AHCI RESEARCH GROUP
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proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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2025
Yadav, R.; Huzooree, G.; Yadav, M.; Gangodawilage, D. S. K.
Generative AI for personalized learning content creation Book Section
In: Transformative AI Practices for Personalized Learning Strategies, pp. 107–130, IGI Global, 2025, ISBN: 979-836938746-7 (ISBN); 979-836938744-3 (ISBN).
Abstract | Links | BibTeX | Tags: Adaptive feedback, Advanced Analytics, AI systems, Contrastive Learning, Educational contents, Educational experiences, Enhanced learning, Ethical technology, Federated learning, Immersive, Learning content creation, Personalized learning, Student engagement, Students, Supervised learning, Tools and applications, Virtual Reality
@incollection{yadav_generative_2025,
title = {Generative AI for personalized learning content creation},
author = {R. Yadav and G. Huzooree and M. Yadav and D. S. K. Gangodawilage},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005387236&doi=10.4018%2f979-8-3693-8744-3.ch005&partnerID=40&md5=904e58b9c6de83dcd431c1706dda02b3},
doi = {10.4018/979-8-3693-8744-3.ch005},
isbn = {979-836938746-7 (ISBN); 979-836938744-3 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Transformative AI Practices for Personalized Learning Strategies},
pages = {107–130},
publisher = {IGI Global},
abstract = {Generative AI has emerged as a transformative force in personalized learning, offering unprecedented opportunities to tailor educational content to individual needs. By leveraging advanced algorithms and data analysis, AI systems can dynamically generate customized materials, provide adaptive feedback, and foster student engagement. This chapter explores the intersection of generative AI and personalized learning, discussing its techniques, tools, and applications in creating immersive and adaptive educational experiences. Key benefits include enhanced learning outcomes, efficiency, and scalability. However, challenges such as data privacy, algorithmic bias, and equitable access must be addressed to ensure responsible implementation. Future trends, including the integration of immersive technologies like Virtual Reality (VR) and predictive analytics, highlight AI's potential to revolutionize education. By navigating ethical considerations and fostering transparency, generative AI can become a powerful ally in creating inclusive, engaging, and student- centered learning environments. © 2025, IGI Global Scientific Publishing. All rights reserved.},
keywords = {Adaptive feedback, Advanced Analytics, AI systems, Contrastive Learning, Educational contents, Educational experiences, Enhanced learning, Ethical technology, Federated learning, Immersive, Learning content creation, Personalized learning, Student engagement, Students, Supervised learning, Tools and applications, Virtual Reality},
pubstate = {published},
tppubtype = {incollection}
}
Generative AI has emerged as a transformative force in personalized learning, offering unprecedented opportunities to tailor educational content to individual needs. By leveraging advanced algorithms and data analysis, AI systems can dynamically generate customized materials, provide adaptive feedback, and foster student engagement. This chapter explores the intersection of generative AI and personalized learning, discussing its techniques, tools, and applications in creating immersive and adaptive educational experiences. Key benefits include enhanced learning outcomes, efficiency, and scalability. However, challenges such as data privacy, algorithmic bias, and equitable access must be addressed to ensure responsible implementation. Future trends, including the integration of immersive technologies like Virtual Reality (VR) and predictive analytics, highlight AI's potential to revolutionize education. By navigating ethical considerations and fostering transparency, generative AI can become a powerful ally in creating inclusive, engaging, and student- centered learning environments. © 2025, IGI Global Scientific Publishing. All rights reserved.