What Do Scopus Index Keywords Reveal About Educational Data Mining Research? A Bibliometric Analysis (2014-2024)

Introduction: Educational Data Mining (EDM) has emerged as a pivotal interdisciplinary field addressing the increasing demand for data-driven educational enhancement. However, a comprehensive understanding of its developmental trajectory is hindered by fragmented literature reviews and a lack of longitudinal analysis spanning critical technological and educational transformations.Objective: This study investigates the evolution of EDM research over the transformative decade from 2014 to 2024 through systematic bibliometric analysis, aiming to identify growth patterns, thematic developments, and methodological innovations.Method: We conducted an extensive analysis of 436 peer-reviewed publications indexed in Scopus, employing rigorous keyword analysis, mathematical modeling of research trends, and systematic thematic classification to examine temporal evolution patterns. The methodology utilized PRISMA-guided selection procedures, standardized keyword extraction and normalization, and quantitative measures including growth ratios, Shannon diversity indices, and thematic strength calculations.Results: Our analysis reveals remarkable research growth, with a 777.8 % increase in publication output, representing a compound annual growth rate of 24.3 %. The findings document a significant paradigmatic shift from descriptive analytics toward predictive methodologies, evidenced by a 215-fold growth in Machine Learning and AI themes and the complete emergence of deep learning applications. Thematic evolution analysis identified 47.3 % of recent keywords as entirely new terms, indicating substantial conceptual expansion.Conclusions: The research demonstrates EDM's transition from foundational exploration (2014-2017) through rapid expansion (2018-2020) to sophisticated maturation (2021-2024), characterized by methodological pluralism and the integration of advanced computational techniques.