1. ************************************************
CALL FOR JOURNAL PAPERS
Special Issue on dataTEL
“Datasets and Data Supported Learning in Technology-Enhanced Learning”
International Journal of Technology Enhanced Learning (IJTEL)
ISSN (Online): 1753-5263 - ISSN (Print): 1753-5255
Deadline of submissions: 25 October 2011
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SCOPE
The prospect of great growth of open and linked data in the knowledge society creates
opportunities for new insights through advanced analysis methods based on e.g.,
information extraction, filtering, and retrieval technologies. Educational institutions also
create and own large datasets on their students’ and course activities. The analytic use
of such data, however, is very limited, when considering new educational services,
recommending suitable peers or content or processes or goals, and improving the
personalization of learning. Nevertheless, personalized learning is expected to have the
potential to create more effective learning experiences, and accelerate learners’ time-to-
competence. In the educational world, the literature is sparse on how to build upon
today’s very limited public datasets and how to accommodate the lack of agreed quality
standards on the personalization of learning.
The special issue on dataTEL in IJTEL aims to address this issue by collecting high
value research papers to develop a body of knowledge about data-based
personalization of learning. So far, there is no consensus on algorithms that can be
successfully applied to make reliable analyses of data in a specific learning setting.
Having an initial collection of datasets, coupled with case studies of their use in TEL,
could be a first major step towards a theory of personalisation within TEL that can be
based on empirical experiments with verifiable and valid results.
However, data driven research confronts researchers with a new set of challenges, for
instance, a lack of common dataset formats or policies to share educational datasets, a
huge variety of different evaluation methods for comparing diverse personalization
techniques, and new ethical and privacy issues that arise from the ability to link and
mine information.
Therefore, the objective of this special issue is to explore suitable datasets for TEL –
with a specific focus on recommender and information filtering systems that can take
advantage of these datasets. In this context, new challenges emerge like unclear legal
protection rights and privacy issues, suitable policies and formats to share data, required
pre-processing procedures and rules to create sharable data sets, common evaluation
criteria for recommender systems in TEL and how a data set driven future in TEL could
look like.

2. TOPICS
Relevant topics include, but are not limited to:
- descriptions of datasets that can be used for experimentation
- descriptions of data experiments (methods or results of experiments)
- experiences with those datasets
- dealing with legal protection rights towards datasets on a European level
- privacy preservation for educational datasets
- methods of effective anonymisation of educational datasets
- management and pre-processing procedures for educational datasets
- future scenarios for educational datasets
- impact of educational datasets for learners, teachers, and parents
- mash-ups based on educational datasets
- recommender approaches that are based on educational data
- evaluation methodologies and metrics for educational recommender systems
SPECIAL ISSUE CO-EDITORS
Hendrik Drachsler, Open University, The Netherlands
Katrien Verbert, K.U. Leuven, Belgium
Miguel-Angel Sicilia, University of Alcalá, Spain
Nikos Manouselis, Agro-Know Technologies, Greece
Stefanie Lindstaedt, KnowCenter, Austria
Martin Wolpers, Fraunhofer Institute for Applied Information Technology, Germany
Riina Vuorikari, European Schoolnet, Belgium
SUBMISSIONS
Authors are invited to submit original unpublished research as papers. All submitted
papers will be peer-reviewed by at least two members of the program committee for
originality, significance, clarity, and quality. In addition, the authors are asked to
contribute short abstracts of their submissions to the dataTEL group space at
TELeurope.
Submission will be available through the EasyChair submission system:
http://www.easychair.org/conferences/?conf=datatel2011
Details of the journal, manuscript preparation are available on the here:
http://www.inderscience.com/www/authorguide.pdf
Any questions and submissions should be sent to: hendrik.drachsler@ou.nl

3. REVIEW COMMITTEE (to be confirmed)
Erik Duval, K.U. Leuven, Belgium
Seda Gurses, K.U. Leuven, Belgium
Abelardo Pardo, University Carlos III of Madrid, Spain
Julià Minguillón, Open University of Catalonia, Spain
Olga Santos, aDeNu, Spanish National University for Distance Education, Spain
Julien Broisin, Université Paul Sabatier, France
Christoph Rensing, TU Darmstadt, Germany
Shlomo Berkovsky, CSIRO, Australia
John Stamper, Datashop, Pittsburgh Science of Learning Center, USA
Eelco Herder, Forschungszentrum L3S, Germany
Martin Memmel, DFKI, Germany
Xavier Ochoa, Escuela Superior Politécnica del Litoral, Ecuador
Fridolin Wild, KMI, Open University, UK
Wolfgang Reinhardt, University of Paderborn, Germany
Wolfgang Greller, Open Universiteit, The Netherlands
Marco Kalz, Open Universiteit, The Netherlands
Adriana Berlanga, Open Universiteit, The Netherlands
Peter Sloep, Open Universiteit, The Netherlands
Ralf Klamma, RWTH Aachen, Germany
Pythagoras Karampiperis, NCSR Demokritos, Greece
Giannis Stoitsis, IEEE, Greece
IMPORTANT DATES
Submission of manuscripts: 25 October 2011
Completion of first review: 30 November 2011
Submission of revised manuscripts: 15 January 2011
Final decision notification: 10 February 2012
Publication date (tentative): February 2012
SUBMISSION GUIDELINES
The manuscripts should be original, unpublished, and not in consideration for publication
elsewhere at the time of submission to the International Journal on Technology-
Enhanced Learning and during the review process.
Please carefully follow the author guidelines at
http://www.inderscience.com/mapper.php?id=31 while preparing your manuscript. To
get familiarity with the style of the journal, please see a previous issue at
http://www.inderscience.com/browse/index.php?journalID=246
All manuscripts will be subject to the usual high standards of peer review. Each paper
will undergo double blind review.