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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65404
Volume:
10 |
6 |
Jun 2026
Pages:
1-11
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Application
Nehru Institute of Information Technology and Management
MCA, M.Phil., Ph.D,Head of the Department, Department of Computer Application
Nehru Institute of Information Technology and Management
C.O.G.N.I.S is proposed as an intelligent academic and career support platform that integrates AI-driven resume screening, conversational assistance, emotion analysis, and adaptive learning recommendations within a unified architecture. The system combines NLP, computer vision, and machine learning to deliver personalized guidance while improving recruitment readiness and learner engagement. This paper positions the platform as a research contribution by presenting its architecture, research objectives, and evaluation framework for engineering education.
KEYWORDS
The AI-Based Student Support System was successfully developed as an intelligent platform that enhances learning through Artificial Intelligence. It combines features such as an AI chatbot, resume screening, emotion analysis, and personalized learning recommendations to provide better academic support for students. The system helps students access study materials, receive instant assistance, improve their resumes, and get personalized learning suggestions. It also enables teachers to monitor student progress and allows parents to stay informed about their child's academic performance. Developed using HTML, CSS, Bootstrap, JavaScript, PHP, Python, and MySQL, the system is secure, user-friendly, and scalable. Overall, the project demonstrates how AI can improve the learning experience by making education more interactive, personalized, and efficient.
[1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020. [2] I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning, MIT Press, 2016. [3] A. Rajaraman and J. D. Ullman, Mining of Massive Datasets, Cambridge University Press, 2019. [4] A. Kumar and R. Gupta, "AI-Based Resume Screening System Using Natural Language Processing," International Journal of Computer Applications, 2022. [5] S. Sharma and P. Verma, "Chatbot Systems for Education Using NLP Techniques," International Journal of Engineering Research & Technology (IJERT), 2023. [6] H. Li and J. Zhang, "Emotion Recognition Using Deep Learning and Computer Vision Techniques," IEEE Access, 2021, pp. 11234–11245. [7] A. Patel and R. Singh, "Personalized Learning Recommendation Systems in E-Learning Platforms," International Journal of Advanced Computer Science and Applications, 2022. [8] K. Sharma, "Machine Learning Approaches in Educational Data Mining," International Journal of Computer Science Trends and Technology, 2021. [9] S. Brown and T. Wilson, "Natural Language Processing for Intelligent Chatbots," Proceedings of IEEE International Conference on AI Systems, 2020. [10] TensorFlow Documentation, https://www.tensorflow.org/
Publication Date
6/24/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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