AI-Powered Personalization in Online Learning Systems for Enhanced Engagement and Effective Learning using Collaborative and Content-Based filtering algorithms

DOI

10.2991/978-94-6463-718-2_94How to use a DOI?

Keywords

Personalized Learning; Artificial Intelligence (AI); Adaptive Assessments; Skill Tracking; Skill Maintenance; Dynamic Learning Pathways; AI in Education; E-Learning Platforms; AI-Generated Quizzes; Lifelong Learning; Recommendation Systems; Collaborative Learning; Community Engagement

Abstract

As continuous skill development continues to grow in importance in our fast-paced, technology-driven world, the shortcomings of existing e-learning platforms are becoming increasingly clear. Although there are many learning assets and tools out in the wild, such as Coursera and Udemy, for example, courses are designed with a one-size-fits-all approach that is rigid and doesn’t address personalized needs. However, learners struggle to preserve pre-existing competencies when learning more, leading to ineffective learning that also creates redundancy of skills. This paper provides a new artificial intelligence (AI)-based approach for personalized learning support, AI-Enhanced Personalized Learning Support System (APeLSS), that transforms educational instruction and support from static and generic into adaptive, personalized, and dynamic. Utilizing AIED, the system develops personalized learning trajectories, practice adaptive assessments, and instantly provides feedback on language and composition abilities. A 360 degree tracking interface provides the mentor and organizations insights into the progress being being made, identify gaps in knowledge and provide exactly the right support. Additionally, it includes collaborative elements like discussion boards and instant messaging tools, encouraging peer learning and information exchange. If people stick to defined learning goals and this system helps them to adjust to the changes around them, it can provide the right 3D training for people and institutions in our modern times.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - S. Vadivel
AU  - R. Banupriya
AU  - M. K. Nivodhini
AU  - N. D. Surendhar
AU  - N. Subashree
AU  - M. Sabesh Murali
PY  - 2025
DA  - 2025/05/23
TI  - AI-Powered Personalization in Online Learning Systems for Enhanced Engagement and Effective Learning using Collaborative and Content-Based filtering algorithms
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 1114
EP  - 1139
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_94
DO  - 10.2991/978-94-6463-718-2_94
ID  - Vadivel2025
ER  -