Educational Data Mining is a leading international forum for high-quality research that mines data sets to answer educational research questions that shed light on the learning process. These data sets may originate from a variety of learning contexts, including learning 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. The overarching goal of the Educational Data Mining research community is to better support learners by developing data-driven understandings of the learning process in a wide variety of contexts and for diverse learners.
The theme of this year’s conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks such as writing, design, and collaborative problem-solving. And it has been used in new informal contexts where student actions are at best semi-structured. For this 12th iteration of the conference, we specifically welcome research in these new areas.
Topics of interest to the conference include but are not limited to:
Les contributions sont téléchargeables soit à l'unité, soit regroupées dans un seul document (pdf, 823 p.)