DOI QR코드

DOI QR Code

AI 기반 수학 교수·학습에 대한 체계적 문헌 고찰: AI의 역할과 교사의 역할을 중심으로

Systematic literature review on AI-based mathematics teaching and learning: Focusing on the role of AI and teachers

  • 윤정은 (서울대학교 ) ;
  • 권오남 (서울대학교)
  • Jungeun Yoon (Seoul National University) ;
  • Oh Nam Kwon (Seoul National University)
  • 투고 : 2024.07.08
  • 심사 : 2024.08.06
  • 발행 : 2024.08.31

초록

본 연구는 AI 기반 수학 교수·학습에 대한 문헌을 체계적, 종합적으로 고찰하여 연구 동향을 탐색하고자 수행되었다. 이를 위해 최근 10년 간의 수학교육 문헌 중 문헌선정기준에 부합하는 57개의 문헌을 연구 대상, 연구 방법, 연구 목적, 학습 내용, AI의 유형, AI의 역할, 교사의 역할 측면에서 체계적 문헌 고찰하였다. 연구 결과, 연구 대상 중 학생을 대상으로 한 연구가 51%로 가장 많은 비중을 차지했으며, 연구 방법 중 양적 연구의 비중이 49%로 가장 높았다. 연구 목적은 효과 분석 44%, 이론적 논의 35%, 수업 사례 탐색 21%로 분포했다. 학습 내용으로 '수와 연산'과 '문자와 식'이 가장 많이 다루어졌고, AI 유형 중 지능형 튜터링 시스템(ITS)이 가장 많이 사용되었다. AI의 역할은 학습자 교수의 비중이 40.4%로 가장 높았으며, 교수자 지원 22.8%, 학습자 지원 21%, 시스템 지원 15.8% 순으로 분포하였다. 교사의 역할은 초기 연구일수록 'AI 수용자'로서의 역할이, 최근 연구일수록 'AI와의 건설적 파트너'로서의 역할이 부각되었고, 각 역할이 교육학적, AI-기술적, 내용적 측면에서 탐색되었다. 이를 통해 국내 수학교육 후속 연구의 방향이 제안되었고, AI 기반 수학 교수·학습에서의 교사가 갖추어야 할 소양이 논의되었다.

The purpose of this study is to explore research trends on AI-based mathematics teaching and learning. For this purpose, a systematic literature review was conducted on 57 literatures in terms of research subject, research method, research purpose, learning content, type of AI, role of AI, and role of teachers. The results indicate that student accounted for the largest proportion at 51% among the research subjects, and quantitative research was the highest at 49% among the research methods. The purpose of study was distributed as follows: effect analysis 44%, theoretical discussion 35%, case study 21%. 'Numbers and Operations' and 'Variables and Expressions' covered learning contents most, and Intelligent Tutoring System (ITS) was used the most among the types of AI. 'Student teaching' was the largest parts of role of AI at 40.4%, followed by 'teacher support' at 22.8%, 'student support' at 21%, and 'system support' at 15.8%. The role of teachers as 'AI recipients' was highlighted in earlier studies, and the role of teachers as 'constructive partner with AI' was highlighted in more recent studies. Also, role of teachers was explored in pedagogical, AI-technological, content aspects. Through this, follow-up research was suggested and the roles that teachers should have in AI-based mathematics teaching and learning were discussed.

키워드

참고문헌

  1. Auccahuasi, W., Santiago, G. B., Nunez, E. O., & Sernaque, F. (2018). Interactive online tool as an instrument for learning mathematics through programming techniques, aimed at high school students. Proceedings of the 6th International conference on information technology: IoT and Smart City, 70-76. https://doi.org/10.1145/3301551.3301580
  2. Barana, A., Marchisio, M., & Roman, F. (2023). Fostering Problem Solving and Critical Thinking in Mathematics through Generative Artificial Intelligence. International Association for Development of the Information Society.
  3. Bernacki, M. L., & Walkington, C. (2018). The role of situational interest in personalized learning. Journal of Educational Psychology, 110(6), 864-881.
