본문 바로가기
KERD
논문KCI 등재

개별화 학습 지원을 위한 지능형 튜터링 시스템 연구 동향 분석: LDA 토픽 모델링을 활용하여

Analysis of Research Trends on Intelligent Tutoring Systems for Supporting Personalized Learning Using LDA Topic Modeling

신서경|장지수
한국교육정보미디어학회 (Korea Association for Educational Information and Media)|2023.12|교육정보미디어연구 (Journal of Korean Association for Educational Information and Media)|제29권 제4호|pp. 1095-1122

0

조회

0

다운로드

2

인용

0

참고문헌

키워드

LDA 토픽 모델링LDA Topic Modeling키워드 네트워크 분석Keyword Network AnalysisIntelligent Tutoring System개별화 학습적응형 학습Personalized LearningAdaptive Learning지능형 튜터링 시스템
주제분류교육학

초록

본 연구는 인공지능 활용 교육 맥락에서 개별화 학습을 지원하기 위한 테크놀로지 중 하나인 지능형 튜터링 시스템(Intelligent Tutoring System, ITS)의 연구 주제 동향을 종합적인 시각에서 파악하고자 하였다. 이를 위해 본 연구는 Scopus, Web of Science, ACM Digital Library를 활용하여 2013년부터 2022년까지 최근 10년간 발행된 학술지 논문 836편을 대상으로 키워드 네트워크 분석과 토픽 모델링을 실시하였다. 연구 결과, ITS와 관련된 연구에서는 개별화 및 적응형 학습과 관련된 키워드들이 자주 등장함과 동시에 학습자 중심의 키워드들이 주를 이루고 있었다. 또한 ITS 연구를 구성하는 핵심 연구 주제는 총 4개로 도출되었으며, 이는 각각 ‘적응형 학습 시스템 구축을 위한 ITS 모델 설계 및 교육 프로그램 개발’, ‘학습자의 문제 해결 지원을 위한 피드백과 스캐폴딩 제공 전략 설계’, ‘학습자 성취 수준 진단 및 학습 경로 예측을 위한 알고리즘 설계’, ‘인간 - 컴퓨터 상호작용(HCI)을 위한 대화 분석 및 시스템 설계’로 명명하였다. 이때 연구 주제별로 주목할 특징으로는 ‘학습자의 문제 해결 지원을 위한 피드백과 스캐폴딩 제공 전략 설계’ 주제의 비중이 가장 높은 논문의 비율은 최근 10년간 대부분의 연도에서 가장 높은 수치를 보이고 있었으며, ‘학습자 성취 수준 진단 및 학습 경로 예측을 위한 알고리즘 설계’ 연구는 ITS에 관한 다른 세 연구 주제와는 상대적으로 유사성이 떨어지며 독립적인 맥락의 연구 주제를 형성하고 있었다. 연구 결과에 기초하여 미래 교육 현장에 ITS가 성공적으로 도입되기 위한 후속 연구 방향을 제언하였다.

Abstract

This study identifies trending research topics on intelligent tutoring systems(ITS), technology used to support personalized learning in the context of artificial intelligence in education. Scopus, the Web of Science, and the ACM Digital Library were used to perform keyword network analysis and LDA topic modeling for 836 papers from academic journals published in the 10-year period from 2013 to 2022. The results show that keyword related to personalized and adaptive learning frequently appeared in research related to ITS, as well as learner-centered keyword. Among the research topics, four key themes emerged: (1) ITS model design and educational program development for adaptive learning systems, (2) feedback design and scaffolding strategies to support learners’ problem-solving, (3) algorithm design for learner achievement diagnosis and learning path prediction, and (4) dialog analysis and system design for human–computer interaction (HCI). Notably, the topic with the highest in most of the years was feedback design and scaffolding strategies. In addition, the topic of algorithm design for learner’s learning paths was relatively less similar to the other three research topics and formed an independent context. Findings and implications suggest what topics can be focused on in ITS-related research to successfully introduce ITS to future education environments. Areas for follow-up research are also suggested based on the limitations of this research.

