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LAK 2011 : 1st International Conference Learning Analytics and Knowledge


Conference Series : Learning Analytics and Knowledge
When Feb 27, 2011 - Feb 27, 2011
Where Banff, Alberta, Canada
Submission Deadline Nov 1, 2010
Categories    data mining

Call For Papers

Call for Papers

1st International Conference Learning Analytics & Knowledge
February 27-March 1, 2011, Banff, Alberta, Canada

Sponsored by Athabasca University (Canada) and University of Queensland (Australia)
In partnership with EDUCAUSE

Publication of accepted conference papers in Springer's LNCS volume (pending approval)
A special issue in a leading international journal planned.

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The growth of data surpasses the ability of organizations to make sense of it. This concern is particularly pronounced in relation to knowledge, teaching, and learning. Learning institutions and corporations make little use of the data learners "throw off" in the process of accessing learning materials, interacting with educators and peers, and creating new content. In an age where educational institutions are under growing pressure to reduce costs and increase efficiency, analytics promises to be an important lens through which to view and plan for change at course and institutions levels. Corporations face pressure for increased competitiveness and productivity, a challenge that requires important contributions in organizational capacity building from work place and informal learning. Learning analytics can play a role in highlighting the development of employees through their learning activities. In enterprise settings, information flow and social interactions can yield novel insights into organizational effectiveness and capacity to address new challenges or adapt rapidly when unanticipated event arise. Thirdly, as we witness the expansion of learning and knowledge work beyond formal institutional boundaries, myriad platforms in the cloud hosting the activity of individuals will be providing/exchanging analytics.

Advances in knowledge modeling and representation, the semantic web, data mining, analytics, and open data form a foundation for new models of knowledge development and analysis. The technical complexity of this nascent field is paralleled by a transition within the full spectrum of learning (education, work place learning, informal learning) to social, networked learning. These technical, pedagogical, and social domains must be brought into dialogue with each other to ensure that interventions and organizational systems serve the needs of all stakeholders.

Learning Analytics 2011 will focus on integrating the technical and the social/pedagogical dimensions of learning analytics.


Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs. Conference organizers are seeking submissions that cover various topics related to learning analytics including (but not limited to):


* Software development and use in analytics
* The role of knowledge representation and ontologies in learning analytics
* The semantic web and linked data: meaning in connections
* Data mining in learning analytics
* Artificial intelligence in learning analytics
* Internet of things (sensors) and learning applications
* "Big Data" applications and opportunities in learning and education
* Latent semantic analysis/natural language processing
* Attention metadata
* Architecture of learning environments and implications to learning analytics
* Software needed to advance learning analytics as a field


* Visualization: data, learner networks, conceptual knowledge
* Predictive applications of data
* Interventions based on analytics
* Social and technical systems to manage information abundance
* Personalization and adaptivity in the learning process
* Corporate and higher education case studies of learning analytics
* Learning analytics for intelligent tutoring systems
* Open data: data access for learners
* Harmonizing individual learning with organizational learning
* Importing insights for existing analytics
* Use of learning analytics in centralized (learning management systems) and decentralized (personal learning environments) settings

Conceptual & Pedagogical

* The relationship between learning analytics and existing theories and approaches (such as pedagogical models and learning sciences)
* Social network analysis
* Cognitive modelling
* Harnessing the power of context and location aware systems
* Informal learning: integrating learning and knowledge systems
* Privacy & ethics in learning analytics
* The influence of analytics on designing for learning
* The influence of analytics on delivery and support of learning

Paper Categories

The following types of original papers are solicited:

* Research papers: These should report a substantial research contribution to learning analytics or the application of analytics. Full paper submissions should not exceed 20 pages.
* Vision or conceptual papers: These may describe interesting, visionary, or thought-provoking concepts that are not yet fully developed or evaluated, make an initial contribution to challenging research issues in learning analytics. These papers should not exceed 10 pages.
* Mini-tutorial papers: Learning analytics is a young field of research with contributions from technical, social, and pedagogical domains. As such, there is a need for illustrations, examples, and cross-discipline discussion to unite these domains. Mini-tutorials are solicited that provide discussion points for mapping common ideas between related and complementary research topics of learning analytics. A mini-tutorial submission should be between 15 and 20 pages.
* Tool demonstration papers: Learning analytics focuses on new technologies and tools. As a result, we seek papers that present software tools related to the field of learning analytics. These papers will accompany a tool demonstration to be given at the conference. These papers must not exceed 10 pages. The selection criteria include the originality of the tool, its innovative aspects, the relevance of the tool to learning analytics, and the maturity of the tool.

Paper Submission and Publication

All the accepted papers will be published in a post proceedings open volume in Springer's Lecture Notes in Computer Science series (pending Springer's approval). Selected and revised papers will be published in a special issue of a leading international journal.

Please submit papers through Learning Analytics EasyChair conference system:

All papers must be formatted according to the Springer?s Lecture Notes in Computer Science style:

Important Dates

Paper submission: November 1, 2010
Notification: December 1, 2010
Early bird-registration deadline: December 15, 2010


Steering Committee Members

* Jon Dron, CSIS, Athabasca University, Canada
* Erik Duval, Katholieke Universiteit Leuven, Belgium
* David Wiley, Brigham Young University, US
* John Campbell, Purdue University, US
* Dave Cormier, University of Prince Edward Island, Canada
* Tony Hirst, Open University, UK
* Grainne Conole, Open University, UK
* Martin Weller, Open University, UK
* Shane Dawson, University of British Columbia, Canada
* Dragan Gasevic, CSIS, Athabasca University, Canada
* Michael Kouritzin, University of Alberta, Canada
* Simon Buckingham Shum, Knowledge Media Institute, UK
* Linda Baer, Gates Foundation, US
* Martin Wolpers, Fraunhofer-Institut f?r Angewandte Informationstechnik FIT
* Caroline Haythornthwaite, University of British Columbia, Canada
* Ryan S.J.d. Baker, Worcester Polytechnic Institute, US
* Cyprien Lomas, CEIT, University of Queensland, Australia

Conference Co-chairs

* George Siemens, TEKRI, Athabasca University, Canada
* Phillip Long, CEIT, University of Queensland, Australia

Conference Program Committee Chairs

* Dragan Gasevic, Athabasca University, Canada
* Grainne Conole, Open University, UK

Publicity Chair

* Milan Stankovic, Universit? Paris-Sorbonne and Hypios Research, France


* George Siemens,

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