  4. Borba, M. C. (2021). The future of mathematics education since COVID-19: Humans-with-media or humans-with-nonliving-things. Educational Studies in Mathematics, 108(1), 385-400. https://doi.org/10.1007/s10649-021-10043-2
  5. Bray, A., & Tangney, B. (2017). Technology usage in mathematics education research-A systematic review of recent trends. Computers & Education, 114, 255-273. https://doi.org/10.1016/j.compedu.2017.07.004
  6. Bringula, R. P., Fosgate Jr, I. C. O., Garcia, N. P. R., & Yorobe, J. L. M. (2018). Effects of pedagogical agents on students' mathematics performance: A comparison between two versions. Journal of Educational Computing Research, 56(5), 701-722. https://doi.org/10.1177/0735633117722494
  7. Cabestrero, R., Quiros, P., Santos, O. C., Salmeron-Majadas, S., Uria-Rivas, R., Boticario, J. G., ... & Ferri, F. J. (2018). Some insights into the impact of affective information when delivering feedback to students. Behaviour & Information Technology, 37(12), 1252-1263. https://doi.org/10.1080/0144929X.2018.1499803
  8. Casler-Failing, S. (2021). Learning to teach mathematics with robots: Developing the 'T' in technological pedagogical content knowledge. Research in Learning Technology, 29. https://doi.org/10.25304/rlt.v29.2555
  9. Chang, H., & Nam, J. (2021). The use of Artificial Intelligence in elementary mathematics education-Focusing on the math class support system 'Knock-knock! math expedition'. The Journal of Korea Elementary Education, 31(Supplement), 105-123. http://dx.doi.org/10.20972/Kjee.31.S.202101.S105
  10. Choi, I. (2022). Exploring teaching and learning methods using Artificial Intelligence (AI) in the mathematics classroom: Focusing on the development of middle school statistic scenarios. Journal of the Korean School Mathematics, 25(2), 149-174. https://dx-doi-org.libproxy.snu.ac.kr/10.30807/ksms.2022.25.2.003
  11. Choi, J. (2021). Artificial Intelligence (AI) research trends in mathematics education. The Journal of Curriculum and Instruction Studies, 14(2), 1-14.
  12. Chounta, I. A., Bardone, E., Raudsep, A., & Pedaste, M. (2022). Exploring teachers' perceptions of Artificial Intelligence as a tool to support their practice in Estonian K-12 education. International Journal of Artificial Intelligence in Education, 32(3), 725-755. https://doi.org/10.1007/s40593-021-00243-5
  13. Cook, D. J., Mulrow, C. D., & Haynes, R. B. (1997). Systematic reviews: synthesis of best evidence for clinical decisions. Annals of Internal Medicine, 126(5), 376-380.
  14. Cung, B., Xu, D., Eichhorn, S., & Warschauer, M. (2019). Getting academically underprepared students ready through college developmental education: Does the course delivery format matter?. American Journal of Distance Education, 33(3), 178-194. https://doi.org/10.1080/08923647.2019.1582404
  15. del Olmo-Munoz, J., Gonzalez-Calero, J. A., Diago, P. D., Arnau, D., & Arevalillo-Herraez, M. (2023). Intelligent tutoring systems for word problem solving in COVID-19 days: Could they have been (part of) the solution?. ZDM-Mathematics Education, 55(1), 35-48. https://doi.org/10.1007/s11858-022-01396-w
  16. Ferro, L. S., Sapio, F., Terracina, A., Temperini, M., & Mecella, M. (2021). Gea2: A serious game for technology-enhanced learning in STEM. IEEE Transactions on Learning Technologies, 14(6), 723-739.
  17. Fissore, C., Floris, F., Marchisio, M., & Sacchet, M. (2022). Didactic activities on Artificial Intelligence: the perspective of stem teachers. Proceedings of the 19th international conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2022, pp. 11-18). IADIS press.
