Advancing Personalized Learning through Artificial Intelligence: Practical, Ethical and Scalable Approaches to Tailoring Educational Content for Diverse Student Needs and Learning Styles

V. Rekha, C. Ramya, K. Sivakumar, K. Arulini, K. S. Guruprasad, G. V. Rambabu

2025

Abstract

Artificial Intelligence (AI) in education has allowed for new ways to promote personalized learning tailored to the student's needs and the student's learning style. To overcome the shortcomings of existing studies which are not scalable, suffer from biased datasets, and lack a real application in the field of AI-based personalized learning, in this work, a practical and ethically-aligned scalable framework of AI-driven personalized learning is proposed. The paper presents adaptive methods based on models learned over comprehensive and balance data sets to deliver fair and responsive content. The classroom simulation model is employed to demonstrate its practical feasibility at the real classroom levels with the emphasis on the measurable leaming results and long-term effective application. The ethical considerations such as privacy, transparency and explainability are considered in system construction. Supporting both technical depth and pedagogical relevance, we present a substantial, deployable model acting as a midrange solution between academic rigor and classroom reality. Results show remarkable enhancements in learning engagement, adaptability and performance for different learning environments.

Paper Citation

in Harvard Style

Rekha V., Ramya C., Sivakumar K., Arulini K., Guruprasad K. and Rambabu G. (2025). Advancing Personalized Learning through Artificial Intelligence: Practical, Ethical and Scalable Approaches to Tailoring Educational Content for Diverse Student Needs and Learning Styles. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 236-242. DOI: 10.5220/0013862000004919

in Bibtex Style

@conference{icrdicct`2525,
author={V. Rekha and C. Ramya and K. Sivakumar and K. Arulini and K. Guruprasad and G. Rambabu},
title={Advancing Personalized Learning through Artificial Intelligence: Practical, Ethical and Scalable Approaches to Tailoring Educational Content for Diverse Student Needs and Learning Styles},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25},
year={2025},
pages={236-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013862000004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25
TI - Advancing Personalized Learning through Artificial Intelligence: Practical, Ethical and Scalable Approaches to Tailoring Educational Content for Diverse Student Needs and Learning Styles
SN - 978-989-758-777-1
AU - Rekha V.
AU - Ramya C.
AU - Sivakumar K.
AU - Arulini K.
AU - Guruprasad K.
AU - Rambabu G.
PY - 2025
SP - 236
EP - 242
DO - 10.5220/0013862000004919
PB - SciTePress