Graph-based Educational Datamining (G-EDM)

http://www.cs.pitt.edu/~collinl/G-EDM/

Held in Conjunction with the 7th International
Conference on Educational Datamining
July 4th - 7th 2014.


Graph data has become increasingly prevalent in data-mining and data
analysis. Many types of data can be represented naturally as graphs
including social network data, log traversal, and online discussions.
Recent work on peer tutoring, online resource use, and argumentation has
highlighted educationally relevant data that lends itself to graphical
analysis including:

* Graphical solution representations such as argument diagrams;
* Graph-based models of problem-solving processes;
* Student traversal of shared resources in online textbooks or MOOCs;
* Sub-communities of learners within larger courses such as study
groups;
* Peer tutors and collaborative groups such as project teams; and
* Class assignments within a larger knowledge space.

While this type of educational data has grown increasingly common it has
only recently been approached by the EDM community and no strong community
of educational graph researchers has developed to share common problems,
tools, and techniques. In our view developing such a community is
essential to support educational datamining in this area. Our intended
audience includes academic and industry researchers who have graphical
data and are seeking advice or analytical tools and interested tool
developers and theoreticians who seek substantive problems.

This workshop will foster a shared community by providing a forum to
discuss ongoing work, share lessons learned, and to identify common
challenges. The workshop will be structured as a mini-conference with
time set aside for paper presentations, demos, and meetings to discuss
future avenues of research. We will consider submissions of full and
short papers as well as posters and demos covering a range of graphical
topics above including:

* Social network data.
* Graphical solution representations.
* Graphical behavior models.
* Graph-based log analysis.
* Large network datasets.
* Novel graph-based machine learning methods.
* Novel graph analysis techniques.
* Relevant analytical tools and standard problems.
* Issues with graph models.


Sincerely:
Dr. Collin Lynch, & Dr. Tiffany Barnes.


--------- Paper Formats ----------------
We particularly welcome submission of in-progress work both from students
and researchers with problems who are seeking appropriate analytical
tools, and developers of graph analysis tools who are seeking new
challenges. We will accept both short and long-papers. The papers will
be hosted online at the workshop website and at http://ceur-ws.org/.

Short papers should be from 3 to 5 pages long and describe planned
research; existing datasets that would be amenable to graphical analysis;
or analytical tools that are available for use.

Long papers should be from describe mature work and be from 6-8 pages
long.

Papers should be submitted in the EDM 2014 latex and word formats:
http://educationaldatamining.org/EDM2014/index.php?page=submission



--------- Organization -----------------
The workshop will be organized as a mini-conference with time set aside
for short presentations, collaborative discussion, and demos. More
information on the presentation formats will be made available once the
final submissions are selected.



--------- Important Dates --------------

14 April 2014 - Submissions Due.
12 May 2014 - Acceptance notification.
4 July 2014 - Tentative Workshop Date.