  18. Forsstrom, S. E., & Afdal, G. (2020). Learning mathematics through activities with robots. Digital Experiences in Mathematics Education, 6(1), 30-50. https://doi.org/10.1007/s40751-019-00057-0
  19. Forsstrom, S. E., & Kaufmann, O. T. (2018). A literature review exploring the use of programming in mathematics education. International Journal of Learning, Teaching and Educational Research, 17(12), 18-32. https://doi.org/10.26803/ijlter.17.12.2
  20. Gillespie, J., Winn, K., Faber, M., & Hunt, J. (2022). Implementation of a Mathematics Formative Assessment Online Tool Before and During Remote Learning. International Conference on Artificial Intelligence in Education, 168-173. Springer International Publishing. https://doi.org/10.1007/978-3-031-11647-6_29
  21. Gonzalez-Calero, J. A., Arnau, D., Puig, L., & Arevalillo-Herraez, M. (2015). Intensive scaffolding in an intelligent tutoring system for the learning of algebraic word problem solving. British Journal of Educational Technology, 46(6), 1189-1200. https://doi.org/10.1111/bjet.12183
  22. Graesser, A. C. (2016). Conversations with AutoTutor help students learn. International Journal of Artificial Intelligence in Education, 26, 124-132. https://doi.org/10.1007/s40593-015-0086-4
  23. Grawemeyer, B., Mavrikis, M., Holmes, W., Gutierrez-Santos, S., Wiedmann, M., & Rummel, N. (2017). Affective learning: Improving engagement and enhancing learning with affect-aware feedback. User Modeling and User-Adapted Interaction, 27, 119-158. https://doi.org/10.1007/s11257-017-9188-z
  24. Guliherme, A. (2017). AI and Education: The importance of teacher and student relations. AI and Society, 32(1), 1-8. https://doi.org/10.1007/s00146-017-0693-8
  25. Gulz, A., Londos, L., & Haake, M. (2020). Preschoolers' understanding of a teachable agent-based game in early mathematics as reflected in their gaze behaviors-an experimental study. International Journal of Artificial Intelligence in Education, 30, 38-73. https://doi.org/10.1007/s40593-020-00193-4
  26. Hamim, T., Benabbou, F., & Sael, N. (2022). Student profile modeling using boosting algorithms. International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 17(5), 1-13. http://doi.org/10.4018/IJWLTT.20220901.oa4
  27. Han, W., Kim, E., & Lee, S. (2021). Analysis of elementary and middle school teachers' perceptions of the use of AI in instructional design. Journal of Learner-Centered Curriculum and Instruction, 21(24), 859-875. https://doi.org/10.22251/jlcci.2021.21.24.859
  28. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. The Center for Curriculum Redesign.
  29. Hong, S., Kim, H., & Park, Y. (2021). Exploring the potentials of AI integration into K-12 education. Journal of Korean Association for Educational Information and Media, 27(3), 875-898. http://dx.doi.org/10.15833/KAFEIAM.27.3.875
  30. How, M. L., & Hung, W. L. D. (2019). Educing AI-thinking in science, technology, engineering, arts, and mathematics (STEAM) education. Education Sciences, 9(3), 184. https://doi.org/10.3390/educsci9030184
  31. Huang, X., Craig, S. D., Xie, J., Graesser, A., & Hu, X. (2016). Intelligent tutoring systems work as a math gap reducer in 6th grade after-school program. Learning and Individual Differences, 47, 258-265. https://doi.org/10.1016/j.lindif.2016.01.012
  32. Hwang, G. J., & Tu, Y. F. (2021). Roles and research trends of Artificial Intelligence in mathematics education: A bibliometric mapping analysis and systematic review. Mathematics, 9(6), 584. https://doi.org/10.3390/math9060584
  33. Jia, J., Li, S., Miao, Y., & Li, J. (2023). The effects of personalised mathematic instruction supported by an intelligent tutoring system during the COVID-19 epidemic and the post-epidemic era. International Journal of Innovation and Learning, 33(3), 330-343. https://doi.org/10.1504/IJIL.2023.130099
  34. Jia, J., Wang, T., Zhang, Y., & Wang, G. (2024). The comparison of general tips for mathematical problem solving generated by generative AI with those generated by human teachers. Asia Pacific Journal of Education, 44(1), 8-28. https://doi.org/10.1080/02188791.2023.2286920
