face lectures amid these changes, it is necessary to study the factors affecting lecture satisfaction. Therefore, This paper presents a new methodology using big data to identify the factors affecting university lecture satisfaction changed before and after COVID-19. We use Topic Modeling method to analyze lecture reviews before and after COVID-19, and identify factors affecting lecture satisfaction. Through this, we suggest the direction for university education to move forward. In addition, we can identify the factors of satisfaction and dissatisfaction of lectures from multiangle by establishing a topic classification model with an F1-score of 0.84 based on KoBERT, a deep learning language model, and further contribute to continuous qualitative improvement of lecture satisfaction.
Keywords
COVID-19; Learning Satisfaction; University education; Text Mining; LDA Topic Modeling; Topic Classification;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Kim, J. Y. & Park, E. H. (2017). E-learning course reviews analysis based on big data analytics. Journal of the Korean Information and Communication Society, 21(2), 423-428.   DOI
2 Kim, P. J. (2019). An analytical study on automatic classification of domestic journal articles using random forest. Journal of the Korean Society for Information Management(JKOSIM), 36(2), 57-77.   DOI
3 Noh, Y. & Lee, K. K. (2020). A study on factors affecting learner satisfaction in none-face-to-face online education. Academy of Customer Satisfaction Management, 22(3), 107-126.   DOI
4 Kim, T. K., Choi, H. R., & Lee, H. C. (2016). A study on research trends in fintech using topic modeling. Journal of Korea Academia-Industrial cooperation Society(JKAIS), 17(11), 670-681.   DOI
5 Lee, S. K., Choi, S. B., & Kim, H. W. (2019). An Exploratory Study of E-learning satisfaction: a mixed methods of text mining and interview approaches, Information Systems Review, 21(1), 39-59.   DOI
6 Song, Y. H. & Ji, S. G. (2012). Relationships among instructor sense of humor, rapport, flow, and satisfaction in university classes. Journal of Educational Studies, 43(4), 245-269.
7 Sim, J. K. (2021). A study on automatic classification of profanity sentences of elementary school students using BERT. Journal of Creative Information Culture, 7(2), 91-98.   DOI
8 Yuk, J. H. & Song, M. (2018). A study of research on methods of automated biomedical document classification using topic modeling and deep learning. Journal of the Korean Society for Information Management(JKOSIM), 35(2), 63-88.   DOI
9 Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. The Journal of Machine Learning Research, 3, 993-1022.
10 Hwang, S. H. & Kim, D. H. (2020). BERT-based classification model for korean documents. The Journal of Society for e-Business Studies, 25(1), 203-214.   DOI
11 Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
12 Hofmann, T. (1999). Probabilistic latent semantic analysis. Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, 289-296.
13 Jeon, Heewon (2021). KoBERT. Available: https://github.com/SKTBrain/KoBERT
14 Kendon, A. (1981). Nonverbal Communication: Interaction and Gesture. The Hague: Mouton Publisher.
15 Mimno, D. & McCallum, A. (2012). Topic models conditioned on arbitrary features with dirichlet-multinomial regression. arXiv preprint arXiv:1206.3278.
16 Rosen-Zvi, M., Griffiths, T., Steyvers, M., & Smyth, P. (2012). The author-topic model for authors and documents. arXiv preprint arXiv:1207.4169.
17 Kim, H. C. S., Ahn, D. J., Yim, J. H., & Lee, H. Y. (2017). A study on automatic classification of record text using machine learning. Journal of the Korean Society for Information Management (JKOSIM), 34(4), 321-344.   DOI
18 Lee, M. S. (2020). Improvement of Recommendation System Using Attribute-based Opinion Mining of Online Customer Reviews. Master's thesis, Kookmin University.
19 Lee, S. B., Kim, S. D., Lee, J. H., Ko, Y. S., & Song, M. (2021). Building and analyzing panic disorder social media corpus for automatic deep learning classification model. Journal of the Korean Society for Information Management(JKOSIM), 38(2), 153-172.   DOI
20 Kim, M. Y. & Kim, M. Y. (2020). An analysis on perception of the satisfaction with university liberal education and learning outcomes. Research on Liberal Arts Education, 14(1), 193-218.
21 Choi, K. H. & Kang. S. (2011). A study measuring university educational service quality using importance-satisfaction transformed index. Journal of the Korean Data & Information Science Society, 22(4), 765-773.
22 Park, E. L. & Cho, S. (2014). KoNLPy: korean natural language processing in python. Proceedings of the 26th Annual Conference on Human & Cognitive Language Technology, 6, 133-136.
23 Kang, M. S. & Park, S. K. (2011). Assessing the effects of service quality on student satisfaction, trust, commitment and loyalty: the case of university education. Academy of Customer Satisfaction Management, 13(1), 129-149.
24 Kee, Y. H. & Roh, H. J. (2005). A comparison study on the effects of blended learning course and on-line course in a university class. The Journal of Lifelong Education and HRD, 1(1), 63-79.
25 Kim, K. K., Kim, Y. H., & Kim, J. H. (2018). A study on customer satisfaction of mobile shopping apps using topic analysis of user reviews. The Journal of Society for e-Business Studies, 23(4), 41-62.   DOI
26 Kim, D. W., Kang, J. Y., & Im, J. I. (2016). Comparative analysis of job satisfaction factors, using LDA topic modeling by industries: the case study of job planet reviews. Korea Society of IT Services, 15(3), 157-171.
27 Kim, S. H. (2017). Education quality improvement by analyzing course evaluation. Research Institute for Social Science, 30(1), 147-174.
28 Kim, S. R. (2021). Development and Validation of Graduate Student' Perceived Educational Satisfaction Model and Scale. Doctoral dissertation, Korea University.
29 Jo, M. W. & Kim, J. Y. (2021). A study on the perception and the satisfaction of online classes at K university in the non-face-to-face era. The Journal of Humanities and Social Science, 12(2), 1399-1414.
30 Jin, S. A., Heo, G. E., Jeon, Y. K., & Song, M. (2013). Topic-network based topic shift detection on twitter. Journal of the Korean Society for Information Management(JKOSIM), 30(1), 285-302.   DOI
31 Han, E. S. & Kim, J. D. (2003). An analysis of influential factors on college of education students' academic satisfaction. The Korean Society for the Study of Teacher Education, 20(3), 313-335.
32 Ham, E. H., Park, S. O., & Kim, E. K. (2017) Using subscale scores of university student satisfaction survey: an application of bifactor models. Asian Journal of Education, 18(4), 713-738.   DOI
33 Baek, S. H. (2021). Verification of predictive factors for gender equality and threat from elder. The Journal of Humanities and Social Science, 12(2), 2543-2556.
34 Park, J. H. & Song, M. (2013). A study on the research trends in library & information science in korea using topic modeling. Journal of the Korean Society for Information Management (JKOSIM), 30(1), 7-32.   DOI
35 Park, J. D. (2015). A study on mapping users' topic interest for question routing for community-based Q&A service. Journal of the Korean Society for Information Management (JKOSIM), 32(3), 397-412.   DOI
36 Park, J. S., Hong, S. G., & Kim, J. W. (2017). A study on science technology trend and prediction using topic modeling. Journal of the Korea Industrial Information Systems Research, 22(4), 19-28.   DOI
37 Suh, K. W. (2011). Factors affecting online lecture satisfaction and intention to recommend. Journal of Cyber Education, 5(2), 159-178.
38 Sin, J. Y., Kwon, L. M., & Moon, S. H. (2009). AHP analysis for the factors that influence college student's satisfaction on the business courses. Korean Business Education Review, 55(1), 53-73.
39 Song, Y. H. (2020). The influence of instructor's non-verbal communication on college student's emotional presence, rapport and learning satisfaction. The Korea Contents Society, 20(10), 259-267.