Akademik Veri Yönetim Sistemi
EDUCATION AND INFORMATION TECHNOLOGIES, cilt.29, sa.7, ss.8961-8985, 2024 (SSCI)
Educational Data Mining (EDM) is an interdisciplinary field that encapsulates different fields such as computer science, education, and statistics. It is crucial to make data mining in education to shape future trends in education for policymakers, researchers, and educators in terms of developments. To have an all-inclusive understanding of EDM studies, a comprehensive examination of both the intellectual and social structure of the field with a global perspective and its evolution over time is required to provide adequate comprehension of the past, present, and as well future research direction for this research field. In this respect, this research study aims to explore the performance analysis of the EDM, the intellectual structure of the EDM, the social structure of the area, and the temporal modeling of the EDM through bibliometric analysis. In this bibliometric analysis, the existing body of knowledge that covered 2010-2021 was presented on educational data mining to provide future directions in the field of education. The results of the study showed the number of publications increased by 1325% (8 to 114) over the years. It has been determined that the most influential journals in the field are "Computers & Education", "International Journal of Advanced Computer Science and Applications" and "Educational Technology & Society" and the most influential authors are "C. Romero", "S. Ventura" and "R.S. Barker", and the USA, Spain, and China seem to be the most influential countries in the field of EDM. The themes of "CLASSIFICATION" and "SYSTEMS" in the first sub-period (2010-2013) of EDM, and "LEARNING ANALYTICS", "PREDICTION OF ACADEMIC PERFORMANCE" and "SOCIAL MEDIA" in the second sub-term (2014-2017) and the third and last sub-period (2018-2021), "PREDICTION OF ACADEMIC PERFORMANCE", "MACHINE LEARNING", "PROCESS MINING", "PARTICIPATION", "KNN", "J48" and "BAYESIAN NETWORK" themes were identified as engine themes. In addition, as a result of the thematic evolution map, it was discovered that the themes "DEEP-LEARNING (DL)" and "EMOTION" are emerging themes for future studies for shaping the future of education based on sustainable goals.