  35. Kautzmann, T. R., & Jaques, P. A. (2019). Effects of adaptive training on metacognitive knowledge monitoring ability in computer-based learning. Computers & Education, 129, 92-105. https://doi.org/10.1016/j.compedu.2018.10.017
  36. Kim, C., Jeon, Y. (2021). The core concepts of mathematics for AI and an analysis of mathematical contents in the textbook. Journal of the Korean School Mathematics Society, 24(4), 391-405. http://doi.org/10.30807/ksms.2021.24.4.004
  37. Kim, H. K., Park, C., Jeong, S., & Ko, H. (2018). A view on complementary relation of human teacher and AI teacher in future education. Journal of Education & Culture, 24(6), 189-207. https://doi.org/10.24159/joec.2018.24.6.189
  38. Kim, J. (2023). Leading teachers' perspective on teacher-AI collaboration in education. Education and Information Technologies, 1-32. https://doi.org/10.1007/s10639-023-12109-5
  39. Kim, J., Kwon, M., & Pang, J. (2023). Elementary school teachers' perceptions of using Artificial Intelligence in mathematics education. Education of Primary School Mathematics, 26(4), 299-316. https://doi.org/10.7468/jksmec.2023.26.4.299
  40. Kitchenham, B., & Charters, S. M. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report.
  41. Ko, H. K. (2020). A study on development of school mathematics contents for Artificial Intelligence (AI) capability. Journal of the Korean School Mathematics Society, 23(2), 223-237. https://doi.org/10.30807/ksms.2020.23.2.003
  42. Krippendorff, K. (2018). Content analysis: An introduction to its methodology. Sage publications.
  43. Ku, N., & Choi, I. (2022). An analysis of the textbook: Focusing on forecast and optimization. Journal of Educational Research in Mathematics, 32(2), 125-147. http://doi.org/10.29275/jerm.2022.32.2.125
  44. Kwon, O. N., Lee, K., Oh S. J., & Park, J. S. (2021). An analysis of 'Related Learning Elements' reflected in textbooks. Communications of Mathematical Education, 35(4), 445-473. http://doi.org/10.7468/jksmee.2021.35.4.445
  45. Levy, B., Hershkovitz, A., Tabach, M., Cohen, A., Segal, A., & Gal, K. (2023). Personalization in graphically rich e-Learning environments for K-6 Mathematics. IEEE Transactions on Learning Technologies, 16(3), 364-376. https://doi.org/10.1109/TLT.2023.3263520
  46. Lim, M., Kim, H., Nam, J., & Hong, O. (2021). Exploring the application of elementary mathematics supporting system using Artificial Intelligence in teaching and learning. School Mathematics, 23(2), 251-270. https://doi.org/10.29275/sm.2021.06.23.2.251
  47. Lim, W., & Park, M. (2021). AI-based mathematics education: A review of issues in international research. Journal of Learner-Centered Curriculum and Instruction, 21(14), 621-635. https://doi.org/10.22251/jlcci.2021.21.14.621
  48. Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
  49. Lopez-Caudana, E., Ramirez-Montoya, M. S., Martinez-Perez, S., & Rodriguez-Abitia, G. (2020). Using robotics to enhance active learning in mathematics: A multi-scenario study. Mathematics, 8(12), 2163. https://doi.org/10.3390/math8122163
  50. Luckin, R., & Holmes, W. (2016). Intelligence unleashed: An argument for AI in education. UCL Knowledge Lab.
  51. Luzano, J. F. P. (2024). Assessment in mathematics education in the sphere of Artificial Intelligence: A systematic review on its threats and opportunities. Assessment, 8(2), 100-104.
  52. Mengist, W., Soromessa, T., & Legese, G. (2020). Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX, 7, 100777. https://doi.org/10.1016/j.mex.2019.100777
  53. Ministry of Education (2021). Announcing the main points of the 2022 revision curriculum. Ministry of Education, 2021.11.24.
  54. Ministry of Education (2022). Mathematics curriculum. proclamation of the ministry of education # 2022-33 [Annex 8]. Ministry of Education.
  55. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group*, T. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264-269.
