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국내외 협력학습분석학(Collaboarative Learning Analytics) 연구 동향에 대한 체계적 문헌고찰

Systematic Literature Review of Research Trends in Collaborative Learning Analytics

정유진|이다혜|김혜준|진명화|임규연
한국교육공학회 (Korean Society Of Educational Technology)|2023.12|교육공학연구 (Journal of Educational Technology)|제39권 제4호|pp. 1081-1121|DOI http://dx.doi.org/10.17232/KSET.39.4.1081

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키워드

체계적 문헌고찰systematic literature review학습분석학learning analytics컴퓨터기반협력학습CSCL협력학습분석학collaborative learning analytics
주제분류교육학

초록

최근 컴퓨터기반 협력학습(CSCL)에서 나타나는 협력 과정을 이해하고 CSCL 과정을 지원하기 위해 협력학습과 학습분석학을 접목하는 협력학습분석학(Collaborative Learning Analytics)이 시도되고 있다. 본 연구는 2014년부터 2023년 4월까지 국내외에서 발표된 협력학습분석학 문헌에 대해 체계적 문헌고찰을 실시함으로써 협력학습분석학의 연구 동향을 분석하고 시사점을 제공하고자 하였다. 이를 위해 국내외 관련 연구 60편을 선정하고, 선행연구에서 도출한 프레임워크를 활용하여 연구 목적과 연구 대상, 연구 맥락, 수집 데이터의 유형, 데이터 분석 방법을 분석하였다. 또한 각 문헌에서 탐색한 CSCL 구인을 수집 데이터 종류 및 데이터 분석 방법과 연계하여 분석하였다. 문헌 분석 결과, 협력학습분석학 연구는 최근 10년간 전반적으로 증가하는 추세를 보였다. 연구 목적은 행동 모델링이 가장 높게 나타났으며, 데이터 유형은 로그데이터와 비디오 및 오디오 데이터가 높은 빈도로 수집되고 있었다. 분석 방법은 협력학습의 과정에 초점을 두는 과정 중심 분석이 가장 활발히 실시되었으며, 그중에서도 특히 프로세스 마이닝이 빈번하게 사용되었다. CSCL 구인과 데이터 유형, 분석 방법을 연계하여 분석한 결과, 참여 범주와 긍정적 상호의존성 범주에 포함된 CSCL 구인이 높은 빈도를 차지하였으며, 수집된 데이터 유형이나 분석 방법은 CSCL 구인에 따라 다양하게 나타났다. 도출한 결과를 바탕으로 실천적 목적을 가진 협력학습분석학 연구의 필요성, 연구에서 수집하는 데이터 유형의 다양화, 이론 기반의 협력학습분석학으로 나아가기 위한 향후 연구 방향에 대한 시사점을 제시하였다.

Abstract

Collaborative learning analytics, which integrates collaborative learning and learning analytics to understand and support collaborative processes in Computer-Supported Collaborative Learning(CSCL), has emerged in recent years. This study aims to conduct a systematic literature review of publications from 2014 to April 2023 to analyze research trends in collaborative learning analytics. To achieve this goal, 60 documents were selected and examined in terms of the research objectives, research contexts, types of collected data, and analysis methods. The findings were aligned with CSCL constructs, collected data, and analysis methods, following the clicks-to-constructs approach. The results indicate an overall increasing trend in collaborative learning analytics research. The research objectives focused on behavior modeling, and the primary type of collected data was log data. The principle approach to data analysis involved a process-oriented analysis. An examination of the alignment between CSCL constructs, data, and methods revealed a high proportion of CSCL constructs in the categories of engagement. Data types and analysis methods exhibited diversity depending on the CSCL constructs. Based on the findings, the study suggested implications, including the need for collaborative learning analytics with an actionable purpose and the advancement toward theory-driven collaborative learning analytics in the future.

