Expanding Elementary Geography Education through AI Thinking - Integration of Play-Based Inquiry and Problem Solving -

doi:10.17279/jkagee.2025.33.4.1

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2025 Vol.33, Issue 4 Next Page

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Expanding Elementary Geography Education through AI Thinking - Integration of Play-Based Inquiry and Problem Solving - AI 사고를 통한 초등 지리교육의 확장 - 놀이형 탐구와 문제 해결의 융합 -: 박지수
Jisu Park; 부산교육대학교 사회교육과 조교수

Assistant Professor, Department of Social Studies Education, Busan National University of Education

30 November 2025. pp. 1~16

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Abstract

This study aimed to explore the educational potential of applying AI thinking to elementary geography education in order to expand data-driven inquiry and practical problem-solving competencies. To this end, a Geo-AI PBL model that integrates play-based inquiry with problem solving was designed, and its effectiveness was examined. Two cycles of design-based research (DBR) were conducted with two fifth-grade classes in Busan, and data were collected through AI response logs, pre- and post-tests (geographical thinking, AI thinking self-efficacy, ethical sensitivity), and interviews. The model was theoretically grounded in CRISP–DM and elements of geographical thinking, aligning the four derived stages of AI thinking with play-based activities to establish the instructional structure of the Geo-AI PBL. The findings indicate that the treatment group showed significant improvements in predictive thinking, multiscalar spatial reasoning, and ethical reflection compared to the comparison group. The simplification tendencies observed in AI outputs during the first cycle were markedly mitigated in the second cycle following the implementation of the prompt reflection and scale-switching strategies. Students connected satellite imagery and local datasets with AI-generated predictions to propose feasible solutions that accounted for cost, equity, and environmental considerations, while also demonstrating reflection on technological dependence and data uncertainty. Based on these results, the study develops an AI–geographical thinking concordance rubric, a codebook for diagnosing simplification and expansion in AI responses, and a mapping of play mechanics to AI functions, thereby offering design principles for shifting elementary geography education from transmission-based instruction toward data-driven praxis.

Keywords

AI thinking

play-based inquiry

problem solving

Geo-AI PBL

elementary geography education

본 연구에서는 AI 사고를 초등 지리교육에 적용하여 데이터 기반 탐구와 실천적 문제 해결 역량을 확장하는 교육적 가능성을 탐색하고자 하였다. 이를 위해 놀이형 탐구와 문제 해결을 통합한 Geo-AI PBL 모형을 설계하고, 그 효과를 검증하였다. 부산광역시 소재 초등학교 5학년 2개 학급을 대상으로 두 차례의 설계기반연구(DBR)를 수행하였으며, AI 응답 로그, 사전·사후 검사(지리적 사고, AI 사고 자기효능감, 윤리 민감도), 면담 자료를 수집·분석하였다. 모형 설계에서는 CRISP–DM과 지리적 사고 요소를 바탕으로 도출한 AI 사고의 네 단계를 놀이 활동과 정합되게 구성하여 Geo-AI PBL의 수업 구조를 마련하였다. 분석 결과, 실험집단은 비교집단 대비 예측적 사고, 다층적 공간 사고, 윤리적 성찰에서 유의미한 향상을 보였다. 1차 주기에서 두드러졌던 AI 출력의 단순화 경향은 2차 주기에서 프롬프트 리플렉션과 스케일 스위치 전략을 도입한 이후 뚜렷하게 완화되었다. 학생들은 위성영상과 지역 자료를 AI 예측과 결합하여 비용·형평·환경을 고려한 실행 가능한 대안을 도출하였으며, 기술 의존의 한계와 데이터 불확실성에 대한 성찰도 나타냈다. 또한 AI 응답의 단순화·확장 양상을 분석하는 코드 체계와 AI 사고–지리적 사고 정합 루브릭을 개발함으로써, 초등 지리교육을 지식 전달 중심에서 데이터 기반 실천으로 전환할 수 있는 설계적 근거를 제공한다.

