Educational Technology International

The Korean Society for Education Technology (한국교육공학회)
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The Meaning of Personalized Learning Structures in AI-based Educational Platforms: From the Perspective of Learned Curriculum

  • Soojin KIM (Elementary Education Research Institute, Korea National University of Education)
  • Received : 2024.08.31
  • Accepted : 2024.10.21
  • Published : 2024.10.30
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Abstract

The recent advancements of AI-based educational platforms are opening up a new era for personalized learning as an alternative for future education. This study explores the structures of personalized learning in the current AI-based educational platforms to interpret their meaning from the perspective of Learned Curriculum. For this, three leading AI-based educational platforms, Classting (Korea), Squirrel AI Learning (China), and Khan Academy (USA) were described with a focus on the personalized contents, methods, and pace to meet students' needs. The results are as follows: First, the personalized contents offered by the platforms are the sequenced contents within the total content structure that students are required to learn; Second, student choice for learning methods is partially being provided within the platforms; Lastly, personalized learning provided by the platforms ultimately means the personalization of pacing based on assessment results. Consequently, the discourse surrounding personalized learning provided by AI-based educational platforms needs to expand beyond personalization within the predetermined content areas to encompass curriculum-level openness. Moreover, the "students' needs" used for diagnosis for personalization should include not only the assessment results of Given Curriculum contents, but also the students' personal interests or goals as guiding objectives for each student's Learned Curriculum.

