The Impact of Artificial Intelligence on teachers of the Higher Education Sector - A Systematic Literature Review using PRISMA and VOS viewer.

Abstract

Introduction: This study analyzes the impact of Artificial Intelligence on higher education teachers through a Systematic Literature Review (SLR) guided by Preferred Reporting Items for Systematic Reviews (PRISMA) and bibliometric methods. The study aims to examine and synthesize the existing body of literature on this topic.

Objectives: This research focuses on identifying the key trends, areas, and gaps in the literature that will give complete insight into how Artificial Intelligence affects higher education from the teachers' perspective over the past decade.

Methods: The analysis was done using the Web of Science and Scopus databases, resulting in 29 articles identified through meticulous filtration of the PRISMA protocol. The study identified gaps in current research, particularly the absence of comprehensive studies examining the long-term effects of AI on teachers' professional growth and academic experiences. VOS software has been used to analyze and visualize bibliometric networks.

Results: While mapping the literature, the study is based on models such as the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Self-determination theory (SDT) that how AI affects teachers’ attitudes, preferences, motivation, etc. with context to the higher education sector. The results of the PRISMA analysis revealed the key issues such as skill adaptation, ethical considerations, and the relationship between AI and human-centered teaching practices.

Conclusions: The study offers valuable insights for researchers, educational institutions, and policymakers who aim to integrate AI while maintaining educators' essential role in the academic landscape