EDM 2019
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| EDM 2019 | |
|---|---|
12th International Conference on Educational Data Mining
| |
| Event in series | EDM |
| Dates | 2019/07/02 (iCal) - 2019/07/05 |
| Homepage: | http://educationaldatamining.org/edm2019/ |
| Twitter account: | @EDM2019MTL |
| Submitting link: | https://easychair.org/conferences/?conf=edm2019 |
| Location | |
| Location: | Montreal, Quebec, Canada |
| Important dates | |
| Papers: | 2019/03/04 |
| Submissions: | 2019/03/04 |
| Notification: | 2019/04/11 |
| Camera ready due: | 2019/05/01 |
| Papers: | Submitted 185 / Accepted 64 (34.6 %) |
| Committees | |
| General chairs: | Michel Desmarais, Roger Nkambou |
| PC chairs: | Collin Lynch, Agathe Merceron |
| Workshop chairs: | Luc Paquette, Cristobol Romero |
| PC members: | Akram Bita, Giora Alexandron, Anne Boyer, Mirjam AugsteinProperty "Has PC member" (as page type) with input value "Mirjam Augstein" contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process., Costin BadicaProperty "Has PC member" (as page type) with input value "Costin Badica" contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process. |
| Keynote speaker: | Mike Mozer, Steve Ritter, Julita Vassileva |
| Table of Contents | |
| Tweets by @EDM2019MTL | |
Event
Topics
Topics of interest to the conference include but are not limited to.
- Modeling student and group interaction for guidance and collaborative problem-solving.
- Deriving representations of domain knowledge from data.
- Modeling real-world problem-solving in open-ended domains.
- Detecting and addressing students’ affective and emotional states.
- Informing data mining research with educational theory.
- Developing new techniques for mining educational data.
- Data mining to understand how learners interact in formal and informal educational contexts.
- Modeling students’ affective states and engagement with multimodal data.
- Synthesizing rich data to inform students and educators.
- Bridging data mining and learning sciences.
- Applying social network analysis to support student interactions.
- Legal and social policies to govern EDM.
- Developing generic frameworks, techniques, research methods, and approaches for EDM.
- Closing the loop between EDM research and educational outcomes to yield actionable advice.
- Automatically assessing student knowledge.