-------- Original-Nachricht -------- Betreff: [WI] Special Issue on "Learning Analytics" in International Journal of Technology Enhanced Learning Datum: Mon, 04 Feb 2013 13:32:33 +0100 Von: Zinayida Petrushyna petrushyna@i5.informatik.rwth-aachen.de An: Verborgene_Empfaenger: ;

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International Journal of Technology Enhanced Learning

Special Issue on "Learning Analytics" Submission Deadline: /7 March, 2013/

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From primary school to university and workplace settings, both formal and informal learning scenarios are gaining complexity with the combination of individual and group tasks as well as distance activities. Also, the integration of a wide range of technologies such as virtual and personal learning environments (VLEs/PLEs), Web 2.0 tools, tangible and virtual or mobile tools is becoming increasingly common in the learning environment. Thus, terms such as "distributed learning environments", "informal learning", "ubiquitous learning" and "learning across spaces" are becoming increasingly popular.

In such settings, organizations and participants ask for information that raises their awareness and helps them to realize what is happening in the learning scenario. Frequently, current solutions provide an overwhelming amount of information that does not address users' needs. Therefore, teachers cannot react in time and learners cannot self-regulate their learning. The acknowledgment of these needs is exemplified by the recent emergence of learning analytics, a research area that draws from multiple disciplines such as learning sciences, information and computer sciences, sociology, psychology, statistics and educational data mining.

According to the Society for Learning Analytics (SoLAR - Society for Learning Analytics: http://solaresearch.org/), /"Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs"./

Among the different challenges that need to be addressed in this research area, *the aim of this special issue is to move forward in the application of learning analytics in authentic learning scenarios, both in formal and informal settings*. These learning scenarios may be in academic as well as workplace environments. Thus, we encourage researchers and practitioners from technological and educational domains to submit original research highlighting conceptual (novel concepts, models or theories), technical (novel tools and systems based on learning analytics) and empirical (case studies and evaluations) works that contribute to the application of learning analytics in authentic learning scenarios.

Contributions can be of the following types:

*Research articles*(5000-7000 words): mature work requiring lengthy explanations of conceptual background, methodology, data analysis and evaluation. These submissions should state: the major issue(s) addressed, potential significance of the work, the theoretical and methodological approach(es) pursued, major findings, conclusions and implications.

*Research notes*(3500-5000 words): papers describing work that makes significant contributions, but which is still in progress, of a smaller scale or which can be reported briefly.

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*Subject Coverage*

Suitable topics include but are not limited to:

* Conceptual and pedagogical underpinning:

* Collaborative knowledge building * Teaching techniques and strategies for online learning * Evaluation methods for TEL * Rethinking pedagogy in TEL * New models of learning enabled by analytics * Learner modelling * Privacy and ethics in learning analytics * Influence and connections between learning analytics and learning sciences, educational research methods, pedagogical models, learning design, delivery and support of learning

* Technological underpinning:

*Ubiquitous and pervasive technologies for TEL * Computer-supported collaborative learning * Architecture of learning environments and implications to learning analytics * Use of learning analytics in centralized (learning management systems) and decentralized (personal learning environments) settings * The limits of web analytics

* Applications and case studies:

*Case studies in formal and informal settings * Corporate and higher education case studies * Learning analytics applications in workplace * Visualization and analysis of group behavior and group dynamics * The study of emotion, flow and affective data in learning analytics * Data TEL: utilizing real-time data to improve teaching and learning * Estimation of group/individual performance by humans vs. automatic * Validating analytics empirically

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*Important Dates*

Submission deadline: /7 March, 2013 (EXTENDED) /

Notification of authors: /9 May, 2013 //(EXTENDED)/

Submission of final papers: /6 June, 2013 //(EXTENDED)/

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*Guest Editors: *

María Jesús Rodríguez-Triana, University of Valladolid, Spain

Simone Braun, CAS Software AG, Germany

Verónica Rivera-Pelayo, FZI Research Center for Information Technology, Germany

Zinayida Petrushyna, RWTH Aachen University, Germany

Ana Loureiro, Polytechnic Institute of Santarém, Portugal

Sara Villagrá-Sobrino, University of Valladolid, Spain

Ricardo Kawase, L3S Research Center, Germany

Lori Lockyer, University of Wollongong, Australia

Abelardo Pardo, University Carlos III of Madrid, Spain

For more details visit our website: http://www.inderscience.com/info/ingeneral/cfp.php?id=1950**