EXPLORING BIBLIOSHINY FOR MAPPING  ARTIFICIAL INTELLIGENCE RESEARCH IN EDUCATION

Hanifah Indah Rahmawati; Zenita Sabitri; Mutiara Nabila Azmi; Danny Meirawan

doi:10.21009/jpensil.v14i2.54083

Authors

Hanifah Indah Rahmawati Building Engineering Education, Faculty of Technology and Industrial Education, Indonesia University of Education
Zenita Sabitri Building Engineering Education, Faculty of Technology and Industrial Education, Indonesia University of Education
Mutiara Nabila Azmi Building Engineering Education, Faculty of Technology and Industrial Education, Indonesia University of Education
Danny Meirawan Building Engineering Education, Faculty of Technology and Industrial Education, Indonesia University of Education

DOI:

https://doi.org/10.21009/jpensil.v14i2.54083

Keywords:

Artificial Intelligence, Bibliometrics, Biblioshiny, Education, Research Trends

Abstract

This study critically analyzes the development of artificial intelligence (AI) research in education using a bibliometric approach, leveraging data from 191 Scopus-indexed documents during the 2015-2024 period. Employing Biblioshiny software, the study identifies an annual publication growth rate of 44.22% and an average of 11.88 citations per document. The analysis maps five key clusters: AI-based adaptive learning, automated assessment systems, predictive learning analytics, intelligent pedagogical agents, and personalized learning content. Dominant contributions are observed from countries such as the United States, China, and India, supported by substantial international collaboration. The findings also highlight dominant keywords like "Artificial Intelligence" and "Education Technology," reflecting a global research focus. While emphasizing AI's strategic potential in transforming education systems, this study critically underscores ethical and data privacy challenges that require further attention in advancing educational technology.

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