Documenting the Half-Century Evolution of Islamic Education Research: A Probabilistic Topic Modeling Study of the Literature from 1970 to 2023

Awaludin, Aziz

STUDIA ISLAMIKA
Vol 31, No 3 (2024): Studia Islamika

In this systematic literature review, I used Correlated Topic Modeling (CTM), a machine learning technique, to analyze 1,116 Scopus-indexed documents on Islamic education spanning 54 years (1970-2023). I identified 19 topics grouped into four thematic clusters: Foundational Concepts and Methods, Social Issues, Teaching and Learning, and Education Systems and Settings. My main argument is that Islamic education is inherently interdisciplinary, encompassing history, philosophy, leadership, policy, citizenship, gender, and technology. While some topics, like education history and values education, have seen consistent focus, others, such as citizenship, education policy, and student learning, remain underexplored. My analysis reveals the field’s adaptability to societal and technological changes. Particularly, I discuss the implications for Southeast Asia’s Islamic education, which has balanced modernization and national policies with global trends. By pioneering machine learning applications in this field, this review uncovers new research directions and demonstrates the potential of large-scale text analysis for Islamic education scholarship.