A Systematic Literature Review of Data Privacy in AI-Driven Educational Platforms

Artificial Intelligence (AI) driven educational platforms are transforming education towards personalized learning. Despite the affordances of AI-driven education platforms, concerns about data privacy, ethical issues in data handling, and regulatory compliance limit their widespread adoption. Adding to this is the limited literature that comprehensively explains the types of AI-driven educational platforms, their challenges, and the strategies for ensuring data privacy in them. This study presents findings from a Systematic Literature Review (SLR), guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) model. Included in this study were 27 journal articles drawn from Science Direct, IEEE, Springer Nature Link, and Google Scholar. The results of this study categorized the AI-driven educational platforms into Learning Management Systems (LMSs), adaptive learning, intelligent tutoring systems, learning analytics, and AI-personalized learning platforms, AI-enabled educational tools and automated scoring systems, and general AI education systems. Furthermore, several challenges of these AI-driven educational platforms were identified, which include data privacy, data breaches, bias, and the implementation of the AI-driven educational platforms. The strategies for ensuring data privacy include data encryption, user authentication, regular audits, adherence to the General Data Protection Regulation (GDPR), and differential privacy. These results facilitate the development of policies for ensuring that the AI-based educational platforms are secure, considering the large volumes of data that are collected by these and used in systems.

Artificial Intelligence, AI-Driven Education Platforms, Data, Privacy, Conceptual Framework

1. Al-Hamad, N. Q. Moodle As a Learning Management System: Perceived Efficacy and Actual Use. In Journal of Educators Online (Vol. 19, Issue 3), 2022a, https://doi.org/10.9743/JEO.2022.19.3.2 [Google Scholar] [Crossref]

2. Al-Hamad, N. Q. Moodle As a Learning Management System: Perceived Efficacy and Actual Use. Journal of Educators Online, 19(3), 2022b, https://doi.org/10.9743/JEO.2022.19.3.2 [Google Scholar] [Crossref]

3. Ali, M., Siddique, A., Aftab, A., Kamran Abid, M., Fuzail, M., & Abid, K. AI-Powered Customized Learning Paths: Transforming Data Administration for Students on Digital Platforms. Journal of Computing & Biomedical Informatics, 06(02), 2024, https://doi.org/10.56979/602/2024 [Google Scholar] [Crossref]

4. Alier, M., Casañ Guerrero, M. J., Amo, D., Severance, C., & Fonseca, D. Privacy and e-learning: A pending task. Sustainability (Switzerland), 13(16), 2021, https://doi.org/10.3390/su13169206 [Google Scholar] [Crossref]

5. Alotaibi, N. S. The Impact of AI and LMS Integration on the Future of Higher Education: Opportunities, Challenges, and Strategies for Transformation. In Sustainability (Switzerland) (Vol. 16, Issue 23). Multidisciplinary Digital Publishing Institute (MDPI), 2024, https://doi.org/10.3390/su162310357 [Google Scholar] [Crossref]

6. Altinpulluk, H., & Kesim, M. A Systematic Review of the Tendencies in the Use of Learning Management Systems. Turkish Online Journal of Distance Education, 22(3), 1–14, 2021, https://doi.org/10.17718/tojde.961812 [Google Scholar] [Crossref]

7. Arslan, A. An Empirical Design Model for an AI-enabled Learning System. 8(8), 153–167, 2021 [Google Scholar] [Crossref]

8. Bognár, L., Ágoston, G., Bacsa-Bán, A., Fauszt, T., Gubán, G., Joós, A., Juhász, L. Z., Kocsó, E., Kovács, E., Maczó, E., Mihálovicsné Kollár, A. I., & Strauber, G. Re-Evaluating Components of Classical Educational Theories in AI-Enhanced Learning: An Empirical Study on Student Engagement. Education Sciences, 14(9), 974, 974,2024, https://doi.org/10.3390/educsci14090974 [Google Scholar] [Crossref]

9. Borenstein, J., & Howard, A. Emerging challenges in AI and the need for AI ethics education. AI and Ethics, 1(1), 61–65, 2021, https://doi.org/10.1007/s43681-020-00002-7 [Google Scholar] [Crossref]

10. Chen, L., Chen, P., & Lin, Z. Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278, 2020, https://doi.org/10.1109/ACCESS.2020.2988510 [Google Scholar] [Crossref]

11. Chima Abimbola Eden, Olabisi Oluwakemi Adeleye, & Idowu Sulaimon Adeniyi. A review of AI-driven pedagogical strategies for equitable access to science education. Magna Scientia Advanced Research and Reviews, 10(2), 044–054, 2024, https://doi.org/10.30574/msarr.2024.10.2.0043 [Google Scholar] [Crossref]