참고문헌 (51)

  1. 임규연, "온라인 토론학습에서 사회연결망분석 기반 피드백이 상호작용 및 성취도에 미치는 영향", 교육공학연구, 30(3), pp.443~466 (2014), 한국교육공학회
  2. 조영환, "학습분석 기반 적응적 협력학습 지원에 대한 학습자의 인식", 교육정보미디어연구, 25(1), pp.25~57 (2019), 한국교육정보미디어학회[DOI]
  3. Bao, H., "The effects of a learning analytics dashboard on teachers’ diagnosis and intervention in computer-supported collaborative learning", Pedagogy and Education, 30(2), pp.287~303 (2021)
  4. Blumenfeld, P. C., "The Cambridge handbook of the learning sciences", pp.475~488 (2006), Cambridge University Press
  5. Chatti, M. A., "A reference model for learning analytics", International Journal of Technology Enhanced Learning, 4(5-6), pp.318~331 (2012)
  6. Chen, B., "Handbook of learning analytics", pp.86~95 (2022), Society for Learning Analytics Research
  7. Chi, M. T., "The ICAP framework: Linking cognitive engagement to active learning outcomes", Educational Psychologist, 49(4), pp.219~243 (2014)
  8. Cress, U., "The international handbook of collaborative learning", pp.93~111 (2013), Springer
  9. Csanadi, A., "When coding-and- counting is not enough: Using epistemic network analysis (ENA) to analyze verbal data in CSCL research", International Journal of Computer-Supported Collaborative Learning, 13(4), pp.419~438 (2018)
  10. Dillenbourg, P, "Collaborative learning: Cognitive and computational approaches", pp.1~19 (1999), Emerald Group Publishing Limited
  11. Dindar, M., "Detecting shared physiological arousal events in collaborative problem solving", Contemporary Educational Psychology, 69, pp.102050~ (2022)
  12. Dönmez, P., "Computer-Supported Collaborative Learning 2005", pp.125~134 (2005), Routledge
  13. Hadwin, A., "Handbook of self-regulation of learning and performance", pp.83~106 (2017), Routledge
  14. Hmelo-Silver, C. E., "Handbook of educational psychology", pp.363~377 (2015), Routledge
  15. Hmelo-Silver, C. E., "International Handbook of Computer-Supported Collaborative Learning", pp.65~83 (2021), Springer International Publishing
  16. Hoppe, H. U, "Handbook of learning analytics", pp.23~33 (2017), SOLAR
  17. Galikyan, I., "Students' engagement in asynchronous online discussion: The relationship between cognitive presence, learner prominence, and academic performance", The Internet and Higher Education, 43, pp.100692~ (2019)
  18. Gasevic, D., "Let’s not forget : Learning analytics are about learning", TechTrends, 59(1), pp.64~71 (2015)
  19. Goodyear, P., "Handbook of research on educational communications and technology", pp.439~451 (2014), Springer
  20. Gunawardena, C. N., "Analysis of a global online debate and the development of an interaction analysis model for examining social construction of knowledge in computer conferencing", Journal of Educational Computing Research, 17(4), pp.397~431 (1997)
  21. Järvelä, S., "Bridging learning sciences, machine learning and affective computing for understanding cognition and affect in collaborative learning", British Journal of Educational Technology, 51(6), pp.2391~2406 (2020)
  22. Järvelä, S., "What multimodal data can tell us about the students’ regulation of their learning process", Learning and Instruction, 72, pp.101203~ (2021)
  23. Jeong, H., "An Overview of CSCL Methodologies", Learning in the Disciplines: Proceedings of the 9th International Conference of the Learning Sciences (ICLS 2010), 1, pp.921~928 (2010), International Society of the Learning Sciences
  24. Jeong, H., "An examination of CSCL methodological practices and the influence of theoretical frameworks 2005-2009", International Journal of Computer-Supported Collaborative Learning, 9, pp.305~334 (2014)
  25. Johnson, D. W., "Handbook of research on educational communications and technology", pp.401~425 (2008), Routledge
  26. Jovanović, J., "Learning analytics to unveil learning strategies in a flipped classroom", Internet and Higher Education, 33, pp.74~85 (2017)
