다이내믹 토픽 모델링을 통한 2010년대 중반 이후 학습분석학 해외 연구 동향 분석
Analysis of global research trends in learning analytics since the mid-2010s through dynamic topic modeling
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
지능정보사회의 도래 이후 등장한 디지털 대전환의 흐름은 교육 현장에 전례 없는 변화를 일으키고있다. 인공지능 및 빅데이터 기술의 발전에 토대를 두고 있는 이러한 변화는 다양한 학습자 데이터의수집과 분석을 가능하게 함으로써 학습분석학의 성장에 기여했으며, 특히 2012년 AlexNet의 등장 이후딥러닝 기반의 신경망 기술이 본격적으로 확산되면서 학습자의 데이터를 더욱 정교하게 분석하고 이를 통해 학습 환경을 최적화하기 위한 연구가 다양한 형태로 이루어지고 있다. 이러한 맥락에서 본연구는 2010년대 중반 이후 학습분석학 분야의 해외 연구 동향을 파악하고자 하며, 이를 위해 2015년1월부터 2024년 7월까지 학습분석학이 적용된 해외 논문 3,372편을 검토하였다. 특히 2010년대 중반이후 학습분석학 연구의 주요 주제와 연도별 핵심어를 탐색하기 위해, 대규모의 문서에 대해 주제의변화를 시계열적으로 분석하여 새로운 통찰력을 도출하는데 적합한 다이내믹 토픽 모델링(Dynamic Topic Modeling, DTM) 기법을 활용하여 토픽의 변화를 종단적으로 분석하였다. 분석 결과, 2010년대 중반 이후 학습분석학 분야의 해외 연구 동향에 대해 ‘컴퓨터 기반 협력 학습 연구’, ‘기계학습 기반 학업성취도 예측 연구’, ‘교육정보기술 플랫폼의 활용 방안 연구’, ‘온라인 학습 상황의 학습자 참여도연구’, ‘교수 설계 및 평가 연구’, ‘학습분석학 관련 동향 연구’의 6개 주요 토픽이 도출되었다. 본 연구는 DTM 분석의 접근을 통해 2010년대 중반 이후 학습분석학의 해외 연구 동향을 살펴보고 국내학습분석학 연구의 현주소를 검토한다는 점에서 의미를 갖는다.
Abstract
The emergence of the intelligent information society, coupled with the subsequent digital transformation, has engendered unprecedented shifts within the field of education. Underpinned by advancements in artificial intelligence and big data technologies, these developments have facilitated the comprehensive collection and analysis of diverse learner data, thereby accelerating the expansion of learning analytics. Following the introduction of AlexNet in 2012, the proliferation of deep learning-based neural networks has enabled increasingly nuanced analyses of learner data, stimulating a range of research dedicated to optimizing educational environments. To explore the principal themes and annual keywords of learning analytics research since the mid-2010s, this study employs the Dynamic Topic Modeling (DTM) technique-a method well-suited for deriving novel insights by longitudinally analyzing thematic shifts within large-scale corpora. The findings of our analysis revealed six major themes in international learning analytics research since the mid-2010s: ‘computer-supported collaborative learning research,’ ‘machine learning-based academic performance prediction research,’ ‘studies on the utilization of EdTech platforms,’ ‘research on learner engagement in online learning environments,’ ‘instructional design and evaluation research,’ and ‘trends in learning analytics research.’ This study is significant in that it not only examines global research trends in learning analytics since the mid-2010s through the lens of DTM analysis but also provides a critical review of the current state of domestic learning analytics research.
