The 9th International Conference on Learning Analytics & Knowledge (LAK19) Special Theme: “Learning Analytics to Promote Inclusion and Success” 4-8 March 2019, Tempe, Arizona • http://lak19.solaresearch.org The 2019 edition of the international conference on Learning Analytics & Knowledge will take place in Tempe, Arizona, USA. LAK19 is organised by the Society for Learning Analytics Research (SoLAR) […]
LAK’ 18 Workshop – International Workshop on Orchestrating Learning Analytics: Learning Analytics Adoption at the Classroom Level (OrLa 2018)
Call for Participation International Workshop on Orchestrating Learning Analytics: Learning Analytics Adoption at the Classroom Level In conjunction with LAK 2018 at The University of Sydney, Australia March 5, 2018 https://latte-analytics.sydney.edu.au/index.php/pre-conference-events http://orla.utscic.edu.au/ Adopting learning analytics solutions in a real setting requires effective identification and communication between different stakeholder communities (including researchers, teachers, students and technology […]
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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 donate:
• 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
• Deadline: May 20, 2017
• 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 challenge.
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 and procedure
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.).
The paper should be written according to the IxD&A authors’ guidelines
Link to the paper submission page:
(Please upload all submissions using the Submission page. When submitting the paper, please, choose Domain Subjects under:
“IxD&A special issue on: ‘Connecting Learning Design with Learning Analytics’)
More information on the submission procedure and on the characteristics
of the paper format can be found on the website of the IxD&A Journal
where information on the copyright policy and responsibility of authors,
publication ethics and malpractice are published.
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
15th International Conference on Web-Based Learning (ICWL 2016)26-29 October 2016, Rome, Italy http://icwl2016.dis.uniroma1.itICWL is an annual international conference on Web-based learning, founded by the Hong Kong Web Society. The first IC…
My colleague Nic. Nistor from LUM Munich gave a presentation on our joint work on existing learning analytics literature covering empirical research at EC-TEL 2015. Most work is following main stream, meaning to analyse the log data of some university …
L@S 2016, the Third Annual Meeting of the
The conference is at the intersection of computer science and the learning sciences, seeking to improve practice and theories of learning at scale. Strong submissions typically build on relevant research and frameworks beyond a single home discipline. The program committee is multidisciplinary and will expect that contributions expand what is known when the state of the art of several relevant source literatures is considered.
Full papers due: Oct 18, 2015 Notifications of acceptance of Full Papers: Dec 14, 2015
Work-in-progress (WiP) and Demonstration papers due: Jan 3, 2016
Full Papers camera-ready copy due: Jan 14, 2016
Notifications of acceptance of WiP and Demonstration papers: Jan 31, 2016
WiP, Demonstrations camera-ready copy due: Feb 14, 2016
L@S 2016 Conference: Apr 25, 26, 2016
No extensions will be given.
We solicit paper submissions reporting on rigorous research on methodologies, studies, analyses, tools, or technologies for learning at
scale. Learning at Scale includes MOOCs, games (including massively
multiplayer online games), citizen science communities, and other types of
learning environments which (a) provide learning experiences to large
number of learners and/or (b) produce detailed, high volume data about the
learning process. Papers that tackle specific aspects of scale are
particularly encouraged, for example, papers that deal with learning or
educational phenomena that can only occur, be supported, or be observed
with very large numbers of students, or in which the system improves after
being exposed to data from previous use by many students.
Example topics include but are not limited to:
* Usability studies and effectiveness studies of design elements for
students or instructors, including:
* Status indicators of student progress
* Status indicators of instructor effectiveness
* Tools and pedagogy to promote community, support learning, or
increase retention in at-scale environments
* Log analysis of student behavior, e.g.:
* Assessing reasons for student outcome as determined by modifying
* Modeling students based on responses to variations in tool design
* Evaluation strategies such as quiz or discussion forum design
* Instrumenting systems and data representation to capture relevant
indicators of learning.
