Artificial Intelligence in University Pedagogy: A Bibliometric Assessment of AI’s Impact on Teaching and Learning Outcomes in Universities Globally

Abstract

This bibliometric study examines the global impact of artificial intelligence (AI) on university pedagogy, focusing on teaching and learning outcomes from 2019 to 2024. Using Biblioshiny, we analyzed publication trends, key contributors, thematic clusters, and collaboration networks across 7 objectives. Findings reveal a significant increase in publications post-November 2022, with a 150% growth rate from 2022 to 2023, driven by top institutions like the University of California and countries such as the United States and China. Leading authors, including Gaeevi, Dragan, shape the field, with highly cited works emphasizing AI’s role in human-centered education. Thematic analysis highlights evolving.trends in learning analytics and AI-driven predictive modeling, though empirical validation of student outcomes remains limited. Global collaboration is diverse but fragmented, with minimal contributions from less-resourced regions. AI’s influence on teaching methodologies shows a shift toward data-driven, personalized practices, underscoring the need for further experimental research to validate its efficacy

Ähnliche Arbeiten