[AISWorld] Feb 10 2014 Submission Deadline - CfP: Big Data in Education and Learning Analytics @ ICALT 2014

[Jelena Jovanovic]

*** Apologies for cross posting ***
*Big Data in Education and Learning Analytics*
in conjunction with the 14th IEEE International Conference on Advanced
Learning Technologies - ICALT2014
Athens, Greece, July 7-10, 2014

URL: http://www.ask4research.info/icalt/2014/node/29

Paper Submission Deadline: February 10, 2014
Paper Acceptance Notification: March 17, 2014

Track Description and Topics of Interest

The analysis and discovery of relations between human learning and
contextual factors that influence these relations have been one of the
contemporary and critical global challenges facing researchers in a
number of areas, particularly in Education, Psychology, Sociology,
Information Systems, and Computing. These relations typically concern
learner performance and the effectiveness of the learning context. Be
it the assessment marks distribution in a classroom context or the
mined pattern of best practices in an apprenticeship context, analysis
and discovery have always addressed the elusive causal question about
the need to best serve learners' learning efficiency and the need to
make informed choices on a learning context's instructional
effectiveness. Significant advances have been made in a number of
areas from educational psychology to artificial intelligence in
education, which explored factors contributing to learning efficiency
and instructional effectiveness. With the advent of new technologies
such as eye-tracking, activities monitoring, video analysis, content
analysis, sentiment analysis, social network analysis and interaction
analysis, one could study these factors in a data-intensive fashion.
This very notion is what is currently being explored under big data
learning analytics, which includes related areas such as learning
process analytics, institutional effectiveness, academic analytics,
web analytics and information visualisation. BDELA at ICALT2014 will
explore continuous monitoring of learner progress and traces of skills
development among individual learners across programs and
institutions. It will discuss issues concerning continuous mapping of
institutional learning related achievements to gauge alignment with
strategic plans and alignment of governmental strategies. It will
examine assessment frameworks of academic productivity to continuously
measure impact of teaching. It will discuss concerns such as how
quality of instruction, attrition, and measurement of curricular
outcomes using big data as the premise.

Track Chairs

Jelena Jovanovic, University of Belgrade, Serbia
Vive Kumar, Athabasca University, Canada (vive at athabascau.ca) [Co-ordinator]
Riccardo Mazza, University of Lugano, Switzerland
Abelardo Pardo, University of Sydney, Australia
Miguel-Angel Sicilia, University of Alcala, Spain

Members of Track Program Committee

Jelena Jovanovic, University of Belgrade, Serbia
Vive Kumar, Athabasca University, Canada,
Riccardo Mazza, University of Lugano, Switzerland
Abelardo Pardo, University of Sydney, Australia
Miguel-Angel Sicilia, University of Alcala, Spain
Mark Brown, Massey University, New Zealand
Shane Dawson	, University of South Australia, Australia
Michael Derntl, RWTH Aachen University, Germany
Stefan Dietze, L3S Research Center, Germany
Alfred Essa, McGraw-Hill Education, USA
Dragan Gasevic, Athabasca University, Canada (Invited)
Alejandra Martinez, University of Valladolid, Spain
Negin Mirriahi, University of New South Wales, Australia
Mimi Recker, Utah State University, USA
Katrien Verbert, Technische Universiteit Einhoven, Holand
Lanqin Zheng, Beijing Normal University, China
Amal Zouaq, Royal Military College of Canada, Canada
Vanda Luengo, University Joseph Fourier, France
Christos Doulkeridis, University of Piraeus, Greece
Anastasios Economides, University of Macedonia, Greece
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