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Improving Learning Outcomes for All Learners
Educational Data Mining is a leading international forum for high-quality research that mines datasets to answer educational research questions, including exploring how people learn and how they teach. These data may originate from a variety of learning contexts, including learning and information management systems, interactive learning environments, intelligent tutoring systems, educational games, and data-rich learning activities. Educational data mining considers a wide variety of types of data, including but not limited to raw log files, student-produced artifacts, discourse, multimodal streams such as eye-tracking and other sensor data, and additional databases of student information. The overarching goal of the Educational Data Mining research community is to support learners and teachers more effectively, by developing data-driven understandings of the learning and teaching processes in a wide variety of contexts and for diverse learners.
The theme of this year’s conference is “Improving Learning Outcomes for All Learners”. The theme comprises two parts: (1) Identifying actionable learning or teaching strategies that can be used to improve learning outcomes. (2) Using EDM to promoting more equitable learning across diverse groups of learners. For this 13th iteration of the conference we specifically welcome research that advances aforementioned areas.