* Personalization and adaptation, based on log data, user modeling, or
* Studies of applications of existing learning theories to the MOOC
context (peer learning, project based learning, etc.).
* Informing theories of learning at scale.
* Large online learning in the developing world
* New tools and techniques for learning at scale, including:
* Games for learning at scale
* Automated feedback tools (for essay writing, programming, etc)
* Automated grading tools
* Tools for interactive tutoring
* Tools for learner modeling
* Interfaces for harnessing learning data at scale
* Innovations in platforms for supporting learning at scale
* Tools to support for capturing, managing learning data
* Tools and techniques for managing privacy of learning data
* Investigation of observable student behaviors and their correlation if
any with learning, e.g.:
* What do more successful learners do more of?
* What do more successful instructors do more of?
* Self- and co-regulation of learning at scale
* Collaborative learning in courses that have scale
* Depth and retention of learning and understanding
* Improvements to learning, community, and pedagogy in large-scale
in-person and blended online and in-person courses
* Instructional principles for learning at scale
* Facilitation of informal subcommunities
We invite full paper, shorter papers reporting on work-in-progress, and demonstrations.
### Full Papers
Full papers must not exceed 10 pages (shorter is fine) and must use the
ACM CHI Archive Format, available in latex and Word. Submissions
must be in PDF format, written in English, contain original work and not
be under review for any other venue while under review for this
conference. All papers should be submitted through the EasyChair.
In order to increase high quality papers and independent merit, the
evaluation process will be double blind. The papers submitted for review
MUST NOT contain the authors’ names, affiliations, or any information that
may disclose the authors’ identity (this information is to be restored in
the camera-ready version upon acceptance). Please replace author names and
affiliations with Xs on submitted papers. In particular, in the version
submitted for review please avoid explicit auto-references, such as “in
 we show” — consider “in  it is shown”. I.e., you should cite your
own relevant previous work, so that a reviewer can access it and see the
new contributions, but yet the text should be written so that it does not
state that the cited work belongs to the authors.
A Work-in-Progress (WiP) is a concise report of recent findings or other
types of innovative or thought-provoking work that has not yet reached a
level of completion that would warrant submission of a full paper. Topics
are the same as those listed for full papers.
At the conference, all accepted WiP submissions will be presented in
poster form. Selected WiPs may be invited for oral presentation during the
conference. Rejected full-papers can be resubmitted as WiP and will be
Formatting: Work-in-Progress submissions 4 pages or fewer in length in the
Extended Abstracts Format and submitted as a PDF file. Due to the very
rapid selection process we cannot offer any extensions to the deadline.
WiP submissions are not anonymous and should therefore include all author
names, affiliations and contact information. If accepted, you should
expect to prepare a poster to present at the conference venue. WiP
submissions should be submitted through the EasyChair.
Demonstrations show aspects of learning at scale in an interactive
hands-on form. A live demonstration is a great opportunity to communicate
ideas and concepts in a powerful way that a regular presentation cannot.
We invite demonstrations of learning and analytical environments and other
systems that have direct relevance to learning at scale. We especially
encourage authors of accepted papers and industrial partners to showcase
their technologies using this format. Demonstration submissions are 2
pages or fewer in length in the Extended Abstracts Format and submitted
as a PDF file. A demonstration proposal should address two components:
* The merit and nature of the demonstrated technology. If the proposed
demonstration is associated with a Full Paper or a WiP submission, please
point to the title of the submission instead of repeating the information
* Details of how the demo will be executed in practice, and how visitors
will interact with it during the conference.
Proposals for demonstrations should be submitted through the EasyChair.
### Archival Proceedings
Full papers will appear in the conference proceedings published by the ACM
Press in the ACM Digital Library. Work-in-Progress and Demonstration
papers will appear in a separate part of the conference proceedings. The
status of Work-in-Progress paper will be akin to what CHI describes as
“semi-archival”, meaning the results reported in the WIP must be original,
but copyright is retained by the authors and the material can be used as
the basis for future publications in ACM venues as long as there are
significant revisions from the original.
