“Design and Development of an Expert System for Predicting Academic Performance of Secondary School Students”

Abstract

 This study focuses on the design and development of an intelligent expert system for predicting the academic performance of secondary school students in Raigad District by examining the current status of ICT implementation, analyzing student performance, and identifying key influencing parameters such as intrinsic motivation, self-efficacy, teaching methods, and socioeconomic factors. A descriptive and analytical research design was adopted using proportionate stratified sampling across principals, teachers, students, and parents, with data collected through structured questionnaires and analyzed using statistical techniques including chi-square tests, t-tests, and factor analysis to ensure validity and reliability. The proposed system is a rule-based decision-support framework integrating a knowledge base, inference engine, and fact database to process multidimensional inputs and generate predictive outputs. It is expected to enable early identification of at-risk students, provide personalized learning recommendations, enhance teaching effectiveness, and support data-driven academic planning. The study concludes that academic performance is influenced by interconnected psychological, pedagogical, and environmental factors, and the developed expert system demonstrates strong predictive capability, contributing to improved educational outcomes, efficient resource utilization, and the advancement of ICT-enabled intelligent education systems.