AI-Driven Academic Excellence By Building An Advanced Student Performance Analysis System

Krishnaprasad Venkatesh Awala; Tushar Kumar Tailor; Prof. Dr. Rekha Sugandhi

AI-Driven Academic Excellence By Building An Advanced Student Performance Analysis System

Authors: Krishnaprasad Venkatesh Awala, Tushar Kumar Tailor, Prof. Dr. Rekha Sugandhi

Unique Paper ID: 164558
Volume: 10
Issue: 12
PageNo: 1723-1730

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.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 10
Issue: 12
PageNo: 1723-1730

AI-Driven Academic Excellence By Building An Advanced Student Performance Analysis System

Available:https://ijirt.org/Article?manuscript=164558

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now