참고문헌 (88)

  1. 인공지능(AI) 디지털교과서로 1:1 맞춤 교육시대 연다, "교육부", 교육부, ~ (2023)
  2. 인공지능을 활용한 디지털 교육으로 ‘모두를 위한 맞춤 교육시대’연다, "교육부", 교육부, ~ (2023)
  3. 김은경, "토픽 모델링과 키워드 네트워크 분석을 활용한 국내 성인 대상 교육훈련 요구분석 연구동향: 2012-2021년 학술지 게재 논문을 중심으로", HRD연구, 24(1), pp.397~421 (2022), 한국인력개발학회[DOI]
  4. 노동원, "키워드 네트워크 분석(keyword network analysis)을 통한 국내 코칭 연구 동향 분석", HRD연구, 23(2), pp.91~121 (2021), 한국인력개발학회[DOI]
  5. 류지헌, "학습용 에이전트의 사실성 수준과 대화식 내레이션이 의인화 지각에 미치는 영향", 교육정보미디어연구, 19(1), pp.55~82 (2013), 한국교육정보미디어학회
  6. 류지헌, "학습용 에이전트의 제스처와 얼굴표정이 학습이해도 및 의인화 효과에 미치는 영향", 감성과학, 16(3), pp.281~292 (2013), 한국감성과학회
  7. 박성익, "개별화학습의 전망과 과제", 교육방법연구, 20(1), pp.1~22 (2008), 한국교육방법학회[DOI]
  8. 박자현, "토픽모델링을 활용한 국내 문헌정보학 연구동향 분석", 정보관리학회지, 30(1), pp.7~32 (2013), 한국정보관리학회[DOI]
  9. 송유경, "디자인 씽킹 기반 인공지능 서비스 기획 교육 프로그램 개발 연구", 교육정보미디어연구, 27(2), pp.619~650 (2021), 한국교육정보미디어학회
  10. 임규연, "테크놀로지 기반 개별화 학습에 대한 체계적 문헌 분석: 2011-2020년 국내연구를 중심으로", 교육공학연구, 37(3), pp.525~559 (2021), 한국교육공학회[DOI]
  11. 임철일, "미래 사회와 교육을 위한 교육공학 연구 및 실천 영역의 재조명", 교육공학연구, 35(2), pp.253~287 (2019), 한국교육공학회[DOI]
  12. 장혜원, "초등수학교육에서 인공지능 활용의 실제- 초등수학 수업지원시스템 ‘똑똑! 수학탐험대’를 중심으로-", 한국초등교육, 31, pp.105~123 (2021), 초등교육연구원[DOI]
  13. 홍성연, "토픽 모델링 분석 기법을 활용한 대학의 학생 지원 연구 동향 분석", 학습자중심교과교육연구, 17(8), pp.21~48 (2017), 학습자중심교과교육학회[DOI]
  14. Abdelrahman, G., "Knowledge tracing : A survey", ACM Computing Surveys, 55(11), pp.1~37 (2023)
  15. Aggarwal, C. C., "Mining text data", pp.1~10 (2012), Springer
  16. Aleven, V., "Handbook of Research on Learning and Instruction", pp.522~560 (2017), Routledge
  17. Alkhatlan, A., "Intelligent tutoring systems : A comprehensive historical survey with recent developments", International Journal of Computer Applications, 181(43), pp.1~20 (2018)
  18. Amit, K., "Learning styles based adaptive intelligent tutoring systems: Document analysis of articles published between 2001 and 2016", International Journal of Cognitive Research in Science, Engineering and Education, 5(2), pp.83~98 (2017)
  19. Afzal, S., "Artificial Intelligence in Medicine", pp.133~145 (2020), Springer
  20. Balakrishnan, V., "Stemming and lemmatization: A comparison of retrieval performances", Lecture Notes on Software Engineering, 2(3), pp.262~267 (2014)
  21. Baker, R. S., "Stupid tutoring systems, intelligent humans", International Journal of Artificial Intelligence in Education, 26, pp.600~614 (2016)
  22. Belland, B. R., "A framework for designing scaffolds that improve motivation and cognition", Educational Psychologist, 48(4), pp.243~270 (2013)
  23. Bernacki, M. L., "The role of situational interest in personalized learning", Journal of Educational Psychology, 110(6), pp.864~ (2018)
  24. Bingham, A. J., "Ahead of the curve : Implementation challenges in personalized learning school models", Educational Policy, 32(3), pp.454~489 (2018)
  25. Blei, D. M., "Latent dirichlet allocation", Journal of Machine Learning Research, 3, pp.993~1022 (2003)
  26. Blei, D. M., "Probabilistic topic models", Communications of the ACM, 55(4), pp.77~84 (2012)
  27. Bloom, B. S., "The 2 sigma problem : The search for methods of group instruction as effective as one-to-one tutoring", Educational Researcher, 13(6), pp.4~16 (1984)
  28. Bouchet, F., "Evaluating adaptive pedagogical agents’ prompting strategies effect on students’ emotions", Intelligent Tutoring Systems: 14th International Conference, pp.33~43 (2018)
  29. Boyer, K. E., "Investigating the role of student motivation in computer science education through one-on-one tutoring", Computer Science Education, 19(2), pp.111~135 (2009)
  30. Cao, J., "Student acceptance of intelligent tutoring systems during COVID-19: The effect of political influence", The International Journal of Electrical Engineering & Education (2021)
  31. Chang, J., "Reading tea leaves : How humans interpret topic models", Advances in Neural Information Processing Systems, 22 (2009)
  32. Chang, M., "Building ontology-driven tutoring models for intelligent tutoring systems using data mining", IEEE Access, 8, pp.48151~48162 (2020)
  33. Corbett, A. T., "Handbook of human-computer interaction", pp.849~874 (1997), Elsevier Science
  34. Das, K., "Study on centrality measures in social networks : A survey", Social Network Analysis and Mining, 8, pp.1~11 (2018)
  35. Deerwester, S., "Indexing by latent semantic analysis", Journal of the American Society for Information Science, 41(6), pp.391~407 (1990)
