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Jelena Jovanovic
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Jelena Jovanovic

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1st International Workshop on Open Badges in Education (#OBIE2014) - 2nd Call for Papers

=> in conjunction with the 13th International Conference on Web-based Learning (ICWL2014), Tallinn, Estonia, 14-17 August 2014
=> proceedings published by Springer

* 1 May 2014: Paper submission deadline
* 23 May 2014: Notification of acceptance
* 13 June 2014: Camera-ready paper
* 16 August 2014: Open Badges in Education workshop day (to be confirmed by the Conference organizers)

* Weiqin Chen, University of Bergen, Norway 
* Vladan Devedzic, University of Belgrade, Serbia
* Dragan Gasevic, Athabasca University, Canada
* Jelena Jovanovic, University of Belgrade, Serbia

Open Badges (OBs) initiative is a community effort aimed at introducing novel means and practices for knowledge/skill assessment, recognition, and credentialing. Along the way, it is also promoting values such as openness and learner?s agency, as well as participatory learning practices and peer-learning communities.
Even though digital badges are not a new phenomenon, their use prior to the emergence of the OBs initiative was largely associated with isolated efforts of individual organizations, and there was no systematic approach to issuing and using badges. Likewise, OBs should not be equated with digital badges that are used solely as a part of gamification efforts aimed at motivating users for different kinds of tasks; OBs differ in at least two significant ways. First, they allow learners to gather badges that originate from different sources (i.e., organizations acting as badge issuers), and to select and combine the earned badges into custom profiles suitable for the given occasion (e.g., job application). Second, OBs are self-sufficient in the sense that they carry all the information one would need to understand and value the achievement/status they refer to. 
All these novel and distinctive features have positioned OBs as suitable candidates for addressing some of the pressing challenges in the context of life-long and Web-based learning, including: i) recognition of learning in multiple and diverse locations and environments that go beyond traditional classrooms; ii) recognition of diverse kinds of skills and knowledge, including soft and general skills; iii) recognition of alternative forms of assessment; iv) the need for transparent and easily verifiable digital credentials.

Open Badges (OBs) are rapidly gaining traction among educational practitioners as well as education-oriented companies and non-profit organizations. However, so far, there have been only a few research studies aimed at validating the propositions related to OBs. This indicates an obvious need for higher engagement of the research community in order to assure a deeper understanding of not only OBs and their potential roles, but also the larger educational ecosystem within which they operate and evolve. 

Considering everything stated above, this workshop would welcome submissions on some of the topics from the following (though not restrictive) list:

* OBs as a motivational mechanism
* OBs as means of supporting and promoting participatory learning practices
* OBs as means of supporting and recognizing alternative assessment 
* OBs as means of recognizing prior learning
* OBs as means of charting learning trajectories
* OBs as a facilitator of self-regulated learning
* OBs as means of building and maintaining learner's profile (portfolio)
* Implementation of OBs in different kinds of educational settings (formal, non-formal, informal)
* Software systems and tools for the implementation and deployment of OBs
* Technical challenges in enabling the intended functionalities of OBs

We welcome the following types of contributions:

   * Short (up to 5 pages) and full (up to 10 pages) research papers,
   * Poster abstracts and system demonstrations (should not exceed 2 pages).

All submissions must be written in English and must be formatted according to the Springer LNCS format 

Please submit your contributions electronically in PDF format at


All the submissions will go through a double-blind review process. Submissions 
will be evaluated according to their significance, originality, technical content, style, clarity, and relevance to the workshop. 
At least one author of each accepted paper is expected to attend the workshop.

All accepted workshop papers will be published in a separate post-proceedings volume in Springer Lecture Notes in Computer Science (LNCS). 

* Samuel Abramovich, University at Buffalo - SUNY, USA
* Simon Cross, The Open University, UK
* Elizabeth Dalton, University of New Hampshire, USA
* Rebecca Galley, The Open University, UK
* Sheryl Grant, Duke University, USA
* Richard Kimbell, Goldsmiths University of London, UK
* Rudy McDaniel, University of Central Florida, USA
* Ivana Mijatovic, University of Belgrade, Serbia
* Michael R. Olneck, University of Wisconsin-Madison, USA
* Razvan Rughinis, University Politehnica of Bucharest, Romania
* Jose Luis Santos Odriozola, KU Leuven, Belgium
* Julian Sefton-Green, London School of Economics and Political Sciences, UK
* Felicia M. Sullivan, Tufts University, USA

For further questions please contact the organisers via 
* obie2014[at] * 
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Jelena Jovanovic

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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


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@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 ([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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Structured Data Markup Helper seems so easy to use and so effective, exactly the kind of tool needed  to streamline the adoption of structured data 
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Associate Professor
  • University of Belgrade
    Associate Professor, 2013 - present
  • University of Belgrade
    Assistant Professor, 2008 - 2013
  • University of Belgrade
    Teaching Assistant, 2004 - 2008
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Hi, I'm Linked Data and Semantic Web enthusiasts; I'm also doing research related to learning and knowledge management; recently, I've became interested also in motivation and game mechanics
Besides research, I adore travelling and I'm a fitness addict:) 
  • University of Belgrade
    B.Sc. in Information systems and technologies, 1997 - 2003
  • University of Belgrade
    M.Sc in Software engineering and informatics, 2003 - 2005
  • University of Belgrade
    PhD in Software engineering and informatics, 2005 - 2007
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