키워드

AI 사고

놀이형 탐구

문제 해결

Geo-AI PBL

초등 지리교육

References

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곽소아·김서진·양정현·이현주·장윤재, 2022, 놀이로 배우는 인공지능, 제이펍.
서지영, 2025, “수업 관련 AI 활용 허용 수준에 대한 대학생 인식 분석: 문헌정보학과 학생을 중심으로”, 한국비블리아학회지, 36(1), 87-108.
윤옥경·유수진, 2023, “2022 개정 교육과정 초등 지리 영역 개발과 주요 특징”, 한국지리환경교육학회지, 31(1), 15-27.
이종원, 2024, “AI는 지리 교수학습을 어떻게 바꿔놓을 것인가?: 지리탐구를 중심으로”, 한국지리환경교육학회지, 32(1), 95-112.
장의선, 2019, “지리교육의 5대 빅아이디어를 적용한 초등 사회과 지리 영역의 내용 체계 개발”, 대한지리학회지, 54(2), 251-269.
조성욱, 2005, “지리교육에서 지역규모 인식”, 한국지리환경교육학회지, 13(1), 139-149.10.1017/S106279870500013X
조윤진, 2021, “초등 사회과 지리 영역에서의 인공지능 활용 교육의 가능성: 한성 백제의 역사경관을 중심으로”, 한국초등교육, 32(2), 189-206.
조윤진·한동균, 2022, “초등 사회과 지역화 학습을 위한 AI 챗봇 개발 및 적용 가능성 모색”, 한국초등교육, 33(4), 1-18.
한동균, 2025, “체화된 인공지능의 지리교육적 활용 가능성 탐색”, 사회과수업연구, 13(2), 59-81.10.34261/jssls.2025.13.2.59
Barrows, H. S. and Kelson, A. C., 1995, Problem-based learning in secondary education and the problem-based learning institute, Springfield, IL: Problem-Based Learning Institute, 1(1), 1-5.
Bergen, D., 2009, Play as the learning medium for future scientists, mathematicians, and engineers, American Journal of Play, 1(4), 413-428.
Braun, V. and Clarke, V., 2006, Using thematic analysis in psychology, Qualitative Research in Psychology, 3(2), 77-101.10.1191/1478088706qp063oa
Brown, A. L., 1992, Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings, Journal of the Learning Sciences, 2(2), 141-178.10.1207/s15327809jls0202_2
Bridgman, P. W., 1927, The logic of modern physics, Macmillan.
Caillois, R., 2001, Man, play and games, University of Illinois Press.
Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., and Wirth, R., 2000, CRISP-DM 1.0: Step-by-step data mining guide, NCR Systems Engineering, DaimlerChrysler, SPSS.
Cohen, L., Manion, L., and Morrison, K., 2002, Research Methods in Education, Routledge. 10.4324/9780203224342
Gersmehl, P., 2014, Teaching Geography, Guilford Press.
Goodchild, M. F., 2009, Challenges in spatial analysis, The SAGE handbook of spatial analysis, 465-480.10.4135/9780857020130.n24
Hmelo-Silver, C. E., 2004, Problem-based learning: What and how do students learn?, Educational Psychology Review, 16(3), 235-266.10.1023/B:EDPR.0000034022.16470.f3
Johnson, R. B. and Onwuegbuzie, A. J., 2004, Mixed methods research: A research paradigm whose time has come, Educational Researcher, 33(7), 14-26.10.3102/0013189X033007014
Long, D. and Magerko, B., 2020, What is AI literacy? Competencies and design considerations, Proceedings of the CHI ’20 Conference on Human Factors in Computing Systems, ACM. 10.1145/3313831.3376727
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., and Kasneci, G., 2023, ChatGPT for good? On opportunities and challenges of large language models for education, Computers and Education: Artificial Intelligence, 4, 100114.10.35542/osf.io/5er8f
Miles, M. B. and Huberman, A. M., 1994, Qualitative Data Analysis: An Expanded Sourcebook (2nd ed.), Sage, Thousand Oaks.
Mwinsa, G. M. and Dagada, M., 2025, Play-based learning: A pedagogical approach for social skills development in ECE learners in Zambia, Social Sciences & Humanities Open, 11, 101396.10.1016/j.ssaho.2025.101396
National Research Council, 2006, Learning to Think Spatially: GIS as a Support System in the K–12 Curriculum, National Academies Press.
Newman-Griffis, D., 2025, AI Thinking: a framework for rethinking artificial intelligence in practice, Royal Society Open Science, 12(1), 241482.10.1098/rsos.24148239780964PMC11706651
Niu, T., Li, Z., Huang, M., and Yuan, L., 2023, The application of virtual reality technology in geography teaching. In Proceedings of the 2nd International Conference on Education, Language and Art (ICELA 2022) (Vol. 730, p. 12). Springer Nature.10.2991/978-2-38476-004-6_3
Roelofsen, M. and Carter‐White, R., 2022, Virtual reality as a spatial prompt in geography learning and teaching, Geographical Research, 60(4), 625-636.10.1111/1745-5871.12551
Sedlák, M., Šašinka, Č., Stachoň, Z., Chmelík, J., and Doležal, M., 2022, Collaborative and individual learning of geography in immersive virtual reality: An effectiveness study, Plos one, 17(10), e0276267.10.1371/journal.pone.027626736256672PMC9578614
Smilansky, S., 1968, The effects of sociodramatic play on disadvantaged preschool children. Wiley.
Vygotsky, L. S., 1967, Play and its role in the mental development of the child, Soviet psychology, 5(3), 6-18.10.2753/RPO1061-040505036
Wing, J. M., 2006, Computational thinking, Communications of the ACM, 49(3), 33-35.10.1145/1118178.1118215
Wing, J. M., 2017, Computational thinking’s influence on research and education for all, Italian Journal of Educational Technology, 25(2), 7-14.
Zosh, J. M., Hirsh-Pasek, K., Hopkins, E., Jensen, H., Liu, C., Neale, D., Solis, S. L., and Whitebread, D., 2017, Learning through Play: A Review of the Evidence, LEGO Foundation.
부산광역시교육청, 2023, “AI 디지털교과서 도입지원 플랫폼 운영 안내”, 부산광역시교육청 보도자료.