  36. Dermeval, D., "Authoring tools for designing intelligent tutoring systems : A systematic review of the literature", International Journal of Artificial Intelligence in Education, 28, pp.336~384 (2018)
  37. Dillenbourg, P., "Design for classroom orchestration", Computers & Education, 69, pp.485~492 (2013)
  38. Doo, M. Y., "A meta-analysis of scaffolding effects in online learning in higher education", International Review of Research in Open and Distributed Learning, 21(3), pp.60~80 (2020)
  39. Duffy, M. C., "Motivation matters : Interactions between achievement goals and agent scaffolding for self-regulated learning within an intelligent tutoring system", Computers in Human Behavior, 52, pp.338~348 (2015)
  40. Erdemir, M., "Investigating pre-service mathematics teachers’ innovation awareness and views regarding intelligent tutoring systems", Universal Journal of Educational Research, 4(12), pp.2783~2794 (2016)
  41. Fadel, C., "Artificial intelligence in education: Promises and implications for teaching and learning" (2019), The Center for Curriculum Redesign
  42. Feng, S., "A systematic review of literature on the effectiveness of intelligent tutoring systems in STEM", 2021 IEEE Frontiers in Education Conference, pp.1~9 (2021)
  43. González-Calero, J. A., "Intensive scaffolding in an intelligent tutoring system for the learning of algebraic word problem solving", British Journal of Educational Technology, 46(6), pp.1189~1200 (2015)
  44. Grant, S., "Reverse engineering co-maintenance relationships using conceptual analysis of source code", 2011 18th Working Conference on Reverse Engineering, pp.87~91 (2011)
  45. Heidig, S., "Do pedagogical agents make a difference to student motivation and learning", Educational Research Review, 6(1), pp.27~54 (2011)
  46. Holstein, K., "Intelligent tutors as teachers’ aides: Exploring teacher needs for real-time analytics in blended classrooms", Proceedings of the seventh international learning analytics & knowledge conference, pp.257~266 (2017)
  47. Holstein, K., "Co-designing a real-time classroom orchestration tool to support teacher–AI complementarity", Journal of Learning Analytics, 6(2), pp.27~52 (2019)
  48. Exploring acceptance of intelligent tutoring system with pedagogical agent among high school students, "Huang, H.", Universal Access in the Information Society, 1~12 (2022)
  49. Huang, X., "Intelligent tutoring systems work as a math gap reducer in 6th grade after-school program", Learning and Individual Differences, 47, pp.258~265 (2016)
  50. Jelodar, H., "Latent Dirichlet allocation(LDA)and topic modeling : models, applications, a survey", Multimedia Tools and Applications, 78, pp.15169~15211 (2019)
  51. Karaci, A., "Student perceptions of an intelligent tutoring system : A technology acceptance model perspective", International Journal of Computer Applications, 182(22), pp.31~36 (2018)
  52. Kim, N. J., "Scaffolding for optimal challenge in K–12 problem-based learning", Interdisciplinary Journal of Problem-Based Learning, 13(1), pp.1~23 (2019)
  53. King, C. L., "Intelligent tutoring system : Learning math for 6th-grade primary school students", Education Research International, 2021, pp.1~10 (2021)
  54. Koedinger, K. R., "Exploring the assistance dilemma in experiments with cognitive tutors", Educational Psychology Review, 19, pp.239~264 (2007)
  55. Koedinger, K. R., "The Cambridge handbook of the learning sciences", pp.61~77 (2006), Cambridge University Press
  56. Kulik, J. A., "Effectiveness of intelligent tutoring systems : A meta-analytic review", Review of Educational Research, 86(1), pp.42~78 (2016)
  57. Liu, T., "Knowledge tracing: A bibliometric analysis", Computers and Education: Artificial Intelligence, pp.100090~ (2022)
  58. Ma, W., "Intelligent tutoring systems and learning outcomes : A meta-analysis", Journal of Educational Psychology, 106(4), pp.901~918 (2014)
  59. Merrill, D. C., "Effective tutoring techniques : A comparison of human tutors and intelligent tutoring systems", Journal of the Learning Sciences, 2(3), pp.277~305 (1992)
  60. Mihalcea, R., "Textrank: Bringing order into text", Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, pp.404~411 (2004)
  61. Mohamed, H., "Implementing flipped classroom that used an intelligent tutoring system into learning process", Computers & Education, 124, pp.62~76 (2018)