### Submission Instructions
Full Papers and Work in Progress should be submitted at EasyChair
Please direct all inquiries to: firstname.lastname@example.org
Conference Chair: Jeff Haywood, the University of Edinburgh, UK
Vincent Aleven, Carnegie Mellon University, USA
Judy Kay, University of Sydney, Australia
Ido Roll, University of British Columbia, Canada
Local Organization Chair:
Dragan Gasevic, the University of Edinburgh, UK
Tiffany Barnes, North Carolina State University, USA
Marie Bienkowski, SRI International, USA
Gautam Biswas, Vanderbilt University, USA
Ulrike Cress, Knowledge Media Research Center, Germany
Pierre Dillenbourg, École Polytechnique Fédérale de Lausanne, Switzerland
Douglas Fisher Vanderbilt University, USA
Armando Fox, University of California at Berkeley, USA
Dragan Gasevic, University of Edinburgh, UK
Art Graesser, University of Memphis, USA
Philip Guo, University of Rochester, USA
Marti Hearst, University of California at Berkeley, USA
Daniel Hickey, Indiana University, USA
Ulrich Hoppe, University of Duisburg-Essen, Germany
Juho Kim, Massachusetts Institute of Technology, USA
Kenneth Koedinger, Carnegie Mellon University, USA
Chinmay Kulkarni, Carnegie Mellon University, USA
Marcia Linn, University of California at Berkeley, USA
Marsha Lovett, Carnegie Mellon University, USA
Rose Luckin, The London Knowledge Lab, UK
Robert Miller, Massachusetts Institute of Technology, USA
John Mitchell, Stanford University, USA
Antonija Mitrović, University of Canterbury, New Zealand
Zachary Pardos, University of California at Berkeley, USA
Beverly Park Woolf, University of Massachusetts, USA
Jeremy Roschelle, SRI International, USA
Carolyn Rose, Carnegie Mellon University, USA
Daniel Russell, Google, USA
Mehran Sahami, Stanford University, USA
Eileen Scanlon, Open University, UK
Daniel Seaton, Massachusetts Institute of Technology, USA
Karen Swan, Univ of Illinois, Springfield, USA
Candace Thille, Stanford University, USA
Astrid Wichmann, Ruhr-University Bochum, Germany
Tallinn University is hiring: ERA Chair holder, Research Professor of Learning Analytics and Educational Innovation
Tallinn University (TU, www.tlu.ee/en) invites outstanding scholars to submit an application for a Research Professor of Learning Analytics and Educational Innovation. The position will be opened in the framework of the project CEITER: Cross-Border Educational Innovation thru Technology-Enhanced Research (ceiter.tlu.ee/about). The CEITER project is funded by the Horizon 2020 ERA Chair programme and it aims to […]
Games and Learning Alliance Conference (GaLA Conference 2015)Rome, ItalyDecember 10-11, 2015 http://www.galaconf.orgAIMS AND SCOPEThere is a wide consensus in the scientific community about the educational potential of Serious Games. A…
CALL FOR PAPERS
We invite submissions to the 8th International Conference on Education Data Mining (EDM 2015), to be held under auspices of the International Educational Data Mining Society at UNED, the National University for Distance Education in Spain.
The EDM conference is a leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process.
We are glad to announce three confirmed keynote speakers:
– Prof. George Siemens, Founding President of SoLAR, Society for Learning Analytics Research.
– Pekka Räsänen, Clinical neuropsychologist; Executive vice director in Niilo Mäki Institute, Finland
– Bror Saxberg, Chief Learning Officer, Kaplan, Inc.
EDM 2015 will follow the AIED 2015 (22-26 June 2015) that is also organized by UNED in Madrid, Spain. Synergies between both EDM and AIED communities will be supported.
