№ files_lp_4_process_1_48726
Academic overview of the research field of educational data mining describing its origins, data sources, analytical techniques, and applications in studying learning processes within computer-based educational systems.
Academic field: Educational Data Mining
Related disciplines: Data Mining; Machine Learning; Psychometrics; Text Mining; Web Log Analysis
Thematic area: Technology-Enhanced Learning
Type of document: Academic reference text / encyclopedia-style overview
Authors: Oliver Scheuer; Bruce M. McLaren
Author affiliations: German Research Center for Artificial Intelligence (DFKI); Carnegie Mellon University
Institutions location: Saarbrücken, Germany; Pittsburgh, PA, United States
Research focus: Analysis of large-scale educational data from computer-based learning environments
Key concepts: student modeling; Bayesian Knowledge Tracing; diagnostic modeling; domain modeling; learning analytics
Data sources described: system interaction logs, quizzes and exercises, collaborative chat data, administrative records, demographic information, physiological sensor data
Analytical methods referenced: data preprocessing, pattern detection, probabilistic modeling, validation of results
Relevant conferences: International Conference on Educational Data Mining; Artificial Intelligence in Education (AIED); Intelligent Tutoring Systems (ITS); User Modeling, Adaptation, and Personalization (UMAP)
Related publication: Journal of Educational Data Mining (JEDM)
Historical development: emergence of EDM as a scientific field around 2008–2009 through dedicated conferences and journal publications
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