  62. Mousavinasab, E., "Intelligent tutoring systems : A systematic review of characteristics, applications, and evaluation methods", Interactive Learning Environments, 29(1), pp.142~163 (2021)
  63. Newman, D., "Automatic evaluation of topic coherence", Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp.100~108 (2010)
  64. Nwana, H. S., "Intelligent tutoring systems : an overview", Artificial Intelligence Review, 4(4), pp.251~277 (1990)
  65. Nye, B. D., "Barriers to ITS adoption: A systematic mapping study", Intelligent Tutoring Systems: 12th International Conference, pp.583~590 (2014)
  66. O’callaghan, D., "An analysis of the coherence of descriptors in topic modeling", Expert Systems with Applications, 42(13), pp.5645~5657 (2015)
  67. Mean what you say: Defining and integrating personalized, blended and competency education, "Patrick, S.", International Association for K-12 Online Learning, ~ (2013)
  68. Phillips, A., "Implementing an adaptive intelligent tutoring system as an instructional supplement", Educational Technology Research and Development, 68, pp.1409~1437 (2020)
  69. Poquet, O., "Handbook of Learning Analytics", pp.38~45 (2022), Society for Learning Analytics Research
  70. Priyanta, S., "Social network analysis of twitter to identify issuer of topic using pagerank", International Journal of Advanced Computer Science and Applications, 10(1), pp.107~111 (2019)
  71. Rebolledo-Mendez, G., "New perspectives on affect and learning technologies", pp.155~168 (2011), Springer Science & Business Media
  72. Sharma, P., "Designing an intelligent tutoring system for computer programing in the Pacific", Education and Information Technologies, 27(5), pp.6197~6209 (2022)
  73. Shemshack, A., "A systematic literature review of personalized learning terms", Smart Learning Environments, 7(1), pp.1~20 (2020)
  74. Shin, D., "Teaching mathematics integrating intelligent tutoring systems: Investigating prospective teachers’ concerns and TPACK", International Journal of Science and Mathematics Education, pp.1~18 (2021)
  75. Sievert, C., "LDAvis: A method for visualizing and interpreting topics", Proceedings of the workshop on interactive language learning, visualization, and interfaces, pp.63~70 (2014)
  76. Steenbergen-Hu, S., "A meta-analysis of the effectiveness of intelligent tutoring systems on K–12 students’ mathematical learning", Journal of Educational Psychology, 105(4), pp.970~987 (2013)
  77. Steenbergen-Hu, S., "A meta-analysis of the effectiveness of intelligent tutoring systems on college students’academic learning", Journal of Educational Psychology, 106(2), pp.331~347 (2014)
  78. Su, J., "Research on the influence of computer aided intelligent tutoring system on teacher’s self-efficacy", Journal of Intelligent & Fuzzy Systems, 35(3), pp.2749~2759 (2018)
  79. Suebnukarn, S., "A Bayesian approach to generating tutorial hints in a collaborative medical problem-based learning system", Artificial intelligence in Medicine, 38(1), pp.5~24 (2006)
  80. Suebnukarn, S., "COMET: A collaborative tutoring system for medical problem-based learning", IEEE Intelligent Systems, 22(4), pp.70~77 (2007)
  81. Tchounikine, P., "Advances in intelligent tutoring systems", pp.447~463 (2010), Springer
  82. VanLehn, K., "The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems", Educational Psychologist, 46(4), pp.197~221 (2011)
  83. Wang, S., "Participant or spectator? Comprehending the willingness of faculty to use intelligent tutoring systems in the artificial intelligence era", British Journal of Educational Technology, 51(5), pp.1657~1673 (2020)
  84. Wasserman, S., "Social network analysis: Methods and applications" (1994), Cambridge University Press
  85. Watson, W. R., "Instructional-Design Theories and Models", pp.93~120 (2016), Routledge
  86. Xie, H., "Trends and development in technology-enhanced adaptive", personalized learning : A systematic review of journal publications from 2007 to 2017, 2019, pp.140, 103599~
  87. Xu, Z., "The effectiveness of intelligent tutoring systems on K-12 students’ reading comprehension : A meta-analysis", British Journal of Educational Technology, 50(6), pp.3119~3137 (2019)
  88. Zawacki-Richter, O., "Systematic review of research on artificial intelligence applications in higher education–where are the educators?", International Journal of Educational Technology in Higher Education, 16(1), pp.1~27 (2019)

