Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{164558,
        author = {Krishnaprasad Venkatesh Awala and Tushar Kumar Tailor and Prof. Dr. Rekha Sugandhi},
        title = {AI-Driven Academic Excellence By Building An Advanced Student Performance Analysis System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {1723-1730},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164558},
        abstract = {In the world of student overall performance evaluation, conventional assessment methods frequently fall quick in capturing the multifaceted nature of pupil success. This paper introduces a unique approach to student performance evaluation, aiming to head past quantitative metrics and encompass a holistic view of pupil development. By leveraging modern technologies and facts-pushed frameworks, our proposed system seeks to offer educators with comprehensive insights into student overall performance, allowing customized getting to know techniques and knowledgeable choice-making. Through dynamic dashboards and interactive visuals, educators can discover pupil facts across various dimensions, uncovering traits and styles that traditional strategies might also neglect. This paper outlines the improvement of an included system that mixes authentication, dashboards, questionnaires, and records importing/parsing functionalities to create a sturdy platform for student overall performance evaluation. The closing purpose is to empower educators with the gear they want to manual students closer to fulfillment of their educational journey.},
        keywords = {Student Analysis System, Holistic Assessment, Quantitative Metrics, Web Application, OCEAN Traits},
        month = {},
        }