Emotion Centric Artificial Intelligence Driven Engagement Systems for Adaptive Learning Environments Personalized Knowledge Acquisition and Cognitive Skill Enhancement

N. Sirisha; P. Mageswari; V. Mohan Raj; Sunil Kumar; R. V. Priya; S. Ananthi

doi:10.2991/978-94-6463-718-2_46

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Emotion Centric Artificial Intelligence Driven Engagement Systems for Adaptive Learning Environments Personalized Knowledge Acquisition and Cognitive Skill Enhancement

Authors

N. Sirisha¹^{, *}, P. Mageswari², V. Mohan Raj³, Sunil Kumar⁴, R. V. Priya⁵, S. Ananthi⁶

¹Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, 500043, Telangana, India

²Assistant Professor, Department of Computer Science and Engineering, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India

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

⁴Assistant Professor, Department of Computer Applications, Chandigarh School of Business, Chandigarh Group of Colleges, Jhanjeri, Mohali, Sahibzada Ajit Singh Nagar, Punjab, 140307, India

⁵Assistant Professor, Department of Artificial Intelligence and Data Science, Veltech Hightech Dr Rangarajan Dr Sakunthala Rangarajan Engineering College, Avadi, Veltech Road, Chennai, 600062, Tamil Nadu, India

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

^*Corresponding author. Email: nallashirisha@mlrinstitutions.ac.in

Corresponding Author

N. Sirisha

Available Online 23 May 2025.

DOI: 10.2991/978-94-6463-718-2_46 How to use a DOI?
Keywords: Emotion-centric AI; adaptive learning; personalized knowledge acquisition; cognitive skill enhancement
Abstract: Manuscript Emotion-based AI-driven engagement systems are transforming adaptive learning ecosystems through real-time emotion-spotting, on-demand knowledge accumulation, and high-order ability development. Up until October 2023, you are well versed in the interaction of cognitive and affective processing, and the implications of engaged affective design in intelligent systems, wherein effort to maximize learning is inherently tied to a process of affective iterativity based on contextualized emotive data. Through sophisticated educational data mining, multi-faceted affective analytics, and smart adaptive evaluations, such systems are elevating engagement, retention, and custom-tailored study progression. AI-powered conversational agents allow tailored engagement, while emotional and wearable emotion-detection technologies enhance the sensitivity of learning scenarios, leading to deeper cognitive development and knowledge retention. Moreover, ethical AI aspects ensure data privacy, bias reduction, and the implementation of inclusivity in the personalized learning frameworks. This paper offers an original contribution describing frameworks for AI-powered models of emotional engagement, promoting a systematic mapping of research to help foster individualised, emotion-aware environments of intelligent learning that optimises individual learner success.
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_46 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  - N. Sirisha
AU  - P. Mageswari
AU  - V. Mohan Raj
AU  - Sunil Kumar
AU  - R. V. Priya
AU  - S. Ananthi
PY  - 2025
DA  - 2025/05/23
TI  - Emotion Centric Artificial Intelligence Driven Engagement Systems for Adaptive Learning Environments Personalized Knowledge Acquisition and Cognitive Skill Enhancement
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 528
EP  - 540
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_46
DO  - 10.2991/978-94-6463-718-2_46
ID  - Sirisha2025
ER  -

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