AI-Driven Academic Excellence By Building An Advanced Student Performance Analysis System
Author(s):
Krishnaprasad Venkatesh Awala, Tushar Kumar Tailor, Prof. Dr. Rekha Sugandhi
Keywords:
Student Analysis System, Holistic Assessment, Quantitative Metrics, Web Application, OCEAN Traits
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.
Article Details
Unique Paper ID: 164558

Publication Volume & Issue: Volume 10, Issue 12

Page(s): 1723 - 1730
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