참고문헌 (36)
- 박연정, "학습분석학 기반 대시보드의 설계와 적용", 교육정보미디어연구, 20(2), pp.191~216 (2014)
- 안미리, "해외 학습분석학 연구에 대한 동향 분석 : 실증 연구 중심으로", 교육정보미디어연구, 21(4), pp.601~643 (2015)
- "The history began from AlexNet: A comprehensive survey on deep learning approaches"[URL]
- Blei, D. M., "Dynamic topic models", Proceedings of the 23rd International Conference on Machine Learning, pp.113~120 (2006), Association for Computing Machinery
- Blei, D. M., "Latent dirichlet allocation", Journal of Machine Learning Research, 3, pp.993~1022 (2003)
- Braun, V., "Using thematic analysis in psychology", Qualitative Research in Psychology, 3(2), pp.77~101 (2006)
- Campbell, J. P., "Academic analytics : A new tool for a new era", EDUCAUSE review, 42(4), pp.40~57 (2007)
- Chinese Academy of Engineering, "The development of deep learning technologies" (2020), Springer
- Ferguson, R., "Learning analytics: Drivers, developments and challenges", International Journal of Technology Enhanced Learning, 4(5, pp.6) (2012), 304~317
- Gašević, D., "Let’s not forget : Learning analytics are about learning", TechTrends, 59(1), pp.64~71 (2015)
- Hinton, G. E., "A fast learning algorithm for deep belief nets", Neural Computation, 18(7), pp.1527~1554 (2006)
- Holmes, W., "Artificial intelligence in education: Promises and implications for teaching and learning" (2019), Center for Curriculum Redesign
- Jayashanka, R., "Technology enhanced learning analytics dashboard in higher education", Electronic Journal of E-Learning, 20(2), pp.151~170 (2022)
- "AlexNet: A revolutionary deep learning architecture" (2024)[URL]
- Lang, C., "Handbook of learning analytics" (2017), Society for Learning Analytics and Research
- Lang, C., "Handbook of learning analytics", pp.8~18 (2022), Society for Learning Analytics Research
- Lawson, C., "Identification of ‘at risk’ students using learning analytics : The ethical dilemmas of intervention strategies in a higher education institution", Educational Technology Research and Development, 64(5), pp.957~968 (2016)
- Mangaroska, K., "Learning analytics for learning design : A systematic literature review of analytics-driven design to enhance learning", IEEE Transactions on Learning Technologies, 12(4), pp.516~534 (2018)
- Mayer-Schönberger, V., "Learning with big data: The future of education" (2014), Houghton Mifflin Harcourt Publishing
- Merceron, A., "Learning analytics : From big data to meaningful data", Journal of Learning Analytics, 2(3), pp.4~8 (2015)
- State of the field report on learning analytics, "Misiejuk, K.", Centre for the Science of Learning & Technology, ~, pp.SLATE Report 2017-2 (2017)
- Namoun, A., "Predicting student performance using data mining and learning analytics techniques : A systematic literature review", Applied Sciences, 11(1), pp.237~ (2020)
- Oliva-Córdova, L. M., "Learning analytics to support teaching skills : A systematic literature review", IEEE Access, 9, pp.58351~58363 (2021)
- 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)
- Paulsen, L., "Learning analytics dashboards are increasingly becoming about learning and not just analytics-A systematic review", Education and Information Technologies, 29(11), pp.14279~14308 (2024)
- Sghir, N., "Recent advances in predictive learning analytics : A decade systematic review(2012-2022)", Education and Information Technologies, 28(7), pp.8299~8333 (2023)
- Shafiq, D. A., "Student retention using educational data mining and predictive analytics : A systematic literature review", IEEE Access, 10, pp.72480~72503 (2022)
- Siemens, G., "Learning analytics : The emergence of a discipline", American Behavioral Scientist, 57(10), pp.1380~1400 (2013)
- Siemens, G., "Learning analytics and educational data mining: Towards communication and collaboration", Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, pp.252~254 (2012), Association for Computing Machinery
- "What is learning analytics?"[URL]
- Tzeng, J., "MOOC evaluation system based on deep learning", International Review of Research in Open and Distributed Learning, 23(1), pp.21~40 (2022)
- Enhancing teaching and learning through educational data mining and learning analytics: An issue brief, "U.S. Department of Education", U.S. Department of Education, ~ (2012)
- Viberg, O., "The current landscape of learning analytics in higher education", Computers in Human Behavior, 89, pp.98~110 (2018)
- Vieira, C., "Visual learning analytics of educational data : A systematic literature review and research agenda", Computers & Education, 122, pp.119~135 (2018)
- Weston, S. J., "Selecting the number and labels of topics in topic modeling : A tutorial", Advances in Methods and Practices in Psychological Science, 6(2), pp.1~13 (2023)
- Ye, D., "The history and development of learning analytics in learning, design, & technology field", TechTrends, 66(4), pp.607~615 (2022)