본문 바로가기
KERD
논문KCI 등재

과학영재학교에서 과학영재의 학습몰입 상황에 대한 토픽 모델링 분석

Topic Modeling Analysis of Science Gifted Students’ Learning Flow Situations in Science Gifted High Schools

박경희|정용석|서혜애
과학교육연구소 (Science Education Research Institute)|2024.12|과학교육연구지 (Journal of Science Education)|제48권 제3호|pp. 290-310|DOI 10.21796/jse.2024.48.3.290

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

토픽 모델링topic modeling학습몰입science gifted students과학영재학교learning flow과학영재NMF 모델science gifted high schoolNMF model

초록

본 연구에서는 과학영재학교에서 과학영재들이 경험하는 학습몰입의 상황과 개인별 특성의 유형을 탐색하는 데 목적을 두었다. 이를 위해 먼저, 4개 과학영재학교의 19명의 과학영재들이 경험하는 학습몰입의 특징과 상황에 대한 질적 자료를 심층 면담으로 수집하였다. 둘째, AI 기반 토픽 모델링 기법으로 대량의 질적 자료를 분석한 결과에 기반하여 과학영재학교에서의 학습몰입 상황의 특징을 탐색하였다. 연구결과, NMF 모델링을 통해 5개 주제의 학습몰입의 상황을 분류할 수 있었다. 5개 주제는 다음과 같았다. 주제 1: 자기주도적 자율활동, 주제 2: 연구활동의 학습몰입, 주제 3: 교과 수업시간에서의 학습몰입, 주제 4: 선호주제와 진로선택활동에서의 학습몰입, 주제 5: 도전적인 문제해결에서의 학습몰입이었다. 개인별로 5개 주제에 대한 비율을 분석한 후, 시각화하여 학습몰입 유형을 탐색하였으며, 5개 유형으로 분류할 수 있었다. 유형 1은 주제 1과 주제 3이 높았으며, 유형 2는 주제 1과 주제 2, 유형 3은 주제 1, 주제 2, 주제 4, 유형 4는 주제 1, 주제 4, 주제 5, 유형 5는 주제 1, 주제 3, 주제 4가 높은 비율로 포함되었다. 과학영재학교별 차이는 연구 참여자 과학영재들이 선호적으로 선택한 교육과정과 교내외 프로그램, 나아가 이들은 지도한 교사의 전문성에 따른 차이로 해석하였다. 결론적으로 과학영재학교에서는 학습몰입에 최적화된 교육적 여건을 효과적으로 제공하는 교육과정 및 개별 맞춤형 지원 시스템을 수립하고 실천해야 할 것이다.

Abstract

This study aimed to explore the types of learning flow situations and individual characteristics experienced by science gifted students in science gifted high schools. For this end, first, in-depth interviews were conducted to collect qualitative data on characteristics and situations of learning flow experienced by 19 science gifted students from four science gifted high schools. Second, the characteristics of learning flow situations were extracted through the analysis of large-scale qualitative data using an AI-based topic modeling technique. Through NMF modeling, the learning flow situations were classified into five themes as follows: Theme 1: Self-directed autonomous activities, Theme 2: Learning flow in research activities, Theme 3: Learning flow during class time, Theme 4: Learning flow in preferred topics and career-related activities, and Theme 5: Learning flow in challenging problem-solving activities. After analyzing the proportion of each student for the five themes, the learning flow types were visualized, and four types were evident. Type 1 showed high scores for Theme 1 and Theme 3; Type 2 showed high scores for Theme 1 and Theme 2; Type 3 showed high scores for Theme 1, Theme 2, and Theme 4; and Type 4 showed high scores for Theme 1, Theme 4, and Theme 5; Type 5 showed high scores for Theme 1, Theme 3, and Theme 4. Differences between the science gifted high schools were interpreted as being related to the educational programs and school programs preferred by the participating students, as well as the professionalism of the teachers who guided them. In conclusion, it is necessary to establish and implement curricula and individualized support systems that effectively provide educational conditions optimized for learning flow in science gifted high schools.

