27.3528, Calls: Computational Linguistics / TAL (Jrnl)

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LINGUIST List: Vol-27-3528. Thu Sep 08 2016. ISSN: 1069 - 4875.

Subject: 27.3528, Calls: Computational Linguistics / TAL (Jrnl)

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Date: Thu, 08 Sep 2016 10:38:32
From: Georges Antoniadis [georges.antoniadis at univ-grenoble-alpes.fr]
Subject: Computational Linguistics / TAL (Jrnl)

 
Full Title: TAL 


Linguistic Field(s): Computational Linguistics 

Call Deadline: 28-Oct-2016 

Topic: NLP for Learning and Teaching

Insights and techniques from Natural Language Processing (NLP) have long been
incorporated into computer-assisted instruction (CAI) - predominantly in the
domain of language learning - in order to support self-directed, blended, or
classroom learning. NLP has also advanced research in CAI. Today, NLP is
driving research and innovation related to Massive Open Online Courses,
pronunciation training, tutoring systems for mathematics, and applications for
learning sign languages, among many other examples.

NLP has mainly served to analyse learners' responses, detect errors and
provide feedback, monitor learning progress, and assist the production of
educational content. NLP is also involved in plagiarism detection, writing
support, and in the creation of ontologies for adaptive learning systems.

While the contribution of NLP to CAI is generally regarded as positive, only a
handful of applications have made it to the general public as commercial
software. This may be due to high production costs, the perceived quality of
NLP for such applications, or the way in which NLP is integrated into current
systems.

This issue of TAL is dedicated to ''NLP for learning and teaching'' and aims
to summarize the contribution of NLP to CAI, both at a theoretical level
(opportunities, limitations, integration methods) and at the level of
implementation.

Authors are invited to submit papers on all aspects of NLP for CAI for a given
discipline, including, but not limited to:

-Contribution of (written or spoken) NLP to CAI systems
-Needs and requirements of NLP techniques and methods for instructional
systems design
-Instructional design methodology for NLP-based CAI systems
-Presentation of systems and learning tools involving NLP
-Collection and use of language corpora for pedagogical purposes using NLP
-Use of learner corpora and error annotation using NLP
-Automated evaluation of learner writing and short answers using NLP
-(Semi)automated diagnostic assessment and remedial help
-Design and setting up of activities involving NLP
-Language resources for NLP-based instruction and learning
-Automated selection of text resources based on pedagogical criteria
-Development, presentation and use of linguistic and metalinguistic
information for pedagogical purposes
-Learner modelling based on his linguistic output
-Approaches and methods for plagiarism detection

Position papers and state of the art papers are also welcome.

Submission Guidelines:

Papers can be written in French or in English. Submissions in English will
only be accepted if at least one of the authors is not a native speaker of
French.

Submitted papers should be 20 to 25 pages long. Any dispensation regarding
length should be previously discussed with the guest editors. 

Authors are invited to submit their paper as a PDF file on
http://tal-57-3.sciencesconf.org/, by clicking on ''Soumission d'un article'',
after having previously registered and logged in on SciencesConf.org.

The TAL Journal follows a double-blind peer-reviewing process. All submissions
must be carefully anonymized. 

Stylesheets are available online on the journal website:
http://www.atala.org/IMG/zip/tal-style.zip.

Important Dates:

-Paper submission deadline: 28 October, 2016
-Notification to the authors after first review: 17 February, 2017
-Notification to the authors after second review: 28 April, 2017
-Publication: September 2017

Guest Editors:

-Georges Antoniadis, Université Grenoble-Alpes, LIDILEM, France
-Piet Desmet, KU Leuven, iMinds-ITEC, Belgium




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