pisco_log
banner

Research on the Construction of AI-Based Precision Personalized Support System for Online Learning

Kaixuan Chen*

Abstract


Amid the rapid development of internet and information technologies, online learning has emerged as a pivotal educational modality, with research in this field steadily growing and recently reaching its peak. China, India, and the United States are leading nations in AI-driven online learning and distance education research [1]. However, traditional online learning suffers from drawbacks such as information
overload and a lack of individualization. This study draws inspiration from targeted advertising methodologies, integrating them with the
demands of online learning scenarios to explore the construction of a precision personalized learning support system leveraging artificial intelligence (AI).

Keywords


Artificial Intelligence; Online Learning; Distance Education; Personalized Learning; Educational Quantification

Full Text:

PDF

Included Database


References


[1] Ouyang F, Zheng L, Jiao P. Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to

2020[J]. Education and Information Technologies, 2022, 27(6): 7893-7925.

[2] Jia K, Wang P, Li Y, et al. Research landscape of artificial intelligence and e-learning: a bibliometric research[J]. Frontiers in psychology, 2022, 13: 795039.

[3] Sumathy V, Navamani G. AI-Driven Personalized Learning: Enhancing Student Success through Adaptive Technologies[J]. Library of

Progress-Library Science, Information Technology & Computer, 2024, 44(3).

[4] Chen L, Chen P, Lin Z. Artificial intelligence in education: A review[J]. Ieee Access, 2020, 8: 75264-75278.

[5] Sasikala P, Ravichandran R. Study on the Impact of Artificial Intelligence on Student Learning Outcomes[J]. Journal of Digital Learning

and Education, 2024, 4(2): 145-155.

[6] Dogan M E, Goru Dogan T, Bozkurt A. The use of artificial intelligence (AI) in online learning and distance education processes: A systematic review of empirical studies[J]. Applied sciences, 2023, 13(5): 3056.

[7] Wang X, Zhang L, He T. Learning performance prediction-based personalized feedback in online learning via machine learning[J]. Sustainability, 2022, 14(13): 7654.

[8] Kotsiantis S, Pierrakeas C, Pintelas P. Predicting Students' performance in Distance Learning Using Machine Learning Techniques[J].

Applied Artificial Intelligence, 2004, 18(5): 411-426.




DOI: http://dx.doi.org/10.70711/aitr.v3i2.7868

Refbacks

  • There are currently no refbacks.