** apologies for cross-posting **
After discussions with the organizers of LAK2016, we have agreed on a
consistent paper deadline for both our co-located conferences. So you now have
a little more time to really polish your L@S papers!
Important Dates
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Nov 1, 2015 : Full papers due
Dec 14, 2015: Notifications of acceptance of Full Papers: Dec 14, 2015
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 on the state of the art of several relevant source
literature is considered.
Topics
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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 tool
design
* 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 choice.
* 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
Paper Submissions
--------------------------------------------------------------------------------
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[1] and Word[2]. 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 [1] we show" -- consider "in [1] 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.
### Work-in-Progress
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 evaluated
accordingly.
Formatting: Work-in-Progress submissions 4 pages or fewer in length in the
Extended Abstracts Format[3] 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
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[3] 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 here.
* 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.
Proceedings from prior years can be accessed here:
* L@S 2014 Proceedings (http://dl.acm.org/citation.cfm?id=2556325).
* L@S 2015 Proceedings (http://dl.acm.org/citation.cfm?id=2724660).
### Submission Instructions
Full Papers and Work in Progress should be submitted at EasyChair
(https://easychair.org/conferences/?conf=las2016).
Inquiries
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Please direct all inquiries to: [email protected]
Organization
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Conference Chair:
Jeff Haywood, the University of Edinburgh, UK
Program Co-Chairs:
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
Program Committee:
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, Stanford 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
[1] https://github.com/sigchi/Document-Formats
[2] http://www.sigchi.org/publications/chipubform/sigchi-paper-format-2016/view
[3] http://chi2015.acm.org/authors/format/#extendedformat
--
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Scotland, with registration number SC005336.
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