EDM 2010 - Special Issue on Data Mining for Personalized Educational Systems

UMUAI Special Issue on Data Mining for Personalized Educational Systems

Guest Editors:

Dr. Cristóbal Romero, Department of Computer Sciences and Numerical Analysis, University of Córdoba, Córdoba, Spain. (cromero-AT-uco.es), http://www.uco.es/~in1romoc/

Dr. Sebastián Ventura, Department of Computer Sciences and Numerical Analysis, University of Córdoba, Córdoba, Spain. (sventura-AT-uco.es), http://www.uco.es/~ma1vesos/



Scope of the Special Issue:

Educational data mining (EDM) is an emerging discipline, concerned with developing methods for exploring the unique types of data that can be gathered in an educational context The increase in instrumented educational software and in databases of student test scores has created large data repositories reflecting how students learn. EDM focuses on computational approaches for using those data to address important educational questions.

One focus of EDM consists in improving personalized educational systems, which is the topic of this special issue.

EDM can enhance the effectiveness, personalization and/or adaptivity of such learning environments. In turn, student data coming from personalized systems are semantically richer than data from traditional web-based education system, and can lead to deeper diagnostic analysis.

Contributions to this special issue are particularly welcome in, but not limited to, the following topics related to Data Mining for Personalized Educational Systems:

Analysis and visualization of student interactions.
Applying recommender system in educational environments.
Prediction of performance and marks.
Applying sequence mining in educational data.
User modeling using data mining.
Applying text mining in educational data.
Improving educational software.
Detecting outliers, cheating, gaming, errors, misuse, gifted, etc.
Detecting motivation, affective, behavior, learning styles, etc.
Improving teacher support and feedback.
Test item analysis.


How to submit:



Submissions to the special issue should follow the UMUAI formatting guidelines and submission instructions available at:

http://www.umuai.org/paper_submission.html



Each submission should note that it is intended for the Special Issue on Data Mining for Personalized Educational Systems. Potential authors are asked to submit a tentative title and short abstract (which can be altered for the actual submission) to assist in the assessment of suitability for the special issue and in the formation of a panel of appropriate reviewers.



UMUAI is an archival journal that publishes mature and substantiated research results on the (dynamic) adaptation of computer systems to their human users, and the role that a model of the system about the user plays in this context. Many articles in UMUAI are quite comprehensive and describe the results of several years of work. Consequently, UMUAI gives "unlimited" space to authors (so long as what they write is important). Authors whose paper exceeds 40 pages in journal format (including illustrations and references) are however requested to supply a short justification upon submission that explains why a briefer discussion of their research results would not be advisable.



Important Dates:

Notification of Intent to Submit: as soon as possible
Submission of Title and Abstract: March 1, 2010
Manuscript Submission: April 16, 2010


Review Process:

Submissions will undergo the normal review process, and will be reviewed by three established researchers selected from a panel of reviewers formed for the special issue. Barring unforeseen problems, authors can expect to be notified regarding the review results within three months of submission.