참고문헌 (58)

  1. Blei, M. D., "Latent dirichlet allocation", Journal of Machine Learning Research, 3, pp.993~1022 (2003)
  2. Chae, Y. J., "Analysis of research trends in Journal of Gifted", Talented Education by periods of master plan for the promotion of gifted and talented education, Talented Education, pp.2018, 28(4)[DOI]
  3. Choe, B., "Korean morphological analyzer for neologism and spacing error based on sequence-to-sequence", Journal of KIISE, 47(1), pp.70~77 (2020)
  4. Choi, B. R., "The structural relationship among school challenge-support, personality, learning strategies, and learning flow", The Journal of the Korean Society for the Gifted and Talented, 14(2), pp.69~94 (2015)
  5. Choi, S. J., "Needs analysis of stakeholders for improving the evaluation policy of gifted schools", Journal of Gifted, 2023, pp.33(2), 141~166
  6. Collobert, R., "Natural language processing(almost)from scratch", Journal of Machine Learning Research, 12, pp.2493~2537 (2011)
  7. Csikszentmihaly, M., "Beyond boredom and anxiety" (1975), Jossey Bass
  8. Csikszentmihalyi, M., "Flow: The psychology of optimal experience" (1990), Harper & Row
  9. Deerwester, S., "Indexing by latent semantic analysis", Journal of the American Society for Information Science, 41(6), pp.391~407 (1990)
  10. Fredricks, J., "Developing and fostering passion in academic and nonacademic domains", Gifted Child Quarterly, 54(1), pp.18~30 (2010)
  11. Fredricks, J. A., "School engagement : Potential of the concept, state of the evidence", Review of Educational Research, 64(1), pp.59~109 (2004)
  12. Goldsmith, J., "Unsupervised learning of the morphology of a natural language", Computational Linguistics, 27(2), pp.153~198 (2001)
  13. Goo, Y. S., "A comparison study of learning style, self-regulated learning and learning flow between gifted and normal student", Journal of Gifted, 2013, pp.23(2), 177~191
  14. Han, K, S., "Current trends and future directions of research in the area of gifted education in Korea", Journal of Gifted, 2007, pp.17(2), 338~364
  15. Hong, S. P., "A study on the early conation, continuous conation, and the flow of gifted and normal students", Journal of Learner-Centered Curriculum and Instruction, 12(1), pp.443~459 (2012)
  16. Heller, K., "Scientific ability and creativity", High Ability Studies, 18(2), pp.209~234 (2007)
  17. Hwang, J. S., "A study on creative problem-solving ability and learning flow in gifted secondary science students participating in the music-science gi-convergence education program", Journal of Gifted, 2022, pp.32(1), 19~44
  18. Hwang, S. I., "A study on the research trends in arts management in Korea using topic modeling and semantic network analysis", Journal of Arts Management and Policy, 47, pp.5~29 (2018)
  19. Jackson, S. A., "Development and validation of a scale to measure optimal experience : The flow state scale", Journal of Sport & Exercise Psychology, 18(1), pp.17~35 (1996)
  20. Jang, K. H., "Curriculum implementation by teachers in science academies for the gifted", The Journal of Curriculum Studies, 40(4), pp.29~56 (2022)
  21. Jang, W. H., "Trend and prospect of research on the education institute for gifted based on text analysis", Journal of Science Education for the Gifted, 11(3), pp.111~125 (2019)
  22. A case study on overseas gifted education (I), "Kang, B. J.", KEDI, ~, pp.CR2011-69 (2011)
  23. Kang, K. H., "The domestic research trend related to science education for the gifted", Journal of Korean Association for Science Education, 30(1), pp.54~67 (2010)
  24. Kim, E. J., "Examining structural relationships among college students’ internal and external factors for learning engagement and satisfaction", Asian Journal of Education, 16(3), pp.107~129 (2015)
  25. Kim, H. J., "The effect of self-regulated learning ability and perceived usefulness on learning persistence in MOOC : The mediating effect of learning engagement and the moderating effect of task technology fit", Journal of Educational Technology, 38(1), pp.149~177 (2022)
  26. Kim, H. W., "Analysis of trends in science gifted education using topic modeling", Journal of Elementary Science Education, 40(3), pp.283~294 (2021)
  27. Kim, J. E., "Content analysis of education activities of science high schools using network text analysis and topic modeling", Journal of Gifted, 2023, pp.33(3), 375~402
  28. Kim, U. J., "The relationships among learning presence, learning flow, and academic achievement at the cyber universities", Asian Journal of Education, 13(3), pp.143~170 (2012)
  29. Lee, A. R., "Research trend analysis on perfectionism of gifted students", The Journal of the Korean Society for the Gifted and Talented, 14(2), pp.171~192 (2015)
  30. Lee, S. H., "A study on the mediated effect of emotional intelligence and self-directed learning skills in the relationship between parental education attitude and learning immersion of gifted students", The Journal of Humanities and Social Science(HSS21), 12(4), pp.2713~2728 (2021)