TOPICS OF INTEREST
Topics of interest to the conference include, but are not limited to:
– Closing the loop between education data research and educational outcomes
– Stealth assessment and evaluating the efficacy of curriculum and
– Deriving representations of domain knowledge from data
– Detecting and addressing students’ affective and emotional states
– Integrating data mining and pedagogical theory
– Data mining with emerging pedagogical environments such as
educational games, MOOCs, and exploratory learning
– Multi-modal learning environments and sensor analysis
– Providing feedback to teachers, students & other stakeholders
generated from EDM methods
– Papers that apply a previously used technique to a new domain, or
that reanalyze an existing data set with a new technique
– Bridging EDM and Learning analytics
– Bridging learning sciences, learning theory and EDM
– Monitoring and mining results of automated feedback and grading
– Monitoring and mining results of learning resources usage logs
– Best practices for adapting the state of the art data mining,
information retrieval, recommender systems and social network analysis
approaches to the educational domain
– Data mining in social and collaborative learning
– Generic frameworks, techniques, research methods and approaches for EDM
– (New!) JEDM Journal Track Papers: Submit your best work to the
Journal of EDM (submission is open already), get it accepted before
April 20th, 2015 and have your work presented at EDM 2015. See further
details at http://educationaldatamining.org/EDM2015/index.php?page=jedm
– Full Papers: 6-8 pages. Should describe original, substantive,
mature and unpublished work.
– Short Papers: 4 pages. Should describe original, unpublished work.
This includes early stage, less developed works in progress.
– Industry Papers: 4-6 pages. Industry papers should describe
innovative ways in which data drives system features or processes in a
– Doctoral Consortium: 3 pages. Should describe the
graduate/postgraduate student¹s research topic, proposed
contributions, results so far, and aspects of the research on which
advice is sought. Should be solely authored by the student.
– Posters: 2 pages. Posters can be used both to describe original and
unpublished work in progress, as well as to share last minute breaking
– Demos: 2 pages. Demos should describe educational data mining tools
and systems, or educational systems that use EDM techniques, which are
to be interactively presented at the conference.
All accepted papers will be published in the open-access proceeding of
the conference. A selection of accepted papers for the conference will
be invited to extend their submission (providing a significant
contribution beyond the conference paper) for a special issue in the
Journal of Educational Data Mining.
Submission guidelines are available at
IMPORTANT DATES (There will be no extensions)
12 Jan 2015: Workshop and Tutorial proposal submissions
26 Jan 2015: Notification of acceptance (Workshops and Tutorials)
2 Feb 2015: Abstract for Full/Short paper submissions
9 Feb 2015: Full and Short paper submissions
19 Feb 2015: Doctoral Consortium submissions
2 Apr 2015: Notification of acceptance (Full/Short/DC)
5 Apr 2015: Poster/Demo/Workshop submissions:
19 Apr 2015: Notification of acceptance (Posters/Demos/Workshops)
26 Apr 2015: Camera ready versions
26-29 Jun 2015: Conference days
Jesus G. Boticario (UNED)
Olga C. Santos (UNED)
Cristóbal Romero (UCO)
Mykola Pechenizkiy (TUE)
Industry track chairs
Agathe Merceron (BUAS)
Piotr Mitros (EdX)
Journal track chair
Michael Desmarais (UM)
Jose Maria Luna (UCO)
Christian Mihaescu (UC)
Interactive Events/Demo chairs
Pablo Moreno (UCM)
Arnon Hershkovitz (TAU)
Doctoral Consortium chairs
Sebastián Ventura (UCO)
Amin Y. Noaman (KAU)
Workshop and Tutorial chairs
Katrien Verbert (VUB)
Kaska Poryaska-Pomsta (LKL)
Sergio Gutierrez-Santos (BBK/LKL)
Taylor Martin (UU)
Dragan Gasevic (AU)
Manolis Mavrikis (LKL)
Kalina Yacef (US)
Pilar Muñoz (UNED)
Local Arrangement chair
Emmanuelle Gutiérrez y Restrepo