[edm-announce] Educational Data Mining 2009, Call for papers
- From: "Ryan S.J.d. Baker" <ryan@xxxxxxxxxxxxxxxxxxxxxxxxx>
- To: edm-announce@xxxxxxxxxxxxx
- Date: Tue, 20 Jan 2009 10:35:28 -0500
<from Tiffany Barnes>
Please forward to your colleagues! The submissions site will be open within
a week.
EDUCATIONAL DATA MINING 2009 (EDM 2009)
CALL FOR PAPERS
July 1-3, 2009, Córdoba, Spain
http://www.educationaldatamining.org/EDM2009/
IMPORTANT DATES
Paper submission: March 31, 2009
Acceptance notification: May 1, 2009
Camera ready paper: May 20, 2009
Conference: July 1-3, 2009
OVERVIEW
The Second 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?
- 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?
- Domain representation. How do learners represent the domain? Does
this representation shift as a result of instruction? Do different
subpopulations represent the domain differently?
- 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.
SUBMISSION TYPES
All submissions should follow the formatting guidelins (MS Word, PDF).
There are two types of submission:
1) Full papers - Maximum of 10 pages. Should describe substantial,
unpublished work
2) Young researcher: Maximum of 8 pages. Designed for graduate students
and undergraduates
ONFERENCE ORGANIZATION
Conference Chairs:
Cristobal Romero Morales, University of Cordóba, Spain
Sebastian Ventura, University of Cordóba, Spain
Program Chairs:
Tiffany Barnes, University of North Carolina at Charlotte, USA
Michel Desmarais, Polytechnique Montreal, Canada
Steering Committee:
Esma Aïmeur, University of Montreal, Canada
Ryan Baker, Carnegie Mellon University, USA
Tiffany Barnes, University of North Carolina at Charlotte, USA
Joseph E. Beck, Worcester Polytechnic Institute, USA
Neil Heffernan, Worcester Polytechnic Institute, USA
Brian Junker, Carnegie Mellon University, USA
Kalina Yacef, University of Sydney, Australia
EDM 2008
http://www.educationaldatamining.org/EDM2008/index.php?page=proceedings
--
Tiffany Barnes
Assistant Professor
Computer Science
UNC Charlotte
Other related posts:
- » [edm-announce] Educational Data Mining 2009, Call for papers - Ryan S.J.d. Baker