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References

  1. Aoki, T. (1993). Legitimating lived curriculum: Towards a curricular landscape of multiplicity. Journal of Curriculum and Supervision, 8(3), 255-268
  2. Babbie, E. (2001). The practice of social research (9th ed.). Wadsworth/Thomson Learning.
  3. Baker, R. (2021). Artificial intelligence in education: Bringing it all together. In OECD Digital Education Outlook 2021: Pushing the frontiers with AI, blockchain, and robots (pp. 43-54), OECD.
  4. Bingham, A., Pane, J., Steiner, E., & Hamilton, L. (2018). Ahead of the curve: Implementation challenges in personalized learning school models. Educational Policy, 32(3), 454-489.
  5. Bloomberg Television. (2019, Jul 12). How Squirrel AI Learning Is Shaking Up Education in China [Video] YouTube. https://youtu.be/eHab0NvT8FQ?si=37DK3bxE28rEkEeq
  6. Bray, B., & McClaskey, K. (2013). A step-by-step guide to personalized learning. International society for technology in education.
  7. Bulger, M. (2016) Personalized learning: The conversations we're not having. Data & Society, 22, 1-29.
  8. Cho, J., & Jeong, K. (2019). The change of meaning the concepts related to school education in personalized learning. Journal of Curriculum Integration, 13(4), 125-146.
  9. Classting. (2024. January 13). AI Gaebyeol Matchum Hakseub [AI personalized learning]. https://www.classting.com/features/personalized-learning
  10. Cuban, L. (1992). Curriculum stability and change. In P. Jackson (Ed.), Handbook of research on curriculum (pp. 216-247). Macmillan.
  11. Dishon, G. (2017). New data, old tensions: Big data, personalized learning, and the challenges of progressive education. Theory and Research in Education, 15(3), 272-289.
  12. Doyle, W. (1992). Curriculum and pedagogy. In P. W. Jackson (Ed.), Handbook of research on curriculum (pp. 66-87). MacMillan.
  13. Erickson, F., Bagrodia, R., Cook-Sather, A., Espinoza, M., Jurow, S., Shultz, J., & Spencer, J. (2008). Students' experience of school curriculum: The everyday circumstances of granting and withholding assent to learn. In M. F. Connelly, M. F. He, & J. Phillion (Eds.), The SAGE Handbook of Curriculum and Instruction (pp.198-218). SAGE Publications.
  14. Erickson, F., & Shultz, J. (1992). Students' experience of the curriculum. In P. Jackson (Ed.), Handbook of research on curriculum (pp. 465-485). Macmillan.
  15. Glatthorn, A. (1999) Curriculum alignment revisited. Journal of Curriculum and Supervision, 15(1), 26-34.
  16. Han, O. (2023). A study on components for designing personalized education system based on generative AI. Journal of Computer Education, 26(6), 127-141.
  17. Jackson, P. (1968). Life in classrooms. Holt, Rinehart, & Winston.
  18. Jacobs, J. (2017). Pacesetter in personalized Learning: summit Charter network shares its model nationwide. Education Next, 17(4), 17-24.
  19. Jang, J, & Shin, S. (2023). Analysis of Research Trends on Intelligent Tutoring Systems for Supporting Personalized Learning Using LDA Topic Modeling. The Journal of Educational Information and Media, 29(4), 1095-1122.
  20. Kang, I., Jin, S., & Bae, H. (2016). Defining the characteristics of LMS for Smart Learning drawn from the analysis of the current cases of LMS. The Journal of Educational Information and Media, 22(2), 195-222.
  21. Kem, D. (2022). Personalised and adaptive learning: Emerging learning platforms in the era of digital and smart learning. International Journal of Social Science and Human Research, 5(2), 385-391.
  22. Kim, S. Y. (2018). A concept and characteristics of personalized learning: From cases of innovative schools in the U.S. The Journal of Curriculum Studies, 36(3), 49-70.
  23. Kim, S. Y., & Cho, M. (2023). AI-based educational platform analysis supporting personalized mathematics learning. Communications of Mathematical Education, 36(3), 417-438.
  24. Kim, S. J., Lee, C., & Jeong, K. (2022). Possibilities of learned curriculum research through student voice research. The Journal of Curriculum Studies, 40(1), 185-209.
  25. Lee, K., Kwon, J., & Oh, S. (2008). A study on support strategies for Personalized Learning in classroom. Korea Institute for Curriculum and Evaluation.
  26. Lim, K., Lim, J., & Jin, M. (2021). A systematic literature review of technology-based personalized learning: Research from 2011 to 2020 in Korea. Journal of Educational Technology, 37(3), 525-559.
  27. Lokey-Vega, A., & Stephens, S. (2019). A batch of one: A conceptual framework for the personalized learning movement. Journal of Online Learning Research, 5(3), 311-330.
  28. Maghsudi, S., Lan, A.S., Xu, J., & van der Schaar, M. (2021). Personalized Education in the Artificial Intelligence Era: What to Expect Next. IEEE Signal Processing Magazine, 38, 37-50.
  29. Martinez, M. (2001). Key design considerations for personalized learning on the web. Educational Technology & Society, 4(1), 26-40.
  30. MIT Technology review. (2019, August 2). China has started a grand experiment in AI education. https://www.technologyreview.com/2019/08/02/131198/china-squirrel-has-started-a-grand-experiment-in-ai-education-it-could-reshape-how-the/
  31. Ministry of Education. (2022). General curriculum of elementary and middle school. Ministry of Education, Notice No. 2022-33.
  32. Patrick, S., Kennedy, K., & Powell, A. (2013). Mean what you say: Defining and integrating personalized, blended, and competency education. iNACOL.
  33. Peng, H., Ma, S., & Spector, J. (2019). Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6(9), 1-14.
  34. Rad, P., Roopaei, M., Beebe, N.L., Shadaram, M., & Au, Y. (2018). AI thinking for cloud educational platform with personalized learning. Proceedings of the Hawaii International Conference on System Sciences, 51, 3-12.
  35. Schubert, W. (2008). Curriculum inquiry. In F. M. Connelly, M. F. He, & J. Phillion, (Eds.), Handbook of curriculum and instruction (pp. 399-419). Sage Publications.
  36. Shaw, C., Larson, R., & Sibdari, S. (2014). An asynchronous, personalized learning platform: Guided learning pathways (GLP). Creative Education, 5(13), 1189-204.
  37. Shemshack, A., Kinshuk, & Spector, J. (2020). A comprehensive analysis of personalized learning components. Journal of Computer Education, 8(4), 485-503.
  38. Shemshack, A., & Spector, J. (2020). A systematic literature review of personalized learning terms. Smart Learning Environments, 7(33), 1-20.
  39. Snyder, J., Bolin, F., & Zumwalt, K. (1992). Curriculum implementation. In W. P. Jakson (Ed.), Handbook of research on curriculum (pp. 402-435), New York Macmillan.
  40. Squirrel AI Learning by Yixue Group. (2019, September 1). Introductory to Squirrel AI Learning. [Video] YouTube. https://youtu.be/tmxKBsBL_6M?si=-i-4Dn8jzSxTQPi7
  41. Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial Intelligence in education: AIEd for personalised learning pathways. The Electronic Journal of e-Learning, 20(5), 639-653.
  42. TED. (2023, May 2). How AI Could Save (Not Destroy) Education. [Video] YouTube. https://youtu.be/hJP5GqnTrNo?si=aybqjXWiR_XnU09c
  43. Watson W. R. & Watson, S. L. (2016). Principles for personalized instruction. In Instructional-Design Theories and Models, Volume IV (pp. 109-136). Routledge.
  44. Yu, H., Miao, C., Leung, C., & white, T. (2017). Towards AI-powered personalization in MOOC learning. Science of Learning, 2(15), 1-5.
  45. Yuyun, I., Suherdi, D. (2023). Components and strategies for personalized learning in higher education: A systematic review. Proceedings of the 20th Asia TEFL-68th TEFLIN-5th iNELTAL Conference, 271-290.
  46. Zais, R. (1981). Conceptions of curriculum and the curriculum field. In H. A. Giroux, A. N. Penna, & W. F. Pinar (Eds.), Curriculum and instruction alternatives in education (pp.31-49). McCutchan Publishing Corporation.
  47. Zawacki-Richter, O., Marin, V., 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.
  48. Zmuda, A., Curtis, G., & Ullman, D. (2015). Learning personalized: The evolution of the contemporary classroom. Jossey-Bass.