  56. Nam, B. H., & Bai, Q. (2023). ChatGPT and its ethical implications for STEM research and higher education: A media discourse analysis. International Journal of STEM Education, 10(1), 66. https://doi.org/10.1186/s40594-023-00452-5
  57. Ning, Y., Zhang, C., Xu, B., Zhou, Y., & Wijaya, T. T. (2024). Teachers' AI-TPACK: Exploring the relationship between knowledge elements. Sustainability, 16(3), 978. https://doi.org/10.3390/su16030978
  58. Nurwahid, M., & Ashar, S. (2024). A literature review: The use of Artificial Intelligence (AI) in mathematics learning. Proceeding International Conference on Religion, Science and Education, 3, 337-344. Retrieved from https://sunankalijaga.org/prosiding/index.php/icrse/article/view/1254
  59. Pai, K. C., Kuo, B. C., Liao, C. H., & Liu, Y. M. (2021). An application of Chinese dialogue-based intelligent tutoring system in remedial instruction for mathematics learning. Educational Psychology, 41(2), 137-152. https://doi.org/10.1080/01443410.2020.1731427
  60. Park, C. J., Hyun, J. S. (2022). Review on teachers' digital competency based on digital technology integration model for 2022 revised curriculum. The Korean Association of Computer Education, 25(1), 17-27. https://doi.org/10.32431/kace.2022.25.1.002
  61. Park, M. (2020). The trends of using Artificial Intelligence in mathematics education. The Journal of Korea elementary education, 31, 91-102. http://dx.doi.org/10.20972/Kjee.31.S.202008.S91
  62. Patel, N., Nagpal, P., Shah, T., Sharma, A., Malvi, S., & Lomas, D. (2023). Improving mathematics assessment readability: Do large language models help?. Journal of Computer Assisted Learning, 39(3), 804-822. https://doi.org/10.1111/jcal.12776
  63. Petticrew, M., & Roberts, H. (2008). Systematic reviews in the social sciences: A practical guide. John Wiley & Sons.
  64. Pham, H., Nong, D., Simshauser, P., Nguyen, G. H., & Duong, K. T. (2024). Artificial intelligence (AI) development in the Vietnam's energy and economic systems: A critical review. Journal of Cleaner Production, 140692. https://doi.org/10.1016/j.jclepro.2024.140692
  65. Phillips, A., Pane, J. F., Reumann-Moore, R., & Shenbanjo, O. (2020). Implementing an adaptive intelligent tutoring system as an instructional supplement. Educational Technology Research and Development, 68(3), 1409-1437. https://doi.org/10.1007/s11423-020-09745-w
  66. Pratikno, P., & Lay, C. (2017). From populism to democratic polity: Problems and challenges in Surakarta, Indonesia. PCD Journal, 3(1-2), 33-62. https://doi.org/10.22146/pcd.25740
  67. Rajendran, R., Iyer, S., & Murthy, S. (2018). Personalized affective feedback to address students' frustration in ITS. IEEE Transactions on Learning Technologies, 12(1), 87-97. https://doi.org/10.1109/TLT.2018.2807447
  68. Reinhold, F., Hoch, S., Werner, B., Richter-Gebert, J., & Reiss, K. (2020). Learning fractions with and without educational technology: What matters for high-achieving and low-achieving students?. Learning and Instruction, 65, 101264. https://doi.org/10.1016/j.learninstruc.2019.101264
  69. Saputra, H., Sumitra, I., Hirawan, D, Lesmana, R., & Soegoto, E. (2023). Smart urban farming application: UV light in hydroponic installations. Journal of Engineering Science and Technology, 18(2), 1007-1018.
