게임 기반 학습에서의 자기 조절 학습 행동 분석: 순서화된 네트워크 분석(Ordered Network Analysis)의 활용
Analysis of Self-Regulated Learning Behaviors in Game-Based Learning Using Ordered Network Analysis
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초록
이 연구에서는 대학원생 30명을 대상으로 자기 조절 학습을 촉진하기 위한 계획 도구를 포함한 게임 기반 학습을 시행하였다. 참여자가 플레이한 게임인 퓨쳐월드(Future Worlds)는 지속 가능 발전 교육을 위해 개발된 컴퓨터 게임이다. 게임플레이 전․후 참여자의 지속 가능 발전 관련 지식을 검사하고 그 결과를 t 검정하였다. 또한 학습자의 게임플레이 행동별 발생 빈도와 사전 지식을 상관분석 하였다. 게임플레이 행동의 시각화와 분석을 위해 수집된 로그 데이터 약 3 만개에 순서화된 네트워크 분석(Ordered Network Analysis)을 적용하였다. 네트워크 그래프 및 로그 데이터를 분석한 결과, 참여자에 따라 계획 도구의 활용 횟수와 패턴이 달랐다. 게임이 진행됨에 따라 전체 게임플레이 행동 중 문제 해결 행동을 제외한 자기 조절 학습 및 학습 행동이 감소하였다. 계획 도구의 활용 횟수에 따라 전체 참여자를 적극 계획 집단과 소극 계획 집단으로 나누고 게임플레이 패턴을 시각화한 결과, 적극 계획 집단은 학습 행동을 더 자주 하는 경향이 있었다. 그러나 두 집단의 지식 점수 향상 정도에 통계적으로 유의미한 차이가 없었다. 연구 결과를 바탕으로 게임 기반 학습에서 자기 조절 학습을 촉진하기 위한 전략과 게임 설계에 대한 시사점을 도출하였다.
Abstract
In this study, 30 graduate students played Futureworld, a sustainable development educational game that includes planning tools to promote self-regulated learning. Participants’ knowledge of sustainable development was examined before and after gameplay, with the data analyzed via t-tested. We also conducted a correlation analysis between the occurrence of each gameplay behavior and prior knowledge. Additionally, an Ordered Network Analysis was conducted on approximately 30,000 gameplay trace log data. The network graphs and log data suggested that the frequency and pattern of planning tool use varied across participants. As the game progressed, the number and proportion of self-regulated learning and learning behaviors decreased. Participants were divided into active and passive planning groups based on the number of times they used the planning tool, and their gameplay patterns were visualized. The active planning group showed the learning behaviors more often, but there was no significant difference in the extent to which the two groups improved their knowledge scores. The findings of this study have implications for game design and strategies to promote self-regulated learning in game-based learning.
참고문헌 (47)
- 김건석, "자기조절학습 수준에 따른 교육용 온라인 게임에서의 지식 구성 과정 유형 분석 연구", 한국게임학회 논문지, 6(3), pp.51~66 (2006)
- 백영균, "게임기반학습의 이해와 적용" (2006), 교육과학사
- 신은혜, "지속 가능 발전 교육을 위한 게임 기반 학습의 효과 분석", 에너지기후변화교육, 14(1), pp.85~94 (2024)
- 이인숙, "e-Learning 환경에서의 자기조절학습전략, 자기효능감과 e-Learning학습전략 수준 및 학업성취도 관련성 규명", 교육공학연구, 19(3), pp.41~68 (2003)
- Azevedo, R., "Theoretical foundations of learning environments", pp.171~197 (2012), Routledge
- Bowman, D., "The mathematical foundations of epistemic network analysis", Advances in quantitative ethnography: ICQE 2020 proceedings, pp.91~105 (2021)
- Clark, D. B., "Digital games, design, and learning : A systematic review and meta-analysis", Review of Educational Research, 86(1), pp.79~122 (2016)
- Dever, D. A., "Capturing sequences of learners' self-regulatory interactions with instructional material during game-based learning using auto-recurrence quantification analysis", Frontiers in Psychology, 13, pp.813677~ (2022)
- Ebner, M., "Successful implementation of user-centered game-based learning in higher education : An example from civil engineering", Computers & Education, 49(3), pp.873~890 (2007)
- Fan, Y., "Dissecting learning tactics in MOOC using ordered network analysis", Journal of Computer Assisted Learning, 39(1), pp.154~166 (2022)
- Fiorella, L., "Paper-based aids for learning with a computer-based game", Journal of Educational Psychology, 104(4), pp.1074~1082 (2012)
- Goslen, A., "International conference on artificial intelligence in education", pp.78~89 (2022), Springer International Publishing
- Gupta, A., "Detecting and mitigating encoded bias in deep learning-based stealth assessment models for reflection-enriched game-based learning environments", International Journal of Artificial Intelligence in Education, pp.1~28 (2023)
- Hartley, K., "Educational research in the Internet age : Examining the role of individual characteristics", Educational Researcher, 30(9), pp.22~26 (2001)
- Kim, Y. J., "Language model-based player goal recognition in open world digital games", Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 19(1), pp.75~85 (2023)
- Knowles, M., "The adult learner" (1998), Butterworth-Heinemann
- Lee, J. J., "Gamification in education: What, how, why bother?", Academic Exchange Quarterly, 15(2), pp.146~ (2011)
