[ACT-R-users] Educational Datamining 2010 call for papers

[Philip Pavlik]

Apologies for cross postings....

 

EDM2010

http://www.educationaldatamining.org/EDM2010

 

The Third International Conference on Educational Data Mining

 

Pittsburgh, PA USA

June 11-13, 2010

 

Call for Papers

 

The Third International Conference on Educational Data Mining brings together

researchers from computer science, education, psychology, psychometrics, and

statistics to analyze large data sets to answer educational research

questions. The increase in instrumented educational software, as well as state

databases of student test scores, has created large repositories of data

reflecting how students learn. The EDM conference focuses on computational

approaches for using those data to address important educational questions.

The broad collection of research disciplines ensures cross fertilization of

ideas, with the central questions of educational research serving as a

unifying focus. This Conference emerges from preceding EDM workshops at the

AAAI, AIED, ICALT, ITS, and UM conferences.

 

Topics of Interest

 

We welcome papers describing original work. Areas of interest include but are

not limited to:

 

   * Improving educational software. Many large educational data sets are

generated by computer software. Can we use our discoveries to improve the

software's effectiveness?

   * Domain representation. How do learners represent the domain? Does this

representation shift as a result of instruction? Do different subpopulations

represent the domain differently?

   * Evaluating teaching interventions. Student learning data provides a

powerful mechanism for determining which teaching actions are successful. How

can we best use such data?

   * Emotion, affect, and choice. The student's level of

interest and

willingness to be a partner in the educational process is critical. Can we

detect when students are bored and uninterested? What other affective states

or student choices should we track?

   * Integrating data mining and pedagogical theory. Data mining typically

involves searching a large space of models. Can we use existing educational

and psychological knowledge to better focus our search?

   * Improving teacher support. What types of assessment information would

help teachers? What types of instructional suggestions are both feasible to

generate and would be welcomed by teachers?

   * Replication studies. We are especially interested in papers that apply a

previously used technique to a new domain, or that reanalyze an existing data

set with a new technique.

   * Best practices for adaptation of data mining techniques to EDM. We are

especially interested in papers that present best practices or methods for the

adaptation of techniques from data mining and other relevant literatures to

the specific needs of analysis of educational data.

 

Important Dates

 

   * Paper submission: March 10, 2010 (23:59:59 EST), no extension

   * Acceptance notification: April 21, 2010

   * Poster abstract submission: April 28, 2010 (23:59:59 EST)

   * Poster notification: May 3, 2010

   * Camera ready papers, posters: May 19, 2010

   * Conference: June 11-13, 2010

 

Submission Types

 

All submissions should follow the formatting guidelines (MS Word, PDF). There

are three types of submission:

 

   * Full papers: Maximum of 10 pages. Should describe substantial, unpublished work

   * Young researchers: Maximum of 8 pages. Designed for graduate students and undergraduates

   * Poster abstracts: Maximum of 2 pages

 

Conference Organization

 

   * Conference Chair: Ryan S.J.d. Baker, Worcester Polytechnic Institute

   * Program Chairs: Agathe Merceron, Beuth University of Applied Sciences Berlin

                     Philip I. Pavlik Jr., Carnegie Mellon University

   * Local Organizing Chair: John Stamper, Carnegie Mellon University

   * Web Chair: Arnon Hershkovitz, Tel Aviv University

 

Program Committee

 

Esma Aimeur, University of Montreal, Canada

Beth Ayers, Carnegie Mellon University, USA

Ryan Baker, Worcester Polytechnic Institute, USA

Tiffany Barnes, University of North Carolina at Charlotte, USA

Joseph Beck, Worcester Polytechnic Institute, USA

Bettina Berendt,  Katholieke Universiteit Leuven , Belgium

Gautam Biswas, Vanderbilt University, USA

Cristophe Choquet, Université du Maine, France

Cristina Conati, University of British Columbia, Canada

Richard Cox, University of Sussex, UK

Michel Desmarais, Ecole Polytechnique de Montreal, Canada

Aude Dufresne, University of Montreal, Canada

Mingyu Feng, Worcester Polytechnic Institute, USA

Art Graesser, Universisty of Memphis, USA

Andreas Harrer, Katholische Universität Eichstätt-Ingolstadt, Germany

Neil Heffernan, Worcester Polytechnic Institute, USA

Arnon Hershkovitz, Tel Aviv University, Israel

Cecily Hiener, University of Utah, USA

Roland Hubscher, Bentley University, USA

Sebastian Iksal, Université du Maine, France

Kenneth Koedinger, Carnegie Mellon University, USA

Vanda Luengo, Université Joseph Fourier Grenoble, France

Tara Madhyastha, University of Washington, USA

Brent Martin, Canterbury University, New Zealand

Noboru Matsuda, Carnegie Mellon University, USA

Manolis Mavrikis, The University of Edinburgh, UK

Gordon McCalla, Univerisity of Saskatchewan, Canada

Bruce McLaren, Deutsches Forschungszentrum für Künstliche Intelligenz,Germany

Julia Mingullon Alfonso, Universitat Oberta de Catalunya, Spain

Tanja Mitrovic, Canterbury University, New Zealand

Jack Mostow, Carnegie Mellon University, USA

Rafi Nachmias, Tel Aviv University, Israel

Roger Nkambou, Université du Québec à Montréal (UQAM), Canada

Mykola Pechenizkiy, Eindhoven University of Technology, Netherlands

Steve Ritter, Carnegie Learning, USA

Cristobal Romero, Cordoba University, Spain

Carolyn Rose, Carnegie Mellon University, USA

Steven Tanimoto, University of Washington, USA

Sebastian Ventura, Cordoba University, Spain

Kalina Yacef, University of Sydney, Australia

Osmar Zaiane, University of Alberta, Canada

 

 

 

 

 

 

 

Philip I. Pavlik Jr.

Human Computer Interaction Institute

Carnegie Mellon University

Pittsburgh, PA 15213 

 

ppavlik at andrew.cmu.edu <mailto:ppavlik at andrew.cmu.edu> 

http://optimallearning.org/ <http://optimallearning.org/> 

 

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