관련 논문AI추천

텍스트 마이닝을 활용한 국내 개별화 학습 연구동향 분석: TF-IDF, LDA 기반 텍스트 마이닝을 중심으로박지우, 박하나, 임규연, 정성희한국교육방법학회 · 교육방법연구2022 · 제34권 제4호TF-IDF 분석과 토픽 모델링을 활용한 AI 기반 개별화 학습 국내외 연구동향 분석김세영한국정보교육학회 · 정보교육학회논문지2023 · 제27권 제4호AI 기반 적응형 학습 시스템에 대한 학습자 반응 분석: 토픽 모델링을 통한 적응성 진단김선영, 임규연한국교육정보미디어학회 · 교육정보미디어연구2025 · 제31권 제6호테크놀로지 기반 개별화 학습에 대한 체계적 문헌 분석: 2011-2020년 국내연구를 중심으로임규연, 임지영, 진명화한국교육공학회 · 교육공학연구2021 · 제37권 제3호다이내믹 토픽 모델링에 기초한 2011-2020 학습분석학 연구 동향 분석이대영, 이현숙한국교육정보미디어학회 · 교육정보미디어연구2021 · 제27권 제3호토픽모델링을 활용한 개별 맞춤형 학습에 관한 연구동향 : 초중등과 대학 수준 간 비교박종향, 안화실한국열린교육학회 · 열린교육연구2023 · 제31권 제6호

이 간행물의 다른 논문 (17건)

디지털 기술을 활용한 교사의 교육활동지원에 대한 요구분석진성희, 임동관, 유미나, 김성욱pp. 761-789수학, 과학 교육용 저작 도구에 대한 교사들의 사용성 평가 연구: STEAMuP의 사례를 중심으로이송희, 김영인, 박찬희, 이경화pp. 791-819대학교육에서 하이브리드 학습 운영을 위한 개념 모형 및 교수설계전략 개발 연구홍수민, 박성경, 한형종, 임은선, 김한휘, 임철일pp. 821-850잠재집단분석을 활용한 대학생의 디지털 리터러시 유형 분류 및 특성 분석강은하pp. 851-871대학생의 아바타 기반 실시간 온라인 토론 경험에 대한 미디어 생태학적 고찰최진, 임지은pp. 873-901
원문 보기