Research Methodologies, System Design, and Implementation Factors of Artificial Intelligence in Education (AIED) in Pakistani Higher Education: A Systematic Literature Review

Abstract

Artificial Intelligence in Education (AIED) refers to intelligent computational systems designed to support learning, teaching, and academic decision-making. This study explored how AIED is researched, conceptualized, and discussed in Pakistani higher education by examining three central variables: research methodologies, AI system design, and reported advantages and challenges. A systematic literature review approach was employed to analyse peer-reviewed studies published between 2020 and 2025, retrieved through PRISMA-aligned database searches. The data were thematically examined. The findings show that Pakistani AIED literature is dominated by descriptive and review-based methods, with limited empirical research to validate AI tools in real academic settings. AIED systems are often portrayed as adaptive and data-driven, yet remain largely theoretical due to infrastructural and institutional limitations. While potential benefits such as personalization, automation, and enhanced engagement are mentioned, they lack strong local evidence; meanwhile, challenges such as weak digital infrastructure, insufficient faculty training, and absence of policy frameworks emerge as persistent barriers. The study offers a consolidated understanding of AIED research in Pakistan and highlights structural and methodological gaps that must be addressed for effective AI integration.