Information

Publisher :The Korean Association Of Geographic And Environmental Education
Publisher(Ko) :한국지리환경교육학회
Journal Title :The Journal of The Korean Association of Geographic and Environmental Education
Journal Title(Ko) :한국지리환경교육학회지
Volume : 33
No :4
Pages :1~16
DOI :https://doi.org/10.17279/jkagee.2025.33.4.1

[1] 교육부, 2015, 사회과교육과정 (별책7: 교육부 고시 제2015-74호).

[2] 교육부, 2021, 2022 개정 사회교과군 교육과정 재구조화 연구 공청회 자료집.

[3] 곽소아·김서진·양정현·이현주·장윤재, 2022, 놀이로 배우는 인공지능, 제이펍.

[4] 서지영, 2025, “수업 관련 AI 활용 허용 수준에 대한 대학생 인식 분석: 문헌정보학과 학생을 중심으로”, 한국비블리아학회지, 36(1), 87-108.

[5] 윤옥경·유수진, 2023, “2022 개정 교육과정 초등 지리 영역 개발과 주요 특징”, 한국지리환경교육학회지, 31(1), 15-27.

[6] 이종원, 2024, “AI는 지리 교수학습을 어떻게 바꿔놓을 것인가?: 지리탐구를 중심으로”, 한국지리환경교육학회지, 32(1), 95-112.

[7] 장의선, 2019, “지리교육의 5대 빅아이디어를 적용한 초등 사회과 지리 영역의 내용 체계 개발”, 대한지리학회지, 54(2), 251-269.

[8] 조성욱, 2005, “지리교육에서 지역규모 인식”, 한국지리환경교육학회지, 13(1), 139-149.10.1017/S106279870500013X

[9] 조윤진, 2021, “초등 사회과 지리 영역에서의 인공지능 활용 교육의 가능성: 한성 백제의 역사경관을 중심으로”, 한국초등교육, 32(2), 189-206.

[10] 조윤진·한동균, 2022, “초등 사회과 지역화 학습을 위한 AI 챗봇 개발 및 적용 가능성 모색”, 한국초등교육, 33(4), 1-18.

[11] 한동균, 2025, “체화된 인공지능의 지리교육적 활용 가능성 탐색”, 사회과수업연구, 13(2), 59-81.10.34261/jssls.2025.13.2.59

[12] Barrows, H. S. and Kelson, A. C., 1995, Problem-based learning in secondary education and the problem-based learning institute, Springfield, IL: Problem-Based Learning Institute, 1(1), 1-5.

[13] Bergen, D., 2009, Play as the learning medium for future scientists, mathematicians, and engineers, American Journal of Play, 1(4), 413-428.