  70. Shakya, A., Rus, V., & Venugopal, D. (2023). Scalable and equitable math problem solving strategy prediction in big educational data. arXiv preprint arXiv:2308.03892. https://doi.org/10.48550/arXiv.2308.03892
  71. Shin, D. (2020a). Artificial intelligence in primary and secondary education: A systematic review. Journal of Educational Research in Mathematics, 30(3), 531-552. https://doi.org/10.29275/jerm.2020.08.30.3.531
  72. Shin, D. (2020b). An analysis prospective mathematics teachers' perception on the use of Artificial Intelligence (AI) in mathematics education. Communications of Mathematical Education, 34(3), 215-234. https://doi.org/10.7468/jksmee.2020.34.3.215
  73. Sim, Y., Kim, J., Kwon, M. (2020). Secondary mathematics teachers' perceptions on Artificial Intelligence (AI) for math and math for Artificial Intelligence (AI). Communications of Mathematical Education, 37(2), 159-181. https://doi.org/10.7468/jksmee.2023.37.2.159
  74. Son, T. (2023). Preservice teacher's understanding of the intention to use the artificial intelligence program 'Knock-Knock! Mathematics Expedition' in mathematics lesson: Focusing on self-efficacy, artificial intelligence anxiety, and technology acceptance model. The Mathematics Education, 62(3), 401-416. https://doi.org/10.7468/mathedu.2023.62.3.401
  75. Suharmawan, W. (2023). Pemanfaatan Chat GPT dalam dunia pendidikan. Journal Educational Research and Development, 7(2), 158-166. https://doi.org/10.31537/ej.v7i2.1248
  76. Tejawiani, I., Sucahyo, N., Usanto, U., & Sopian, A. (2023). Peran Artificial Intelligence Terhadap Peningkatan Kreativitas Siswa Dengan Menerapkan Proyek Penguatan Profil Pelajar Pancasila. JMM (Jurnal Masyarakat Mandiri), 7(4), 3578-3592.
  77. Tuomi, I. (2020). Research for CULT Committee-The use of Artificial Intelligence (AI) in education. European Parliament, Directorate-General for Internal Policies, 2-6. Retrieved from https://web.cs.ucdavis.edu/~koehl/Teaching/ECS188/PDF_files/AI_Education_EU.pdf
  78. Urrutia, F., & Araya, R. (2024). Who's the best detective? Large language models vs. traditional machine learning in detecting incoherent fourth grade math answers. Journal of Educational Computing Research, 61(8), 187-218. https://doi.org/10.1177/07356331231191174
  79. Vuorikari Rina, R., Kluzer, S., & Punie, Y. (2022). DigComp 2.2: The digital competence framework for citizens-with new examples of knowledge, skills and attitudes (No. JRC128415). Joint Research Centre (Seville site).
  80. Wardat, Y., Tashtoush, M. A., AlAli, R., & Jarrah, A. M. (2023). ChatGPT: A revolutionary tool for teaching and learning mathematics. Eurasia Journal of Mathematics, Science and Technology Education, 19(7), em2286. https://doi.org/10.29333/ejmste/13272
  81. Wu, H. M., Kuo, B. C., & Wang, S. C. (2017). Computerized dynamic adaptive tests with immediately individualized feedback for primary school mathematics learning. Journal of Educational Technology & Society, 20(1), 61-72.
  82. Wu, T. T., Lee, H. Y., Wang, W. S., Lin, C. J., & Huang, Y. M. (2023). Leveraging computer vision for adaptive learning in STEM education: Effect of engagement and self-efficacy. International Journal of Educational Technology in Higher Education, 20(1), 53. https://doi.org/10.1186/s41239-023-00422-5
  83. Yoon, J., Park, S., & Kwon, O. N. (2023). ChatGPT-flipped mathematics class case study: Focused on learners' engagement. Journal of Educational Technology, 39(4), 1011-1047. http://dx.doi.org/10.17232/KSET.39.4.1011
  84. Zafrullah, Z., Hakim, M. L., & Angga, M. (2023). ChatGPT open AI: Analysis of mathematics education students learning interest. Journal of Technology Global, 1(01), 1-10.
  85. Zawacki-Richter, O., Marin, V. I., Bond, M., & Gouverneur, F. (2019). 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), 1-27. https://doi.org/10.1186/s41239-019-0171-0
  86. Zhang, Y., Li, Y., Cui, L., Cai, D., Liu, L., Fu, T., ... & Shi, S. (2023). Siren's song in the AI ocean: A survey on hallucination in large language models. arXiv preprint arXiv:2309.01219. https://doi.org/10.48550/arXiv.2309.01219