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Bibliometric Review of Artificial Intelligence in Project-Based Learning: Trends and Gaps in Social Sciences, Arts, and Humanities

Authors: Alfan Bramantya; Eko Pujiati; Dedi Kuswandi; null Fikri Aulia; Sri Untari;

Bibliometric Review of Artificial Intelligence in Project-Based Learning: Trends and Gaps in Social Sciences, Arts, and Humanities

Abstract

Purpose – The rapid development of artificial intelligence (AI) has significantly transformed various aspects of human life, particularly in education. This study aims to examine trends in the use of AI within project-based learning (PjBL) strategies, specifically in the context of social, arts, and humanities topics, over the period of 2014–2024.Method – This study is a bibliometric review. The authors collected relevant research data from the Scopus database using the keywords ("artificial intelligence" OR "AI") AND ("project-based learning" OR "PjBL") AND ("education" OR "educational"), which were then analyzed using VOSviewer software version 1.6.20. At least 120 articles were gathered, and after article extraction, 41 articles were selected for analysis in this study. Findings – The bibliometric review provides a comprehensive understanding of the current state of research on PjBL and AI. While significant progress has been made through interdisciplinary collaborations and high-impact publications, addressing the identified gaps in ethics, global integration, and inclusivity is crucial for realizing the full potential of AI in education. These efforts will enable the development of innovative, ethical, and globally relevant solutions to educational challenges. Research Implications – This research enriches the discourse on educational innovation through a bibliometric review, highlighting the need for interdisciplinary collaboration to integrate AI in PBL. It emphasizes partnerships among computer scientists, educators, and social science experts to create culturally sensitive AI systems that enhance learning while addressing ethical concerns. The findings provide guidance for educators, researchers, and policymakers to ensure equitable and context-aware AI applications in education, benefiting all fields of knowledge.

Keywords

project based learning, Education (General), L7-991, artificial intelligent, AI in Education, Learning Strategy

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold