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UMUAI
Special Issue on Data Mining for Personalized Educational Systems |
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Guest Editors:
Dr. Cristóbal Romero, Department of Computer Sciences and Numerical
Analysis, University of Córdoba, Córdoba, Spain. (cromero@uco.es), http://www.uco.es/~in1romoc/
Dr. Sebastián Ventura, Department
of Computer Sciences and Numerical Analysis, University of Córdoba, Córdoba,
Spain. (sventura@uco.es), http://www.uco.es/users/sventura/en/
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:
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Analysis
and visualization of student interactions.
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Applying
recommender system in educational environments.
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Prediction
of performance and marks.
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Applying
sequence mining in educational data.
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User
modeling using data mining.
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Applying
text mining in educational data.
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Improving
educational software.
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Detecting
outliers, cheating, gaming, errors, misuse, gifted, etc.
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Detecting
motivation, affective, behavior, learning styles, etc.
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Improving
teacher support and feedback.
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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
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Submission of Title and Abstract: March 1,
2010
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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.