[14] Braun, V. and Clarke, V., 2006, Using thematic analysis in psychology, Qualitative Research in Psychology, 3(2), 77-101.10.1191/1478088706qp063oa

[15] Brown, A. L., 1992, Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings, Journal of the Learning Sciences, 2(2), 141-178.10.1207/s15327809jls0202_2

[16] Bridgman, P. W., 1927, The logic of modern physics, Macmillan.

[17] Caillois, R., 2001, Man, play and games, University of Illinois Press.

[18] Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., and Wirth, R., 2000, CRISP-DM 1.0: Step-by-step data mining guide, NCR Systems Engineering, DaimlerChrysler, SPSS.

[19] Cohen, L., Manion, L., and Morrison, K., 2002, Research Methods in Education, Routledge. 10.4324/9780203224342

[20] Gersmehl, P., 2014, Teaching Geography, Guilford Press.

[21] Goodchild, M. F., 2009, Challenges in spatial analysis, The SAGE handbook of spatial analysis, 465-480.10.4135/9780857020130.n24

[22] Hmelo-Silver, C. E., 2004, Problem-based learning: What and how do students learn?, Educational Psychology Review, 16(3), 235-266.10.1023/B:EDPR.0000034022.16470.f3

[23] Johnson, R. B. and Onwuegbuzie, A. J., 2004, Mixed methods research: A research paradigm whose time has come, Educational Researcher, 33(7), 14-26.10.3102/0013189X033007014

[24] Long, D. and Magerko, B., 2020, What is AI literacy? Competencies and design considerations, Proceedings of the CHI ’20 Conference on Human Factors in Computing Systems, ACM. 10.1145/3313831.3376727

[25] Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., and Kasneci, G., 2023, ChatGPT for good? On opportunities and challenges of large language models for education, Computers and Education: Artificial Intelligence, 4, 100114.10.35542/osf.io/5er8f

[26] Miles, M. B. and Huberman, A. M., 1994, Qualitative Data Analysis: An Expanded Sourcebook (2nd ed.), Sage, Thousand Oaks.

[27] Mwinsa, G. M. and Dagada, M., 2025, Play-based learning: A pedagogical approach for social skills development in ECE learners in Zambia, Social Sciences & Humanities Open, 11, 101396.10.1016/j.ssaho.2025.101396

[28] National Research Council, 2006, Learning to Think Spatially: GIS as a Support System in the K–12 Curriculum, National Academies Press.

[29] Newman-Griffis, D., 2025, AI Thinking: a framework for rethinking artificial intelligence in practice, Royal Society Open Science, 12(1), 241482.10.1098/rsos.24148239780964PMC11706651

[30] Niu, T., Li, Z., Huang, M., and Yuan, L., 2023, The application of virtual reality technology in geography teaching. In Proceedings of the 2nd International Conference on Education, Language and Art (ICELA 2022) (Vol. 730, p. 12). Springer Nature.10.2991/978-2-38476-004-6_3

[31] Roelofsen, M. and Carter‐White, R., 2022, Virtual reality as a spatial prompt in geography learning and teaching, Geographical Research, 60(4), 625-636.10.1111/1745-5871.12551

[32] Sedlák, M., Šašinka, Č., Stachoň, Z., Chmelík, J., and Doležal, M., 2022, Collaborative and individual learning of geography in immersive virtual reality: An effectiveness study, Plos one, 17(10), e0276267.10.1371/journal.pone.027626736256672PMC9578614

[33] Smilansky, S., 1968, The effects of sociodramatic play on disadvantaged preschool children. Wiley.

[34] Vygotsky, L. S., 1967, Play and its role in the mental development of the child, Soviet psychology, 5(3), 6-18.10.2753/RPO1061-040505036

[35] Wing, J. M., 2006, Computational thinking, Communications of the ACM, 49(3), 33-35.10.1145/1118178.1118215

[36] Wing, J. M., 2017, Computational thinking’s influence on research and education for all, Italian Journal of Educational Technology, 25(2), 7-14.

[37] Zosh, J. M., Hirsh-Pasek, K., Hopkins, E., Jensen, H., Liu, C., Neale, D., Solis, S. L., and Whitebread, D., 2017, Learning through Play: A Review of the Evidence, LEGO Foundation.

[38] 부산광역시교육청, 2023, “AI 디지털교과서 도입지원 플랫폼 운영 안내”, 부산광역시교육청 보도자료.

The Journal of The Korean Association of Geographic and Environmental Education ISSN:1226-511X(Print) 2586-5641(Online) 한국지리환경교육학회지

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