Journal of Information Systems Engineering and Management

AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms
Ming Yang 1, Fuyuan Weng 2 *
More Detail
1 Ph.D candidate, Krirk University, Bangkok, Thailand
2 Professor, Krirk University, Bangkok, Thailand
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2023 - Volume 8 Issue 1, Article No: 23196
https://doi.org/10.55267/iadt.07.14079

Published Online: 27 Jan 2023

Views: 253 | Downloads: 244

How to cite this article
APA 6th edition
In-text citation: (Yang & Weng, 2023)
Reference: Yang, M., & Weng, F. (2023). AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms. Journal of Information Systems Engineering and Management, 8(1), 23196. https://doi.org/10.55267/iadt.07.14079
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Yang M, Weng F. AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms. J INFORM SYSTEMS ENG. 2023;8(1):23196. https://doi.org/10.55267/iadt.07.14079
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Yang M, Weng F. AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms. J INFORM SYSTEMS ENG. 2023;8(1), 23196. https://doi.org/10.55267/iadt.07.14079
Chicago
In-text citation: (Yang and Weng, 2023)
Reference: Yang, Ming, and Fuyuan Weng. "AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms". Journal of Information Systems Engineering and Management 2023 8 no. 1 (2023): 23196. https://doi.org/10.55267/iadt.07.14079
Harvard
In-text citation: (Yang and Weng, 2023)
Reference: Yang, M., and Weng, F. (2023). AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms. Journal of Information Systems Engineering and Management, 8(1), 23196. https://doi.org/10.55267/iadt.07.14079
MLA
In-text citation: (Yang and Weng, 2023)
Reference: Yang, Ming et al. "AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms". Journal of Information Systems Engineering and Management, vol. 8, no. 1, 2023, 23196. https://doi.org/10.55267/iadt.07.14079
ABSTRACT
Since college students rely more on online education, artificial intelligence (AI) is changing virtual learning paths. The study shows how schools are personalising instruction and improving student engagement, comprehension, and retention with AI algorithms and data analytics. The essay covers key features of AI-powered personalised learning , from content recommendations to customisable evaluations and real-time feedback. The essay critiques these innovations' ethical and transparency difficulties, despite their potential benefits. It emphasises ethical AI-driven teaching by highlighting prejudice and data privacy issues. AI can improve education, but it has limitations, recommending a balance between innovation and ethical scrutiny. The paper proposes federated learning to address these difficulties. Federated learning decentralises data and encourages diverse data sets in localised environments to reduce biases and privacy breaches. Federated learning protects privacy, making it a viable AI-driven education solution, as the study shows. AI-facilitated customised learning may improve academic performance and digital skills, according to the study. It stresses ethics and openness in AI-driven education. Federated learning may help ethically integrate AI into education by balancing privacy and personalisation.
KEYWORDS
REFERENCES
  • Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101.
  • Al-Badi, A., & Khan, A. (2022). Perceptions of Learners and Instructors towards Artificial Intelligence in Personalized Learning. Procedia Computer Science, 201, 445-451.
  • Bernius, J. P., Krusche, S., & Bruegge, B. (2022). Machine learning based feedback on textual student answers in large courses. Computers and Education: Artificial Intelligence, 3, 100081.
  • Bhutoria, A. (2022). Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a human-in-the-loop model. Computers and Education: Artificial Intelligence, 3, 100068.
  • Charles, F. (2023). AI-Powered Personalized Mobile Education for New Zealand Students. International Journal Software Engineering and Computer Science (IJSECS), 3(1), 33-39.
  • Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education: Contributors, collaborations, research Topics, challenges, and future directions. Educational Technology and Society, 25(1), 28-47.
  • Cherner, T., Fegely, A., Hou, C., & Halpin, P. (2023). AI-powered presentation platforms for improving public speaking skills: Takeaways and suggestions for improvement. Journal of Interactive Learning Research, 34(2), 339-367.
  • Dogan, M. E., Goru Dogan, T., & Bozkurt, A. (2023). The use of artificial intelligence (AI) in online learning and distance education processes: A systematic review of empirical studies. Applied Sciences, 13(5), 3056.
  • Huang, A. Y., Lu, O. H., & Yang, S. J. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684.
  • Kamruzzaman, M. M., Alanazi, S., Alruwaili, M., Alshammari, N., Elaiwat, S., Abu-Zanona, M., ... Ahmed Alanazi, B. (2023). AI-and IoT-Assisted Sustainable Education Systems during Pandemics, such as COVID-19, for Smart Cities. Sustainability, 15(10), 8354.
  • Mangi, M., Anwar, R. S., Khan, S., Rehman, M. Z., Bhatti, M. I., & Alonazi, W. B. (2023). Enhancing Sustainability in the Agricultural Sector Amid COVID-19: An Implication of the Transactional Theory. Sustainability, 15(13), 9960.
  • ÖZÇİFT, A. (2023). Artificial Intelligence in Educational Sciences and Real World Applications. PIONEER AND CONTEMPORARY STUDIES IN EDUCATIONAL SCIENCES, 29-42. https://doi.org/10.59287/pcses.330
  • Qu, J., Zhao, Y., & Xie, Y. (2022). Artificial intelligence leads the reform of education models. Systems Research and Behavioral Science, 39(3), 581-588.
  • Shaikh, F., Afshan, G., Anwar, R. S., Abbas, Z., & Chana, K. A. (2023). Analyzing the impact of artificial intelligence on employee productivity: the mediating effect of knowledge sharing and well‐being. Asia Pacific Journal of Human Resources, 61(4), 794-820.
  • St-Hilaire, F., Vu, D. D., Frau, A., Burns, N., Faraji, F., Potochny, J., ... Kochmar, E. (2022). A new era: Intelligent tutoring systems will transform online learning for millions. https://doi.org/10.48550/arXiv.2203.03724
  • Thomas, B. J., & Alkhafaji, S. (2023). Gamification of Personalized Learning Through Massive Open Online Courses: Learner-to-AI Enabled Chatbot. In S. Goundar (Ed.), Massive Open Online Courses - Current Practice and Future Trends. Rijeka, Croatia: IntechOpen. https://doi.org/10.5772/intechopen.1001113
  • Trojer, L., Ambele, R. M., Kaijage, S. F., & Dida, M. A. (2022). A review of the Development Trend of Personalized learning Technologies and its Applications. International Journal of Advances in Scientific Research and Engineering, 8(11), 75-91.
  • Umutlu, D., & Gursoy, M. E. (2022). Leveraging Artificial Intelligence Techniques for Effective Scaffolding of Personalized Learning in Workplaces. In D. Ifenthaler & S. Seufert (Eds.), Artificial Intelligence Education in the Context of Work (pp. 59-76). Cham, Switzerlan: Springer International Publishing.
LICENSE
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.