  31. Lee, D. D., "Learning the parts of objects by non-negative matrix factorization", Nature, 401(6755), pp.788~791 (1999)
  32. Lim, J. M., "The effect of university students' learning flow, self-directed learning, and learning outcomes on uncontacted online class satisfaction", Journal of Digital Convergence, 19(4), pp.393~401 (2021)
  33. Manning, C. D., "Foundations of statistical natural language processing" (1999), MIT Press
  34. Mimno, D., "Optimizing semantic coherence in topic models", Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp.262~272 (2011)
  35. Min, H. S., "A comparison of perfectionism, academic stress and learning flow between gifted and non-gifted in elementary school children", Journal of Gifted, 2012, pp.22(1), 157~171
  36. The 5th comprehensive plan for the promotion for gifted education(2023-2027), "Ministry of Education.", Ministry of Education, ~ (2023)
  37. Science talent identification and development strategies : The 4th comprehensive plan for science talent identification and development(2023-2025), "Ministry of Science and ICT.", Ministry of Science and ICT, ~ (2023)
  38. Olszewski-Kubilius, P., "The future of research in talent development: Promising trends, evidence, and implications of innovative scholarship for policy and practice", pp.161~176 (2019), New Directions for Child and Adolescent Development
  39. Oh, Y. S., "A study on stress factors of scientifically gifted students", The Journal of the Korean Society for the Gifted and Talented, 17(3), pp.101~123 (2018)
  40. Park, J. J., "Analyzing social perception of gifted students and gifted education using topic modeling", Journal of Gifted, 2022, pp.32(2), 187~205
  41. Park, K. B., "Analysis of research trends on gifted education in Korea", Journal of Gifted, 2012, pp.22(4), 823~840
  42. Park, K. J., "The differences on science-gifted education beneficiaries’ perception about gifted education curriculum operation among the gifted class, gifted education center affiliated with metropolitan office of education, and university", Journal of Gifted, 2017, pp.27(4), 565~585
  43. Park, M. S., "Comparison of character strengths, emotional intelligence, and learning flow between elementary gifted students and general students and analysis of the relationships", Journal of Gifted, 2014, pp.24(5), 829~849
  44. Rinn, A. N., "Conducting research on psychosocial skills associated with academic talent development", Journal for the Education of the Gifted, 47(4), pp.340~356 (2024)
  45. Roeper, A., "A personal statement of philosophy of George and Annemarie Roeper", Roeper Review, 19, pp.18~19 (1996)
  46. Student selection for gifted students, "Seo, Y. W.", KEDI, ~, pp.Research Report RR 2015-15 (2015)
  47. Seok, I. B., "Analyzing characters of the learning flow", Journal of Educational Technology, 24(1), pp.187~212 (2008)
  48. Shernoff, D. J., "Student engagement as a function of environmental complexity in high school classrooms", Learning and Instruction, 43, pp.52~60 (2016)
  49. Subotnik, R. F., "Rethinking giftedness and gifted education : A proposed direction forward based on psychological science", Psychological Science in the Public Interest, 12(1), pp.3~54 (2011)
  50. Subotnik, R. F., "Should eminence based on outstanding innovation be the goal of gifted education and talent development? Implications for policy and research", Learning and Individual Differences, 20(4), pp.358~364 (2010)
  51. Tannenbaum, A. J., "Handbook of gifted education", pp.45~59 (2003), Allyn & Bacon
  52. Verschuren, K., "The role of psychosocial and contextual factors in academic talent development : In search of general and specific developmental processes", Journal for the Education of the Gifted, 47(3), pp.1~28 (2024)
  53. Whybra, J., "Meeting the social and emotional needs of gifted and talented children", pp.99~118 (2000), David Fulton Publisher
  54. Won, Y. K., "Analysis of research trends in Korean English education journals using topic modeling", Journal of the Korea Contents Association, 21(4), pp.50~59 (2021)
  55. Yang, T. Y., "Trends of domestic and international creativity education research using topic modeling", The Journal of Creativity Education, 21(2), pp.23~46 (2021)
  56. Yoo, M. H., "Exploring teachers' perceptions and support strategies for highly gifted students : focusing on topic modeling and language network analysis", Journal of Gifted, 2024, pp.34(2), 183~201
  57. Yoon, J, A., "Investigating trends of gifted education in domestic and foreign countries through social network analysis from 2010 to 2015", Journal of Gifted, 2016, pp.26(2), 347~363
  58. Yoon, J, A., "Research trends in science gifted education from 2011 to 2015 : Literature analysis vs social network analysis", Journal of Science Education, 40(3), pp.267~286 (2016)

