Artificial Intelligence for Learning in Indonesia: Current Research Trends and School Implementation
DOI:
https://doi.org/10.61166/elm.v3i2.103Keywords:
Artificial Intelligence, Education Technology, Bibliometric Analysis, Keyword Clustering, Indonesia.Abstract
This study aims to analyze trends and developments in research on Artificial Intelligence for learning in Indonesia. The method used is bibliometric analysis with specific keywords that resulted in 120 research documents. Data analysis was conducted using the VOSviewer application to map keyword clusters and research novelty. The analysis concludes that research on Artificial Intelligence for Learning in Indonesia is divided into four main clusters representing different thematic focuses, including digital technology utilization, cognitive skill development, academic data governance, and instructional integration with performance analysis. The first cluster emphasizes the role of technology in enhancing user engagement, while the second cluster focuses on automation and the development of twenty-first century skills. The third cluster highlights the importance of data management and administrative efficiency, whereas the fourth cluster stresses technology integration in instructional processes and learning evaluation. Furthermore, the novelty analysis indicates that yellow-colored keywords such as “Elementary School”, “Local Wisdom”, and “Motivation” serve as indicators of recent research trends. These findings suggest a shift in research focus toward primary education contexts, the integration of local cultural values, and affective aspects in technology-based instruction.
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