DOI QR코드

DOI QR Code

A Study on the Topic Modeling Analysis of Book Reports on Personality Types and Interest Types

성격유형과 흥미유형에 따른 독서 감상문 토픽 분석 연구

  • Received : 2023.02.15
  • Accepted : 2023.03.13
  • Published : 2023.03.30

Abstract

This study aimed to investigate the difference in response to reading as shown in book reports by personality type and interest type. For this purpose, personality type analysis data, interest type analysis data, and book report data written in subject reading activities were collected from 81 third graders at D Science High School in Daejeon. Topic analysis was conducted on the collected book reports, and the probability of a topic being mentioned was statistically tested according to personality type (thinking type, feeling type) and interest type (investigative type, types other than investigative). Subsequently, the conceptual connection structure of words was measured by keyword network analysis, and the analysis results of topic modeling were complemented by the centrality index. As a result of the study, the topic regression analysis showed statistically significant differences between thinking type (T) and feeling type (F) in topic 2 (understanding and studying) and topic 3 (reading and thinking), and statistically significant differences between investigative type and non-investigative type in topic 2 (understanding and studying). The results of this study can be used as a basis for tailored book recommendations and personalized reading education.

본 연구에서는 성격유형과 흥미유형에 따른 독서 감상문에 나타난 독서에 대한 반응의 차이를 탐구하였다. 이를 위해 대전의 D과학고등학교 3학년 학생 81명을 대상으로 성격유형분석 데이터, 흥미유형분석 데이터, 교과독서 활동으로 작성된 독서 감상문 데이터를 수집하였다. 수집된 독서 감상문의 토픽 분석을 수행하고, 성격유형(사고형, 감정형)과 흥미유형(탐구형, 탐구형 외)에 따른 독서 감상문의 토픽 발현 확률을 통계적으로 검증하였다. 이어서 키워드 네트워크 분석을 통해 단어들의 개념 연결 구조를 측정하고, 중심성 지표를 통해 토픽모델링의 분석 결과를 보완하였다. 연구 결과, 토픽 회귀분석을 통해 토픽2(이해와 공부)와 토픽3(읽기와 사고)에서 사고형(T)과 감정형(F) 간에 통계적으로 유의한 차이를 확인할 수 있었으며, 토픽2(이해와 공부)에서 탐구형과 탐구형 외 간에 통계적으로 유의한 차이가 확인되었다. 본 연구의 결과는 맞춤형 도서 추천이나 개인화를 고려한 독서교육의 기초자료로 활용될 수 있을 것이다.

