Connecting Learning Analytics and Learning Design (CLAD 2016) Workshop @ EC-TEL

Call for Papers
Connecting Learning Analytics and Learning Design (CLAD 2016) Workshop @ EC-TEL


In conjunction with EC-TEL 2016 at Lyon (France) | September 13-16, 2016

*Important Dates*

10 May 2016: Start open submission
15 June 2016: End open submission
30 June 2016: Peer review submission deadline
15 July 2016: Notification to authors
30 August 2016: Video presentation deadline
16 September 2016: Workshop at ECTEL’16

*Workshop Theme*

Learning Design (LD) and Learning Analytics (LA) are both domains of research and action that aim to improve learning effectiveness. In Learning Design or, as some prefer, Design for Learning, practitioners are interested in understanding how the processes undertaken by teachers and trainers can be made visible, shared, exposed to scrutiny, and consequently made more effective and efficient. On the other hand, Learning Analytics are defined as “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”. LA typically employ large datasets to provide real-time or retrospective insights about the effect and effectiveness of various elements and features of learning environments.

According to situational approaches, one of the prerequisites to obtain relevant outputs is not to isolate the analysis of educational data from the context in which it is embedded. Following this perspective, some authors state that this tandem between LD and LA offers the opportunity to better understand student behaviour and provide pedagogical recommendations when deviations from the original pedagogical intention emerge, addressing one of the challenges posed by LA, i.e.: interpreting the resulting data against the original pedagogical intent and the local context, to evaluate the success of a particular learning activity.

This approach of linking LD and LA has been already applied to support learning in different contexts (such as blended, on-line or computer-supported collaborative learning), scales (from small classrooms to MOOCs), and abstraction levels (from particular learning activities to the accomplishment of the curriculum objectives defined in a course). Reciprocally, LA can be helpful to inform teachers on the success and outcomes of their learning designs, e.g., providing evidence of the design impact on aspects such as engagement, learning paths, time consumed to complete the activities, etc. These data can support awareness and reflection about the effects of the learning designs as well as redesign processes, by facilitating the identification of design elements that need to be revised before reuse.

To sum up, LD offers LA a domain vocabulary, representing the elements of a learning system to which analytics can be applied. LA in turn, offers LD a higher degree of rigor by validating or refuting assumptions about the effects of various designs in diverse contexts. Thus, there is a synergistic relationship between both domains, which has led to a growing interest and some initial effort in bringing them together. However, making these links operational and coherent is still an open challenge.

This workshop aims to open up the dialogue between the learning design (LD) and learning analytics (LA) communities, acknowledging the potential benefits for both fields from a productive synergy. As such, we expect participants from both of these communities, who have a deep understanding of one domain, and at least a keen interest in the other. We also welcome participants from other domains where the synergy of LD and LA could offer valuable opportunities.


This workshop solicits original research papers (up to 3-5000 words, not including references) reporting empirical findings, as well as early results and conceptual papers connecting learning design with learning analytics. Concretely, we welcome contributions addressing one or more of these domains:

•    Practical examples of synergies between LD and LA.
•    Methods and tools for developing data-enriched LD and / or design-aware LA.
•    Application domains for integrated LD-LA approaches, such as teacher inquiry, learning at scale, and self-determined learning.
•    Theoretical and conceptual foundations, opportunities and challenges for synergies between LD and LA.
•    Meta-models and mediating frameworks for connecting LD and LA.

All submissions will be single-blind peer reviewed by two reviewers. The paper submission process includes two phases:
•    Open review: contributors will be encouraged to post their paper online for public discussion, instructions will be published in the workshop website.
•    Peer review: contributors are asked to submit their paper for peer review through EasyChair. Reviewers will consider the public discussion of the papers in their review. Papers which have not been submitted to the open review phase will be given a lower priority in the selection process.

Most relevant papers will be invited to send their contributions to the special issue on Connecting Learning Design and Learning Analytics to be announced at the Interaction Design & Architecture(s) journal.

If you have any further questions, we encourage you to contact the organisers.

*Organising Committee*
María Jesús Rodríguez-Triana, École Polytechnique Fédérale de Lausanne (
Davinia Hernández-Leo, Universitat Pompeu Fabra, Barcelona (
Yishay Mor, PAU Education (
Paul Salvador Inventado, Carnegie Mellon University (
Steven Warburton, University of Surrey (
Bart Rienties, Open University UK (
Luis P. Prieto, École Polytechnique Fédérale de Lausanne (
Peter Scupelli, Carnegie Mellon University (