Investigating the personalization of learning of 7–12-year-old students based on artificial intelligence
Subject Areas : curriculum
Roya Davoodi Shandiz
1
,
Maoumeh Al Sadat Abtahi
2
,
حمیدرضا مقامی
3
,
Mahdi Ashouri
4
1 - Department of Educational Sciences, Faculty of Islamic Education and Training, Islamic Azad University, Science and Research Branch, Tehran, Iran
2 -
3 - علامه طباطبایی
4 - Assistant Professor, Department of Educational Sciences, Faculty of Islamic Education, Research Sciences Unit, Islamic Azad University, Tehran, Iran
Keywords: Personalized learning, artificial intelligence, student learning, educational technology, educational data analysis,
Abstract :
Abstract
This study examines the personalization of learning for students aged 7 to 12 based on artificial intelligence. Given the individual differences in abilities, learning styles, and interests of students, traditional teaching approaches are unable to meet the needs of all learners. In this context, artificial intelligence serves as an innovative tool, providing unique capabilities for analyzing educational data and delivering personalized learning experiences. The present research employs a mixed-methods approach, including a literature review, analysis of empirical data, and semi-structured interviews with teachers and education specialists. Quantitative data were collected through standardized questionnaires and analyzed using statistical methods. The results indicate that the implementation of AI-based systems in educational environments can significantly improve academic outcomes, increase motivation, and optimize learning experiences. These technologies can identify learners' needs, strengths, and weaknesses through precise data analysis and provide tailored educational content. However, the use of artificial intelligence in education faces challenges such as data privacy concerns, the need for appropriate technological infrastructure, and teacher training. These challenges must be considered alongside the potential benefits of these technologies to effectively and ethically enhance learning. This study emphasizes the importance of integrating artificial intelligence into the educational process and offers recommendations for educational policymakers and school administrators. To achieve effective personalized learning, it is essential to establish suitable infrastructures and provide necessary training for teachers. Given the growing trends in technology, this research can serve as a scientific basis for future studies in the field of AI-based personalized learning.
1. Edwards, L., Smith, J., & Brown, R. (2021). The impact of age on personalized learning outcomes in educational settings. Journal of Educational Psychology, 113(2), 301-315. https://doi.org/10.1037/edu0000425
2. Ming, H., Li, X., & Wang, Y. (2022). Gender differences in personalized learning: A meta-analysis. Educational Research Review, 17, 100-112. https://doi.org/10.1016/j.edurev.2022.100112
3. Zuo, X., Zhang, Y., & Zhao, J. (2023). The role of artificial intelligence in enhancing student engagement in personalized learning. Computers & Education, 200, 104-118. https://doi.org/10.1016/j.compedu.2022.104118
4. Samiri, Z., Mohammadi, M., & Rezaei, M. (2022). Challenges of implementing personalized learning in the classroom: Insights from teachers. Teaching and Teacher Education, 105, 100-115. https://doi.org/10.1016/j.tate.2022.103412
5. Kurtz, J., Roberts, T., & Lee, S. (2021). The influence of parental support on children's learning outcomes in technology-rich environments. Journal of Family Studies, 27(3), 240-256. https://doi.org/10.1080/13229400.2020.1861278
6. Lam, R., Yuen, A., & Ng, M. (2023). Enhancing learning through intelligent tutoring systems: A global perspective. Educational Technology & Society, 26(1), 1-15. https://www.jstor.org/stable/26977288
7. Johnson, D. W., & Johnson, R. T. (2021). Cooperative learning in the classroom: A meta-analytic review of effects on student achievement. Educational Psychology Review, 33(2), 225-252. https://doi.org/10.1007/s10648-020-09543-0
8. Kwan, A. C., & Wong, K. K. (2022). An analysis of adaptive learning technologies in primary education: Implications for practice. Journal of Computer Assisted Learning, 38(4), 991-1005. https://doi.org/10.1111/jcal.12667
9. Moore, M. G. (2022). Theory and practice of distance education: Insights for personalized learning. Distance Education, 43(2), 177-190. https://doi.org/10.1080/01587919.2021.1898953
10. Pahl, C., & Rowsell, J. (2020). Literacy and learning in the digital age: New insights into personalized learning. Journal of Literacy Research, 52(3), 260-282. https://doi.org/10.1177/1086296X20952906
11. Picciano, A. G. (2021). The role of artificial intelligence in education: Current trends and future directions. Journal of Online Learning Research, 7(2), 121-138. https://www.learntechlib.org/p/219507/
12. Rakes, G. C., & Dunn, K. E. (2021). The relationship between technology integration and student learning outcomes: A meta-analysis. Computers in Human Behavior, 118, 106-123. https://doi.org/10.1016/j.chb.2021.106012
13. Rojas, M. L., & Rodriguez, D. (2020). Gamification and personalized learning: A systematic review of recent studies. Journal of Educational Computing Research, 58(5), 1121-1143. https://doi.org/10.1177/0735633117743123
14. Sharma, P., & Saha, S. (2022). The impact of online learning platforms on student engagement and academic performance. International Journal of Educational Technology in Higher Education, 19(1), 20-34. https://doi.org/10.1186/s41239-022-00303-8
15. Suh, A., & Lee, S. (2021). A study on the effectiveness of personalized learning environments for high school students. Computers & Education, 162, 104-120. https://doi.org/10.1016/j.compedu.2020.104120
16. Wang, F., & Hannafin, M. J. (2020). Design-based research and educational technology: A review of the literature. Educational Technology Research and Development, 68(1), 205-228. https://doi.org/10.1007/s11423-019-09738-y
17. West, D. C., & Lewis, L. (2022). The effects of AI-assisted learning systems on student achievement: A meta-analysis. Educational Technology Research and Development, 70(4), 1047-1070. https://doi.org/10.1007/s11423-022-10035-5
18. Xu, Y., & Chen, N. S. (2021). Personalized learning using artificial intelligence: Insights from recent studies. Computers in Human Behavior, 115, 106-116. https://doi.org/10.1016/j.chb.2020.106171
19. Yang, Y. (2023). Exploring the relationship between self-regulated learning and personalized learning in the digital age. Interactive Learning Environments, 31(3), 579-596. https://doi.org/10.1080/10494820.2021.1910871
20. Zhang, D., & Zhou, G. (2020). The impact of artificial intelligence on educational practice: A systematic review. Journal of Educational Technology Systems, 48(3), 371-389. https://doi.org/10.1177/0047239520909487