- Lester, J. C., "International Handbook of Metacognition and Learning Technologies", pp.471~483 (2013)
- Mayer, R. E., "Adding instructional features that promote learning in a game-like environment", Journal of Educational Computing Research, 42(3), pp.241~265 (2010)
- Min, W., "Player goal recognition in open-world digital games with long short-term memory networks", Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pp.2590~2596 (2016)
- Neitfeld, J., "Serious educational game assessment" (2011), Brill
- Nietfeld, J. L., "The impact of goal assignment in a game-based learning environment", Journal of Computer Assisted Learning, 40(2), pp.848~858 (2024)
- Nietfeld, J. L., "Self-regulation and gender within a game-based learning environment", Journal of Educational Psychology, 106(4), pp.961~ (2014)
- O’Neil, H. F., "Classification of learning outcomes : Evidence from the computer games literature", The Curriculum Journal, 16, pp.455~474 (2005)
- Rowe, J. P., "Play in the museum : Design and development of a game-based learning exhibit for informal science education", International Journal of Gaming and Computer-Mediated Simulations, 9(3), pp.96~113 (2017)
- Ruis, A. R., "Finding common ground : A method for measuring recent temporal context in analyses of complex, collaborative thinking", 13th International Conference on Computer-Supported Collaborative Learning, 1, pp.136~143 (2019)
- Sabourin, J. L., "Understanding and predicting student self-regulated learning strategies in game-based learning environments", International Journal of Artificial Intelligence in Education, 23, pp.94~114 (2013)
- Schunk, D. H., "Developing children's self-efficacy and skills : The roles of social comparative information and goal setting", Contemporary educational psychology, 8(1), pp.76~86 (1983)
- Schunk, D. H., "Enhancing self-efficacy and achievement through rewards and goals : Motivational and informational effects", Journal of Educational Research, 78, pp.29~34 (1984)
- Schunk, D. H., "Goal setting and self-efficacy during self-regulated learning", Educational Psychologist, 25(1), pp.71~86 (1990)
- Shute, V. J., "Adaptive technologies for training and education", pp.7~27 (2012), Cambridge University Press
- Shaffer, D. W., "Quantitative ethnography" (2017), Cathcart Press
- Shaffer, D. W., "A tutorial on epistemic network analysis : Analyzing the structure of connections in cognitive, social, and interaction data", Journal of Learning Analytics, 3(3), pp.9~45 (2016)
- Shaffer, D. W., "Learning analytics: Theory and practice" (2017), Springer
- Siebert-Evenstone, A., "In search of conversational grain size : Modelling semantic structure using moving stanza windows", Journal of Learning Analytics, 4(3), pp.123~139 (2017)
- Siemens, G., "Penetrating the fog : Analytics in learning and education", Educause Review, 46(5), pp.30~32 (2011)
- Tan, Y., "Advances in quantitative ethnography: ICQE 2022 (Communications in computer and information science, 1785)", pp.19~42 (2023), Springer
- Taub, M., "Handbook of game-based learning" (2020), MIT Press
- Wang, C. H., "Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning", Distance Education, 34(3), pp.302~323 (2013)
- Weiler, D. T., "Quantifying the qualitative : Exploring epistemic network analysis as a method to study work system interactions", Ergonomics, 65(10), pp.1434~1449 (2022)
- Winne, P. H., "Improving measurements of self-regulated learning", Educational Psychologist, 45(4), pp.267~276 (2010)
- Wooldridge, A. R., "Quantifying the qualitative with epistemic network analysis : A human factors case study of task-allocation communication in a primary care team", IIE Transactions on Healthcare Systems Engineering, 8, pp.72~82 (2018)
- Zimmerman, B. J., "Becoming a self-regulated learner : Which are the key subprocesses?", Contemporary educational psychology, 11(4), pp.307~313 (1986)
- Zimmerman, B. J., "Handbook of self-regulation", pp.13~39 (2000), Academic Press
- Zimmerman, B. J., "Becoming a self-regulated learner : An overview", Theory Into Practice, 41(2), pp.64~70 (2002)
- Zimmerman, B. J., "Development of a structured interview for assessing student use of self-regulated learning strategies", American Educational Research Journal, 23, pp.614~628 (1986)
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