EDM 2013 invites papers that study how to apply data mining to analyze data generated by various information systems supporting learning or education (in schools, colleges, universities, and other academic or professional learning institutions providing traditional and modern forms and means of teaching, as well as informal learning). EDM may require adaptation of existing or development of new approaches that build upon techniques from a combination of areas, including but not limited to statistics, psychometrics, machine learning, information retrieval, recommender systems and scientific computing.

Topics of Interest

We welcome papers describing original work. Areas of interest include but are not limited to:

• Generic frameworks, methods and approached for EDM
• Learner or student modeling
• Mining assessment data
• Mining browsing or interaction data
• Mining the results of educational research (e.g. A/B tests)
• Educational process mining
• Data-driven adaptation and personalization
• Improving educational software
• Evaluating teaching interventions
• Emotion, affect, and choice
• Integrating data mining and pedagogical theory
• Improving teacher support
• Replication studies
• Best practices for adaptation of data mining, information retrieval, recommender system, opinion mining, and question answering techniques to educational context