G-EDM 2014 - The first International Workshop on: Graph-based Educational Datamining (G-EDM)

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.