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Student Performance Prediction and Future Guidance System

Year: 2026

Type: article

Abstract: This paper presents a system for predicting student performance and providing future academic guidance using data analysis and rule-based techniques. The system analyzes student data such as attendance, marks, and study patterns to predict academic outcomes. Based on the predictions, it suggests personalized guidance to help students improve their performance. The proposed model assists educators in identifying weak students early and enables timely intervention. Experimental results show that the system can effectively predict student performance with good accuracy.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.19567259

Authors: Gunja Narsingh Yadav, gunja, Dr. Manoj singh

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7154245363

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