Future Proof Artificial Intelligence Enhanced Educational Platforms with Personalized Learning Pathways Adaptive Curriculum Development and Virtual Collaboration

Sharanabasappa Raikoti; C. Raghavendra; M. Renuga; M. P. Revathi; Soni Maitrik Chandrakant; M. Devi

doi:10.2991/978-94-6463-718-2_55

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Future Proof Artificial Intelligence Enhanced Educational Platforms with Personalized Learning Pathways Adaptive Curriculum Development and Virtual Collaboration

Authors

Sharanabasappa Raikoti¹^{, *}, C. Raghavendra², M. Renuga³, M. P. Revathi⁴, Soni Maitrik Chandrakant⁵, M. Devi⁶

¹Assistant Professor, Department of Computer Science, Government First Grade College, Chittapur, 585211, Karnataka, India

²Associate Professor, Department of Cyber Security, CVR College of Engineering, Hyderabad, Telangana, India

³Professor, Department of English, Sona College of Technology, Salem, 636005, Tamil Nadu, India

⁴Professor, Department of Computer Science and Engineering, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India

⁵Research Scholar, Department of Computer Science, Sabarmati University, Ahmedabad, Gujarat, India

⁶Assistant Professor, Department of EEE, New Prince Shri Bhavani College of Engineering and Technology, Chennai, 600073, Tamil Nadu, India

^*Corresponding author. Email: sr.raikoti@gmail.com

Corresponding Author

Sharanabasappa Raikoti

Available Online 23 May 2025.

DOI: 10.2991/978-94-6463-718-2_55 How to use a DOI?
Keywords: Artificial Intelligence in Education; Personalized Learning; Adaptive Curriculum; Virtual Collaboration; AI-Powered Learning; Educational Technology; Future-Proof Learning
Abstract: AI is revolutionizing the education sector with personalized learning pathways, adaptive curriculum development, and virtual collaboration tools. But research in this area is mostly theoretical, limited in scope, and unproven in real life. This study addresses this gap by creating and deploying future-proof AI-augmented educational platforms incorporating multi-AI architectures for personalized learning, teacher-AI co-teaching, and accessibility-oriented education. The proposed system will leverage sustainable AI adoption, allowing for seamless integration of AI-powered analytics, predictive learning methods, and ethical AI paradigms to nurture diverse populations of learners. With a shift from existing models of focused AI implementations towards an organisationally open, multi-disciplinary AI learning framework, the research focuses on the overarching issues of inclusivity, data transparency and educational equity. Using empirical studies in a range of learning settings, this will validate AI’s role in boosting student engagement, improving learning outcomes and reshaping digital education in the future. Introduced is a new AI approach that addresses the challenges of scalability, ethics, and AI-human collaboration in the educational sphere.
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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Volume Title: Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series: Advances in Computer Science Research
Publication Date: 23 May 2025
ISBN: 978-94-6463-718-2
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-718-2_55 How to use a DOI?
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.

Cite this article

ris enw bib

TY  - CONF
AU  - Sharanabasappa Raikoti
AU  - C. Raghavendra
AU  - M. Renuga
AU  - M. P. Revathi
AU  - Soni Maitrik Chandrakant
AU  - M. Devi
PY  - 2025
DA  - 2025/05/23
TI  - Future Proof Artificial Intelligence Enhanced Educational Platforms with Personalized Learning Pathways Adaptive Curriculum Development and Virtual Collaboration
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 633
EP  - 647
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_55
DO  - 10.2991/978-94-6463-718-2_55
ID  - Raikoti2025
ER  -

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