Artificial intelligence and students’ cognitive learning outcomes with bibliometric and content analysis for future research agenda
Shaukat Rahman Ansari, Ika Nurul Qamari
Abstract
This study conducted a comprehensive bibliometric and content analysis to explore the integration of artificial intelligence in students’ cognitive learning outcomes. A structured TITLE-ABS-KEY search was performed in the Scopus database using keywords such as “Artificial Intelligence,” “AI,” “Students,” and “cognitive learning outcomes,” resulting in 318 documents published between 2016 and 2025. After filtering, a final dataset of 246 research articles and conference papers was analyzed. The methodology includes bibliometric performance analysis (covering publication trends, countries, affiliations, authors, and journals) and network analysis (comprising co-word, citation, co-authorship, and bibliographic coupling). Additionally, content analysis was conducted on the ten most cited and ten focused articles addressing AI’s impact on cognitive learning outcomes. VOSviewer software was used for data analysis and visualization. Findings indicate increased research output post-2023, driven by digital transformation and global collaboration. Leading affiliations include The University of Hong Kong and Carnegie Mellon University, with the United States, China, and India as top contributing countries. Influential journals and funding bodies include the National Science Foundation and the National Natural Science Foundation of China. Notable authors include Chiu and Cukurova, while Kit Ng, Zhong, and Liu are prominent in bibliographic coupling, emphasizing AI adoption. Co-authorship analysis shows collaboration primarily among developed nations. Co-word analysis reveals Key research themes include contrastive learning, adversarial machine learning, and federated learning. Content analysis highlights AI’s transformative potential for learning, teaching, cognitive learning, and innovation. This study provides managerial and practical recommendations for students, universities, and policymakers. This study has several limitations that future studies will consider.