12. Dube, S., and Scott, E. The organizational constraints of blending e-learning tools in education: Lecturers’ perceptions, Information Technology-New Generations: 14th International Conference on Information Technology. Springer International Publishing, 2018. [Google Scholar] [Crossref]

13. Dube, S. Educators’ pedagogical concerns on blending ICTs in teaching. In European Conference on e-Learning (pp. 150-155). Academic Conferences International Limited, 2017 [Google Scholar] [Crossref]

14. Fu, S., Gu, H., & Yang, B. The affordances of AI-enabled automatic scoring applications on learners’ continuous learning intention: An empirical study in China. British Journal of Educational Technology, 51(5), 1674–1692, 2020, https://doi.org/10.1111/bjet.12995 [Google Scholar] [Crossref]

15. Gamage, S. H. P. W., Ayres, J. R., & Behrend, M. B. A systematic review on trends in using Moodle for teaching and learning. International Journal of STEM Education, 9(1), 2022, https://doi.org/10.1186/s40594-021-00323-x [Google Scholar] [Crossref]

16. Gligorea, I., Cioca, M., Oancea, R., Gorski, A. T., Gorski, H., & Tudorache, P. Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, 13(12), 2023, https://doi.org/10.3390/educsci13121216 [Google Scholar] [Crossref]

17. Golda, A., Mekonen, K., Pandey, A., Singh, A., Hassija, V., Chamola, V., & Sikdar, B. Privacy and Security Concerns in Generative AI: A Comprehensive Survey. IEEE Access, 12(April), 48126–48144, 2024, https://doi.org/10.1109/ACCESS.2024.3381611 [Google Scholar] [Crossref]

18. Huang, L. Ethics of Artificial Intelligence in Education: Student Privacy and Data Protection. Science Insights Education Frontiers, 16(2), 2577–2587, 2023, https://doi.org/10.15354/sief.23.re202 [Google Scholar] [Crossref]

19. Kaleci, D. Integration and application of artificial intelligence tools in the Moodle platform: A theoretical exploration, 2025 [Google Scholar] [Crossref]

20. Khalil, M., Shakya, R., & Liu, Q. Towards Privacy-Preserving Data-Driven Education: The Potential of Federated Learning, 2025, https://doi.org/10.1109/ICTCS65341.2025.10989403 [Google Scholar] [Crossref]

21. Khan, M. A., Khojah, M., & Vivek. Artificial Intelligence and Big Data: The Advent of New Pedagogy in the Adaptive E-Learning System in the Higher Educational Institutions of Saudi Arabia. Education Research International, 2022, 1–10, 2022. https://doi.org/10.1155/2022/1263555 [Google Scholar] [Crossref]

22. Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y. S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. Explainable Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 3(March), 2022, https://doi.org/10.1016/j.caeai.2022.100074 [Google Scholar] [Crossref]

23. Korobenko, D., Nikiforova, A., & Sharma, R. Towards a Privacy and Security-Aware Framework for Ethical AI: Guiding the Development and Assessment of AI Systems. ACM International Conference Proceeding Series, 740–753, 2024, https://doi.org/10.1145/3657054.3657141 [Google Scholar] [Crossref]

24. Kumar, S., & Choudhury, S. Normative ethics, human rights, and artificial intelligence. AI and Ethics, 3(2), 441–450, 2023, https://doi.org/10.1007/s43681-022-00170-8 [Google Scholar] [Crossref]

25. Lin, J. ChatGPT and Moodle Walk into a Bar: A Demonstration of AI’s Mind-blowing Impact on E-Learning. SSRN Electronic Journal, 2018, 2023, https://doi.org/10.2139/ssrn.4393445 [Google Scholar] [Crossref]

26. Malhotra, P., Singh, Y., Anand, P., Bangotra, D. K., Singh, P. K., & Hong, W. C. Internet of Things: Evolution, concerns, and security challenges. Sensors, 21(5), 1–35, 2021, https://doi.org/10.3390/s21051809 [Google Scholar] [Crossref]

27. Muli, M. Legal and Ethical Implications of Data Privacy in Artificial Intelligence: A Review of Data Privacy Among Learners in Kenyan Secondary Schools. Journal of the Kenya National Commission for UNESCO, 5(1), 2024, https://doi.org/10.62049/jkncu.v5i1.170 [Google Scholar] [Crossref]

28. Mutimukwe, C., Viberg, O., Oberg, L. M., & Cerratto-Pargman, T. Students’ privacy concerns in learning analytics: Model development. British Journal of Educational Technology, 53(4), 932–951, 2022, https://doi.org/10.1111/bjet.13234 [Google Scholar] [Crossref]

29. Ndlovu, B., Dube, S., Dube, S. P., and Mpofu, S. A framework for transitioning to virtual classes during life-threatening pandemics like COVID-19, 21st European Conference on e-Learning ECEL 2022. 2022. [Google Scholar] [Crossref]

30. Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221–4241, 2023, https://doi.org/10.1007/s10639-022-11316-w [Google Scholar] [Crossref]

31. Oyebola Olusola Ayeni, Nancy Mohd Al Hamad, Onyebuchi Nneamaka Chisom, Blessing Osawaru, & Ololade Elizabeth Adewusi. AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, 18(2), 261–271, 2024, https://doi.org/10.30574/gscarr.2024.18.2.0062 [Google Scholar] [Crossref]

32. Patel, S. AI-driven educational interventions: an empirical study on their efficacy. 9(2), 145–156, 2024 [Google Scholar] [Crossref]

33. Pedro, F., Subosa, M., Rivas, A., & Valverde, P. Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development. Education Sector: United Nations Educational, Scientific, and Cultural Organization. Ministerio de Educación, 1–46, 2019, https://en.unesco.org/themes/education-policy- [Google Scholar] [Crossref]

34. Qazi, S., Kadri, M. B., Naveed, M., Khawaja, B. A., Khan, S. Z., Alam, M. M., & Su’ud, M. M. AI-Driven Learning Management Systems: Modern Developments, Challenges, and Future Trends during the Age of ChatGPT. Computers, Materials and Continua, 80(2), 3289–3314, 2024, https://doi.org/10.32604/cmc.2024.048893 [Google Scholar] [Crossref]

35. Rawamangun Muka, J., Gadung, P., Jakarta Timur, K., & Khusus, D. Ethical Problems of Digitalization and Artificial Intelligence in Education: A Global Perspective. Journal of Pharmaceutical Negative Results, 14(2), 2150–2161, 2023, https://doi.org/10.47750/pnr.2023.14.S02.254 [Google Scholar] [Crossref]

36. Razi, Q., Piyush, R., Chakrabarti, A., & Singh, A. Enhancing Data Privacy: A Comprehensive Survey of Privacy-Enabling Technologies. IEEE Access, 13(January), 40354–40385, 2025, https://doi.org/10.1109/ACCESS.2025.3546618 [Google Scholar] [Crossref]

37. Rehan, H. Shaping the Future of Education with Cloud and AI Technologies: Enhancing Personalized Learning and Securing Data Integrity in the Evolving EdTech Landscape Shaping the Future of Education with Cloud and AI Technologies: Enhancing Personalized Learning. April 2023, 2024 [Google Scholar] [Crossref]

38. Revesai, Z. Ethical Implications of AI-Driven Education Systems on Digital Rights: A Comparative Analysis. June 2024 [Google Scholar] [Crossref]

39. Neehalika Bavya, S.P.Blessina Bashapaka & Suvarchala Reddy, G. An Empirical Study on the Role of Artificial Intelligence in Human Capital Management. International Research Journal on Advanced Engineering and Management (IRJAEM), 2(03), 223–227, 2024, https://doi.org/10.47392/irjaem.2024.0035 [Google Scholar] [Crossref]

40. Saqr, R. R., Al-Somali, S. A., & Sarhan, M. Y. Exploring the Acceptance and User Satisfaction of AI-Driven e-Learning Platforms (Blackboard, Moodle, Edmodo, Coursera, and edX): An Integrated Technology Model. Sustainability (Switzerland), 16(1), 2024, https://doi.org/10.3390/su16010204 [Google Scholar] [Crossref]

41. Seprum, P., & Wongwatkit, C. Trends and issues of immersive learning environments in higher education from 2001 to 2020: Perspectives on adaptive ubiquitous learning experiences. International Journal of Mobile Learning and Organization, 16(1), 95–122, 2022, https://doi.org/10.1504/IJMLO.2022.119966 [Google Scholar] [Crossref]

42. Sergis, S., Vlachopoulos, P., Sampson, D. G., & Pelliccione, L. Handbook on Digital Learning for K-12 Schools. Handbook on Digital Learning for K-12 Schools, October 2017, https://doi.org/10.1007/978-3-319-33808-8 [Google Scholar] [Crossref]

43. Wang, M., Qin, Y., Liu, J., & Li, W. Identifying personal physiological data risks to the Internet of Everything: the case of facial data breach risks. Humanities and Social Sciences Communications, 10(1), 1–15, 2023, https://doi.org/10.1057/s41599-023-01673-3 [Google Scholar] [Crossref]

44. Wu, Y. Revolutionizing Learning and Teaching: Crafting Personalized, Culturally Responsive Curriculum in the AI Era. Creative Education, 15(08), 1642–1651, 2024, https://doi.org/10.4236/ce.2024.158098 [Google Scholar] [Crossref]

45. Xu, X. W. AI optimization algorithms enhance higher education management and personalized teaching through empirical analysis. Scientific Reports, 15(1), 1–18, 2025, https://doi.org/10.1038/s41598-025-94481-5 [Google Scholar] [Crossref]

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