Research Trends in the Utilization of Artificial Intelligence in Education: Gaps and Opportunities in Library and Information Science

Abstract

This systematic review synthesises findings from 100 studies examining the integration of artificial intelligence (AI) within educational contexts. Employing a comprehensive analytical framework, the review categorises and assesses the objectives, applications, and outcomes of AI across diverse learning environments. Seven primary domains of educational focus were identified: AI literacy, personalised and adaptive learning, curriculum design, performance assessment, teacher support, educational administration, and ethical and social considerations. Prominent trends include a concentration on K–12 education (65%), an increasing adoption of generative AI tools such as ChatGPT (40%), a movement from tool-centric approaches towards embedding AI within pedagogical practices (70%), and a growing number of cross-cultural comparative studies (30%). Predictive statistical models for 2023–2025 indicate that AI literacy and generative AI applications will become increasingly prevalent, with 85% of experimental studies reporting enhancements in student learning outcomes, motivation, and collaborative skills. Despite these advances, research gaps remain in early childhood education and special education contexts. The review highlights future research directions, including interdisciplinary AI applications, longitudinal studies on the development of higher-order cognitive skills, frameworks for AI accountability, AI implementation in underrepresented settings, and AI-supported teaching practices. Overall, the evidence underscores AI’s potential not merely as a technological tool but as a catalyst for redefining educational approaches, facilitating personalised learning, and strengthening educator capabilities. This synthesis provides a consolidated reference for educators and researchers to optimise the use of AI in instructional and learning processes.