관련 논문AI추천

과학영재가 과학영재학교에서의 학습활동을 통해 과학자로 성장해나가는 과정에 대한 질적 연구박경희, 서혜애, 정용석한국과학영재교육학회 · 과학영재교육2024 · 제16권 제3호토픽 모델링을 활용한 과학영재교육 연구동향 분석김혜원, 전영석한국초등과학교육학회 · 초등과학교육2021 · 제40권 제3호텍스트 분석에 기초한 영재교육원 관련 연구의 동향과 전망민소원, 장원형, 홍훈기한국과학영재교육학회 · 과학영재교육2019 · 제11권 제3호과학영재가 친구와 함께 하는 학습몰입의 경험에 나타난 심리사회적 기술의 특징에 대한 질적 연구박경희, 서혜애, 정용석한국영재교육학회 · 영재와 영재교육2024 · 제23권 제3호네트워크 텍스트 분석과 토픽모델링을 활용한 과학(영재)고 교육활동 내용분석김정은, 오영교한국영재학회 · 영재교육연구2023 · 제33권 제3호초등 과학영재 학생의 과학 학업 열정 향상을 위한 학습 경험 탐색강훈식, 고예영, 유지연한국초등과학교육학회 · 초등과학교육2023 · 제42권 제2호

이 간행물의 다른 논문 (12건)

과학교육 전문가의 ChatGPT 활용 SSI 교육 개념틀 개발 과정 분석이지애, 박현주, 최성연, 이화선, 정진수pp. 131-143과학자의 실험과 과학 수업에서 실험 목적에 대한 초등 3학년생들의 인식 비교장명덕pp. 144-153문항 및 피드백 생성에서 규칙기반모형과 대규모 언어모형 비교김성연, 정진민pp. 154-169초등학교 환경교육 관련 성취 기준 및 내용 요소의 분석박재근pp. 170-181환경·지속가능발전 교육을 위한 협업 네트워크 모델 탐색오현정, 김서현, 손연아, 박병열pp. 182-197
원문 보기