  27. Kapur, M., "Examining the effect of problem type in a synchronous computer-supported collaborative learning(CSCL)environment", Educational Technology Research and Development, 55, pp.439~459 (2007)
  28. Kew, S. N., "Learning analytics in online learning environment: A systematic review on the focuses and the types of student-related analytics data", Technology, Knowledge and Learning, 27, pp.1~23 (2022)
  29. Knight, S., "Epistemology, assessment, pedagogy : Where learning meets analytics in the middle space", Journal of Learning Analytics, 1(2), pp.23~47 (2014)
  30. Long, P., "Penetrating the fog : Analytics in learning and education", Educause Review, 46(5), pp.31~40 (2011)
  31. Ludvigsen, S., "The international handbook of collaborative learning", pp.45~63 (2021), Springer
  32. Martinez-Maldonado, R., "What do you mean by collaboration analytics? A conceptual model", Journal of Learning Analytics, 8(1), pp.126~153 (2021)
  33. Newman, M., "Systematic reviews in educational research: Methodology, perspectives and application", pp.3~22 (2020), Springer
  34. Nistor, N., "What types of data are used in learning analytics? An overview of six cases", Computers in Human Behavior, 89, pp.335~338 (2018)
  35. Oikarinen, J. K., "Finnish upper secondary students’ collaborative processes in learning statistics in a CSCL environment", International Journal of Mathematical Education in Science and Technology, 45(3), pp.325~348 (2014)
  36. Papamitsiou, Z., "Learning analytics and educational data mining in practice : A systematic literature review of empirical evidence", Journal of Educational Technology & Society, 17(4), pp.49~64 (2014)
  37. Paulus, T. M., "Looking for insight, transformation, and learning in online talk" (2019), Routledge
  38. Roschelle, J., "Computer-supported collaborative learning Vol. 128", pp.69~97 (1995), Springer
  39. Schneider, B., "Collaboration analytics-current state and potential futures", Journal of Learning Analytics, 8(1), pp.1~12 (2021)
  40. Schneider, B., "Real-time mutual gaze perception enhances collaborative learning and collaboration quality", International Journal of Computer-Supported Collaborative Learning, 8(4), pp.375~397 (2013)
  41. Schneider, B., "International handbook of computer-supported collaborative learning", pp.625~641 (2021), Springer International Publishing
  42. Schunk, D. H., "Handbook of self-regulation of learning and performance", pp.1~15 (2017), Routledge
  43. Siemens, G., "Learning analytics : The emergence of a discipline", American Behavioral Scientist, 57(10), pp.1380~1400 (2013)
  44. Song, Y., "Mapping primary students’ mobile collaborative inquiry-based learning behaviours in science collaborative problem solving via learning analytics", International Journal of Educational Research, 114, pp.101992~ (2022)
  45. Stahl, G., "The cambridge handbook of the learning sciences", pp.479~500 (2014), Cambridge University Press
  46. Vogel, F., "International handbook of the learning sciences", pp.500~510 (2018), Routledge
  47. Vujovic, M., "Round or rectangular tables for collaborative problem solving? A multimodal learning analytics study", British Journal of Educational Technology, 51(5), pp.1597~1614 (2020)
  48. Wang, Q., "A scoping review of empirical studies on theory-driven learning analytics", Distance Education, 43(1), pp.6~29 (2022)
  49. Wise, A. F., "The international handbook of collaborative learning", pp.425~443 (2021), Springer
  50. Wise, A. F., "Nine elements for robust collaborative learning analytics: A constructive collaborative critique", International Journal of Computer-Supported Collaborative Learning, 18(1), pp.1~9 (2023)
  51. Wise, A. F., "Visions of CSCL: Eight provocations for the future of the field", International Journal of Computer-Supported Collaborative Learning, 12, pp.423~467 (2017)

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