/Apologize for unintended cross-mailing

/ =========================================================
due to technical problems
DEADLINE: *5th June*

Special issue on
*"Connecting Learning Design and Learning Analytics"*

to be published at the
/*Interaction Design and Architecture(s) Journal (IxD&A)*/
(ISSN 1826-9745, eISSN 2283-2998)
**** Since 2012 also in Scopus ****
**** *Since 2015 also* in *Emerging Sources Citation Index* and *Web of 
Science* ***
IxD&A implements the Gold Open Access (OA) road to its contents
with no charge to the authors (submission & paper processing)

If you wish to help us in improving the quality of the journal, please 

*Guest Editors:*

/• Davinia Hernández-Leo, Universitat Pompeu Fabra Barcelona
• María Jesús Rodríguez-Triana, École Polytechnique Fédérale of Lausanne
• Yishay Mor, independent consultant
• Paul Salvador Inventado, Carnegie Mellon University/
*Important dates:*
• Deadline: *June 5*, 2017 (extended)
• Notification to the authors: June 30, 2017
• Camera ready paper: July 30, 2017
• Publication of the special issue: end of September, 2017

Learning Design (LD) and Learning Analytics (LA) are both domains of 
research and action that aim to improve learning effectiveness.

Learning Design or, Design for Learning, is an emerging field of 
educational research and practice. Its practitioners are interested in 
understanding how the intuitive processes undertaken by teachers and 
trainers can be made visible, shared, exposed to scrutiny, and 
consequently made more effective and efficient. Arguably, most of the 
work in the field of LD has focused on the creative processes, on 
practices, tools and representations to support it, and on mechanisms 
for sharing its outputs between practitioners. Very little has been done 
in terms of the practices, tools and representations used for evaluating 
the effects of the designs. Several approaches emphasise top-down 
quality enhancement, which help designers to base their work on sound 
pedagogical principles. What is missing is the trajectory that would 
complete the feedback loop: the built-in evaluation of designs to see 
whether they achieved the expected outcomes.

Learning Analytics are about collecting and reporting data about 
learners and their contexts, for purposes of understanding and 
optimising learning environments. 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. 
Learning analytics are rooted in data science, artificial intelligence, 
and practices of recommender systems, online marketing and business 
intelligence. The tools and techniques developed in these domains make 
it possible to identify trends and patterns, and then benchmark 
individuals or groups against these trends. LA can help to identify 
at-risk learners and provide interventions, transform pedagogical 
approaches, and help students gain insight into their own learning.

How Learning Design may help Learning Analytics? 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. 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.

How Learning Analytics may support Learning Design? Reciprocally, 
well-formulated learning analytics can be helpful to inform teachers on 
the success and outcomes of their learning designs. Learning analytics 
can provide evidences of the impact of a design in one or several 
learning situations in aspects such as engagement patterns in the 
activities proposed by the learning design, learning paths followed by 
the students, time consumed to complete the activities, etc.

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. There is a 
natural and 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 

*Topics of Interest*
This special issue solicits original research papers framing connecting 
learning design with learning analytics.
The main topics of interest are:

● Practical examples of synergies between LD and LA.
● Methods and tools for developing data-enriched learning design and / 
or design-aware learning analytics.
● 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 and correlating LD 
and LA.
● Utilising Design Patterns as such meta-models, and as boundary objects 
for all of the above.

Submission guidelines
All submissions (abstracts and later final manuscripts) must be original 
and may not be under review by another publication.
The manuscripts should be submitted either in .doc or in .rtf format.
All papers will be blindly peer-reviewed by at least two reviewers.
Authors are invited to submit 8-20 pages paper (including authors' 
information, abstract, all tables, figures, references, etc.).

Due to temporary technical problems, for this special issue, papers can 
be submitted also by email to
info [at] mifav [dot] uniroma2 [dot] it
marking the subject as:
Paper submission for IxD&A special issue on: Connecting Learning Design 
with Learning Analytics

For scientific advice and queries, please contact any of the 
guest-editors below and mark the subject as:
IxD&A special issue on: Connecting Learning Design with Learning Analytics.

• davinia [dot] hernandez [at] upf [dot] edu
• maria [dot] rodrigueztriana [at] epfl [dot] ch
• yishaym [at] gmail [dot] com
• pinventado [at] cmu [dot] edu

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