March 23, 2011 by Hendrik Drachsler
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We finalized the schedule for the dataTEL workshop at ARV2011. In this posting you can find further information about the workshop that is organized by the dataTEL Theme Team.
First of all, we are glad to annouce that we will have two keynote speakers related to the dataTEL topics: Shlomo Berkovsky (AU) and John Stamper (USA).
Shlomo Berkovsky is a Senior Research Scientist and Research Team Leader at the TLI project (CSIRO – Commonwealth Scientific and Industrial Research Organisation, Tasmanian ICT Centre). The project aims to provide individual users and their families with a personalized dietary and health information to help them to maintain a healthier lifestyle.
His research interests include user modeling and personalization. In particular, he is interested in recommender systems, collaborative and content-based filtering, mediation of user models, ubiquitous user modeling, context-aware personalization, personalized content generation, and use of machine learning and data mining techniques in user modeling and personalization.
Before joining CSIRO, he was a post-doctoral research fellow at the University of Melbourne. He graduated at the University of Haifa. The topic of my PhD was “Mediation of user models for enhanced personalization in recommender systems”.
John Stamper is the Technical Director of the Pittsburgh Science of Learning Center DataShop. He is also a member of the research faculty at the Human-Computer Interaction Institute at Carnegie Mellon University. His primary areas of research include Educational Data Mining and Intelligent Tutoring Systems. John received his PhD in Information Technology from the University of North Carolina at Charlotte, holds an MBA from the University of Cincinnati, and a BS in Systems Analysis from Miami University. Prior to returning to academia, John spent over ten years in the software industry. John is a Microsoft Certified Systems Engineer (MCSE) and a Microsoft Certified Database Administrator (MCDBA). John was the co-chair of the 2010 KDD Cup Competition, titled “Educational Data Mining Challenge,” which centered on improving assessment of student learning via data mining.
On the 1st day Shlomo Berkovsky will give a keynote on:
Setting Up a Data Contest
Abstract: Research contests have attracted attention in many areas, mainly due to their potential to boost research on a specific problem. Contests also facilitate a fair and objective evaluation means, as all the participants share the same data and task. This talk will focus on the details of organizing a research contest. Initially, we will overview several past contests: KDD Cup competition series, Netflix prize competition, and CAMRa challenge on context-aware recommendations. Then, we will discuss the essential components of a successful contest: selection of appropriate tasks, data processing and preparation, publicity and attraction of participants, and the logistics of carrying out the contest. Finally, we will spark the discussion on the upcoming I-KNOW dataTEL contest on predicting the performance of students with an intelligent tutoring system.
On the 2nd day John Stamper will give his keynote on:
DataShop: An Educational Data Mining Platform for the Learning Science Community
In this talk I will discuss my vision of creating a true platform for conducting educational data mining research. The talk will focus on DataShop, part of the Pittsburgh Science of Learning Center, which is an open data repository and set of associated visualization and analysis tools. DataShop has data from thousands of students deriving from interactions with on-line course materials and intelligent tutoring systems. The data is fine-grained, with student actions recorded roughly every 20 seconds, and it is longitudinal, spanning semester or yearlong courses. As of February 2011, over 245 datasets are stored including over 51 million student actions which equates to over 150,000 student hours of data. Most student actions are “coded” meaning they are not only graded as correct or incorrect, but are categorized in terms of the hypothesized competencies or knowledge components needed to perform that action. I plan to open the talk up as an interactive discussion in order
to answer questions related to some of the key issues we faced in developing an open data repository, including security, privacy, and data diversity.
Feel free to go to http:/
Based on the contributions of our participants we identified the following 4 most pressing topics of the workshop:
1. Topic: Evaluation of recommender systems in TEL
2. Topic: Data supported learning examples
3. Topic: Datasets from Learning Object Repositories and Web content
4. Topic: Privacy and data protection for dataTEL
The workshop schedule is available in the dataTEL space you can find it here: http:/
We will tweet about the event and you are free to send you remarks by using the hashtag #datatel11.
