CFP: Special Issue of the Journal of Educational Data Mining

CFP: Special Issue of the Journal of Educational Data Mining

EDUCATIONAL DATA MINING ON VATION, META-COGNITION, AND SELF-REGULATED LEARNING

Guest Editors:

Ryan S.J.d. Baker, Worcester Polytechnic Institute (rsbaker@wpi.edu)
Philip H. Winne, Simon Fraser University (winne@sfu.ca)

Aim of Special Issue

We invite paper submissions for a special issue of the peer-reviewed Journal of Educational Data Mining that focuses on using educational data mining methods to advance basic and applied research on the nature and roles of motivation, meta-cognition, and self-regulated learning (SRL) in learning sciences. Increasingly, it is acknowledged that SRL processes interact in key fashions with motivational and meta-cognitive processes. We seek papers that use EDM to explore these interactions, as well as papers that explore any of these three areas in isolation or in relation to other important processes and constructs.

Papers should apply accepted or novel educational data mining methods in rigorous, demonstrably valid ways to study these topics. We are interested to assemble a collection of articles that explore how new methods for measurement and analysis that EDM affords enable new discoveries in these areas.

Because an important goal of this special issue is to educate researchers who are not familiar with the power and benefits of data mining, papers should be written in a style that is simultaneously meaningful to experts in data mining, and educational for those who are entirely new to these methods. Data can
be drawn from any educational source (e.g. interaction logs, questionnaire instruments, field observations, video or text replays, collaborative chats, discussion forums) so long as it supports valid inference; simulated data is not admissible for this special issue.

All papers must make a contribution to research in the domain studied and must give full detail on the educational data mining methods used
to derive these contributions; it is not necessary, however, that a paper make innovations in educational data mining methods although these are, of course, welcome (so long as they are valid).

Review Process

As stipulated by JEDM reviewing guidelines, each submission will be peer-reviewed by three colleagues in the field, including both members of the JEDM editorial board plus reviewers chosen specifically for this issue.

Submission Guidelines

We invite submissions of any length; see the JEDM submission guidelines. All submissions can be made electronically via email to
Ryan S.J.d. Baker (rsbaker@wpi.edu).

Deadlines

Please submit your manuscript by December 1, 2011. We plan a review cycle of approximately three months so that you should receive feedback and a decision by approximately March 1, 2012.

Please direct questions to the guest editors at rsbaker@wpi.edu and winne@sfu.ca.

Image courtesy of https://secure.flickr.com/photos/franganillo/3676227162/in/photostream/

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