EDM 2018 - 11th International Conference on Educational Data Mining – EDM 2018

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.
Topics of interest
Topics of interest to the conference include, but are not limited to.
Deriving representations of domain knowledge from data.
Detecting and addressing students’ affective and emotional states.
Informing data mining research with educational theory.
Contributing to theories of learning through data mining.
Data mining to understand how learners interact with emerging genres of pedagogical environments such as educational games, MOOCs, and exploratory learning environments.
Analyzing multimodal and sensor data.
Using data mining methods to provide support for teachers, parents and policy makers.
Bridging data mining and learning sciences.
Adapting state-of-the-art data mining approaches to the educational domain.
Building an understanding of social and collaborative learning processes through data mining.
Developing generic frameworks, techniques, research methods, and approaches for educational data mining.
Closing the loop between education data research and educational outcomes.
Automatically assessing student knowledge.
Evaluating the efficacy of curriculum and interventions