Industry panel: The Future of Practical Applications of EDM at Scale
Sunday, June 28, 9:00 – 10:10
- Bror Saxberg, Kaplan Inc.
- Ryan Baker, Teachers College, Columbia University;
- John Carney, Carney Labs LLC;
- Piotr Mitros, edX;
- John Stamper, CMU and PSLC DataShop.
Abstract: This mixed panel of different professionals working in EDM will be a conversation about increasing the connection between research and real-world applications. What's going on now to scale techniques for use "out there" in the field? What should researchers, funders, regulators, publishers, trainers, schools/universities and others be doing to get ready for practical work? What's in the way that we can usefully start work to address? We'll ask the audience to engage in this conversation as well - what's in your way to moving work from research environments to practically help learners at scale - and to generate more useable data at scale?
Panel: Ethics and Privacy in EDM
Sunday, June 28, 13:30 – 14:30
- Taylor Martin, National Science Foundation
- Dragan Gasevic, University of Edinburgh
- Zach Pardos, UC Berkeley;
- Mykola Pechenizkiy, TU Eindhoven;
- John Stamper, Carnegie Mellon University and Pittsburgh Science of Learning Center DataShop;
- Osmar Zaiane; University of Alberta.
Abstract: Educational data mining is inherently falls into the category of the so-called secondary data analysis. It is common that data that have been collected for administrative or some other purposes at some point is considered as valuable for other (research) purpose. Collection of the student generated, student behavior and student performance related data on a massive scale in MOOCs, ITSs, LMS and other learning platforms raises various ethical and privacy concerns among researches, policy makers and the general public.This panel is aimed to discuss major challenges in ethics and privacy in EDM and how they are addressed now or should be addressed in the future to prevent any possible harm to the learners. Several experts are invited to discuss the potential and challenges of privacy-preserving EDM, ethics-aware predictive learning analytics, and availability of public benchmark datasets for EDM among others.
Panel: Grand Challenges for EDM and Related Research Areas
Monday, June 29, 10:30 – 12:10
- Ryan Baker, Teachers College, Columbia University
- Peter Brusilovsky (UM Inc), School of Information Sciences, Pittsburgh University
- Dragan Gasevic (SoLAR), Schools of Education and Informatics, University of Edinburgh
- Neil T. Heffernan (AIED), Department of Computer Science, Worcester Polytechnic Institute
- Mykola Pechenizkiy (IEDMS), Department of Computer Science, TU Eindhoven
- Alyssa Wise (ISLS), Faculty of Education, Simon Fraser University
Abstract: Educational data mining (EDM) and Learning analytics are still rather young research areas. The goal of this panel is to share different views on what major challenges researches need to address in EDM, learning analytics and related research areas including but not limited to User modeling, AI in Education, and Learning Sciences. The representatives of the corresponding communities are invited to discuss what grand challenges we should aim to address for the next five years, and which of these challenges are old and which are new, which of them peculiar to one distinct research area and which of them are shared across two or more research areas.