A Literature Review of Empirical Studies on Empowering GIDA Schools Through AI-Based Academic Data Management

Abstract

This study presents a systematic literature review of empirical research on the use of artificial intelligence (AI)–based academic data management systems in Geographically Isolated and Disadvantaged Areas (GIDA) schools. The review synthesizes studies addressing persistent challenges faced by GIDA schools, including limited infrastructure, scarce resources, and constraints in accessing qualified personnel and learning materials. Using established systematic review procedures, the study examines current academic data management practices, feasibility considerations for AI integration in low-resource settings, and AI technologies reported as suitable for geographically isolated school contexts. The reviewed literature indicates that while AI-driven academic data systems have demonstrated benefits in improving administrative efficiency, data accuracy, and decision-making in well-resourced schools, their application in GIDA schools remains limited. Nevertheless, evidence suggests that context-appropriate AI solutions—particularly those supporting offline functionality, low-bandwidth operation, and user-friendly interfaces—hold significant potential for strengthening academic data management and promoting educational equity. The findings underscore the importance of aligning AI initiatives with local conditions, capacity-building efforts, and national education policies to support inclusive digital transformation in GIDA schools.