Keywords

References

  1. Ahn, Chang-Kyu (1996). Interpretation and Application of Career and Aptitude Search Tests. Seoul: Korea Guidance.
  2. Ahn, Chang-Kyu, Choi, Taejin, & Hong, Joon-Ja (2005) Analysis of decision making patterns of high school students according to holland's vocational personality type. Korean Journal of Counseling, 6(2), 449-468.
  3. Chang, JaeYoon, Choi, YeonJae, & Kang, Ji-Yeon (2020). An exploratory analysis of domestic ICT workers' dissatisfaction with their jobs and differences between former and incumbent employees: application of topical modeling. Korean Journal of Psychology: General, 39(3), 445-480. http://dx.doi.org/10.22257/kjp.2020.9.39.3.445
  4. Han, Jongwoo (2021). Identifying Emerging Topics in Industrial Root Technologies: a Structural Topic Model- and Topic Matrix Analysis-based Approach. Doctoral dissertation, Sungkyunkwan University, Korea.
  5. Jeong, Mee-Seon, Kim, Won-Jeong, & Cho, Unhaing (2010). Carrier related analysis of the gifted middle school students in science based on the self-directed search test developed by holland. Journal of Science Education for the Gifted, 2(1), 1-10.
  6. Jo, Han-jin & Kim, Taehoon (2012). Analysis of the relationship between technological problem solving styles and MBTI character types. The Korean Journal of Technology Education, 12(1), 110-129.
  7. Jo, Wonkwang (2017). The Social Construction of Medical Knowledge and Health Behavior: Using Topic Modeling on Abstracts of Breast Cancer Research and Posts from Online Breast Cancer Patient Forums. Doctoral dissertation, Seoul University, Korea.
  8. Kang, YunSoo (2020). High school students' mathematics learning style and its characteristics according to their MBTI personality disposition types. Communications of Mathematical Education, 34(3), 299-324. https://doi.org/10.7468/jksmee.2020.34.3.299
  9. Kim, Heesop, Seo, Jiwoong, & Lee, Mi sook (2014). An analysis of college students' life satisfaction and internet information activities based on their personality types. Journal of the Korean Society for Information Management, 31(1), 299-317. https://doi.org/10.3743/KOSIM.2014.31.1.299
  10. Kim, Woo-Kyum (2023). Analysis of academic emotional changes and structural topic model (STM) in earth science subject class using virtual reality(VR) contents. The Journal of Learner-Centered Curriculum and Instruction, 23(1), 129-141. https://doi.org/10.22251/jlcci.2023.23.1.129
  11. Korea MBTI Institute [n.d.]. 4 Preference Indicators. Available: https://www.mbti.co.kr
  12. Kwahk, Kee-Young (2019). Social Network Analysis (2nd ed.). Seoul: Chungram.
  13. Kwak, Woojung, Noh, Younghee, Ahn, Inja, & Zhang, Jingjing (2019). A study on the customized services of university libraries according to MBTI personality types of college students. Journal of the Korean BIBLIA Society for Library and Information Science, 30(4), 91-114. https://doi.org/10.14699/KBIBLIA.2019.30.4.091
  14. Lee, HanSu (2019). Relationship between the MBTI test and painting expression. The Korean Journal of Art and Media, 18(1), 201-236. https://doi.org/10.36726/cammp.2019.18.1.201
  15. Lee, Hyunjoo & Chae, Yoojung (2018). An analysis of learning interest and self-regulated learning by giftedness and thinking style. Journal of the Korean Association for Science Education, 38(1), 57-68. http://dx.doi.org/10.14697/jkase.2018.38.1.57
  16. Lee, Soo-Sang (2014). A content analysis of journal articles using the language network analysis methods. Journal of the Korean Society for Information Management, 31(4), 49-66. http://dx.doi.org/10.3743/KOSIM.2014.31.4.049
  17. Lee, Yoon-Jo, Lee, Jeongkyu, & Lee, HangEun (2009). The educational implications in the career counseling for the gifted students in the invention based on their career development data. The Journal of the Korean Society for Gifted and Talented, 13(1), 155-173. http://dx.doi.org/10.17839/jksgt.2014.13.1.155
  18. Lee, Young-Ran & Han, Ki-Soon (2021). Meta-analysis on the personality of gifted and non-gifted students through MBTI. The Journal of the Korean Society for Gifted and Talented, 20(3), 31-59. http://dx.doi.org/10.17839/jksgt.2021.20.3.31
  19. Lim, Jeong-Hoon, Cho, Changje, & Kim, Jongheon (2022). A study on the development of the school library book recommendation system using the association rule. Journal of the Korean Society for Information Management, 39(3), 1-22. http://dx.doi.org/10.3743/KOSIM.2022.39.3.001
  20. Nam, Sangin & Hwang, Kyuho (2011). The relationship between MBTI preference types and metacognitive awareness levels. Korea Journal of Counseling, 12(6), 2293-2306. http://dx.doi.org/10.15703/kjc.12.6.201112.2293
  21. No, Ann-Young & Kang, Young-Shin (2003). Personality Psychology. Seoul: Hakjisa.
  22. Ryu, Jiyoung (2017). Are scientifically gifted students' personalities different from regular students' personalities?: analysis of MBTI of scientifically gifted students. Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, 7(8), 467-477. http://dx.doi.org/10.35873/ajmahs.2017.7.8.043
  23. Yun, Kyung-mi & Yoo, SooHwa (2011). A comparison of career patterns among the gifted in science, the gifted in human and social science and average middle school students by Holland career theory. Secondary Education Research, 59(4), 1011-1030. http://dx.doi.org/10.25152/ser.2011.59.4.1001
  24. Airoldi, E. M. & Bischof, J. M. (2016), Improving and evaluating topic models and other models of text. Journal of the American Statistical Association, 111(516), 1381-1403. https://doi.org/10.1080/01621459.2015.1051182
  25. Bagozzi, B. E. & Berliner, D. (2016). The politics of scrutiny in human rights monitoring: evidence from structural topic models of US State Department human rights reports. Political Science Research and Methods, 6(4), 661-677. https://doi.org/10.1017/psrm.2016.44
  26. Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84. https://doi.org/10.1145/2133806.2133826
  27. Holland, J. L. (1998), Making vocational choices: a theory of vocational personalities and work environments (4th ed.). 안창규, 안현의 옮김 (2004). 홀랜드 직업선택이론. 서울: 한국가이던스.
  28. Myers, I. B. & MaCaulley, M. H. (1985). Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator, 김정택, 제석봉, 심혜숙 옮김 (1995). MBTI 개발과 활용. 서울: 한국심리검사연구소.
  29. Roberts, M. E., Stewart, B. M., & Tingley, D. (2019). Stm: An R package for structural topic models. Journal of Statistical Software, 91, 1-40. https://doi.org/10.18637/jss.v091.i02
  30. Wang, H., Chen, B., & Li, W. J. (2013, August). Collaborative topic regression with social regularization for tag recommendation. Proceedings of In Twenty-Third International Joint Conference on Artificial Intelligence. 2719-2725.