<![CDATA[This study aims to examine the evolution of data collection techniques in educational management research through a systematic review of literature published over the past two decades. The study adopts a literature review design by analyzing scholarly articles, books, and research reports accessed through major academic databases such as Scopus, ERIC, and Google Scholar. The findings reveal a significant shift from traditional techniques such as interviews and manual observation to modern, technology-based approaches such as learning analytics, big data, and the use of social media as alternative data sources. Moreover, the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is increasingly applied in educational management systems to support more accurate and responsive decision-making. The implications of this research suggest that educational practitioners and researchers must adopt more dynamic and context-aware data collection strategies to effectively address the complexities of today's educational systems. This study presents original value by chronologically mapping the trends in data collection techniques and highlighting the gap between conventional educational management practices and current technological advancements. Therefore, this review contributes significantly to the literature by providing a conceptual and methodological framework that can inform future research and policy development in educational management.]]>
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