Prof Pérez-Paredes to join the EB of Artificial Intelligence and Language Education (AILE)

Artificial Intelligence and Language Education (AILE) is a peer-reviewed international open-access journal that focuses on the intersection of artificial intelligence (AI) and language education. The journal welcomes submissions addressing the theoretical, empirical, and practical dimensions of AI-driven advancements in language teaching, learning, and assessment. By bringing together research from linguists, educators, AI experts, and technologists, Artificial Intelligence and Language Education aims to contribute to the ongoing transformation of language education and foster a global dialogue on the role of AI in shaping the future of language learning.

Prof Pérez-Paredes has accepted the invitation to join the Editorial Board of this new journal. His academic background in linguistics and specialisation in corpus-assisted discourse studies equip Prof Pérez-Paredes to critically engage with emerging intersections between language, technology, and pedagogy. His research has explored how digital tools and AI-driven applications are reshaping language practices, both in formal education settings and in broader multilingual environments. He brings experience in analysing large-scale linguistic data and applying discourse methods to examine evolving communicative norms, which can support critical evaluation of AI’s role in shaping language education. Prof Péerez-Paredes is particularly interested in how generative AI tools affect learner agency, feedback mechanisms, and language ideologies, especially in multilingual and southern Europe.

Prof Pérez-Paredes looks forward to contributing to the journal’s mission by fostering interdisciplinary dialogues and supporting rigorous, ethically grounded scholarship in this fast-developing area.

Free copy of our latest paper in Computer Assisted Language Learning

Our article, Language teachers’ perceptions on the use of OER language processing technologies in MALL, has just been published on Computer Assisted Language Learning Journal, Taylor & Francis Online.

50 free eprints can be downloaded from the following URL:

http://www.tandfonline.com/eprint/epWFWhVAGFZ4yRSIaMcA/full

Get yours now!!!!

Abstract

Combined with the ubiquity and constant connectivity of mobile devices, and with innovative approaches such as Data-Driven Learning (DDL), Natural Language Processing Technologies (NLPTs) as Open Educational Resources (OERs) could become a powerful tool for language learning as they promote individual and personalized learning. Using a questionnaire that was answered by language teachers (n = 230) in Spain and the UK, this research explores the extent to which OER NLPTs are currently known and used in adult foreign language learning. Our results suggest that teachers’ familiarity and use of OER NLPTs are very low. Although online dictionaries, collocation dictionaries and spell checkers are widely known, NLPTs appear to be generally underused in foreign language teaching. It was found that teachers prefer computer-based environments over mobile devices such as smartphones and tablets and that teachers’ qualification determines their familiarity with a wider range of OER NLPTs. This research offers insight into future applications of Language Processing Technologies as OERs in language learning.

KEYWORDS: Language learning, teachers’ perceptions, OER, MALL, natural language processing technologies, higher education

#CFP Language Technology for Digital Humanities: Language Resources and Evaluation Journal

From the Corpora List

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CALL FOR PAPERS
We invite submissions of papers to a special issue of the journal ”Language Resources and Evaluation”. The special issue will focus on the use of language technology for digital humanities and will have the title: Language Technology for Digital Humanities.
MOTIVATION:
The use of digital resources and tools across humanities disciplines has steadily increased, giving rise to new research paradigms and associated methods that are commonly subsumed under the term ”digital humanities”. Digital humanities does not constitute a new discipline in itself, but rather a new approach to humanities research that cuts across different existing humanities disciplines. While digital humanities extends well beyond language-based research, textual resources and spoken language materials play a central role in most humanities disciplines. Applying LT tools and data for digital humanities research implies new perspectives on these resources regarding domain adaptation, interoperability, technical requirements, documentation, and usability of user interfaces.
TOPICS:
We invite original contributions on completed work, not published before and not under consideration for publication elsewhere. Specific topics include, but are not limited to:
* Case studies of using language technology and/or language resources with the goal of finding new answers to existing research questions in a particular humanities discipline or addressing entirely new research questions
* Case studies of expanding the functionality of existing language processing tools in order to be able to address research questions in digital humanities
* The design of new language processing tools as well as annotation tools for spoken and written language, showcasing their use in digital humanities research
* Domain adaption of rule-based, statistical, or machine-learning models for language processing tools in digital humanities research
* Challenges posed for language processing tools when used on diachronic data, language variation data, or literary texts
* Showcasing the use of language processing tools in humanities disciplines such as anthropology, gender studies, history, literary studies, philosophy, political science, and theology
SUBMISSION:
Accepted papers will have a length of 20-30 pages, excluding references.
Authors are advised to use the online manuscript submission for the journal. Make sure to select the special issue when asked to provide the article type. More information, including formatting instructions for authors can be found on the journal’s webpage at:  http://www.springer.com/education+%26+language/linguistics/journal/10579#
Authors are requested to send a brief email to the guest editors (LTforDH@gmail.com) indicating their intention to participate as soon as possible, including their contact information and the topic they intend to address in their submission. Questions regarding the special issue should be sent to the same address.
IMPORTANT DATES:
* Submission deadline: 31 October 2017
* Author notification of acceptance: 15 January 2018
GUEST EDITORS:
Erhard Hinrichs, University of Tübingen
Marie Hinrichs, University of Tübingen
Sandra Kübler, Indiana University
Thorsten Trippel, University of Tübingen

#CFP NLP for learning and teaching Traitement Automatique des Langues

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Through the corpora list

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TAL Journal: 2016 Volume 57-3

Call for papers

Topic: NLP for learning and teaching (Link)

Foreign Language Learning and Teaching is one of the fields where the introduction of information and communication technologies (ICT) has proved particularly fruitful. It is thus no wonder that Computer-Assisted Language Learning (CALL) has been among the first, from the 1960’s, to integrate insights and techniques from Natural Language Processing (NLP) to create intelligent computer-assisted learning environments. Since then, various other fields and disciplines have also incorporated NLP into electronic learning environments to support self-directed learning, blended learning or classroom teaching. NLP has overall contributed to the improvement of learning environments, and to the development of research in the related fields. It has allowed for the improvement of integrated systems, not to say the widening of issues in the related fields.

Today, online learning tools, Massive Open Online Courses (MOOCs), Small Private Online Courses, Computer-Assisted Pronunciation Teaching (CAPT) systems, Computer-Assisted Instruction systems for mathematics, sign language learning applications, or Intelligent Tutoring Systems (ITS), among many others, are heavy “consumers” of NLP, or about to become it.

Integrating NLP into these systems enables to consider, process and reproduce for learning purposes aspects of the content of linguistic data, to create more advanced educational resources, but also to make the communication with the learner more relevant in a teaching context.

The aspects of NLP most frequently involved are analysis of learners’ responses, feedback provision, automated generation of exercises, and the monitoring of learning progress. Other aspects related to learning and teaching also involve NLP, such as plagiarism detection, writing support, use of learner corpora or parallel corpora to detect and resolve errors, or adaptive learning systems integrating ontologies for the associated domains.

The contribution of NLP to these systems is generally regarded as positive. It must be recognized, however, that only a handful of such applications have made it to the general public as a commercial software. In most cases, the systems never left the laboratory and have a limited range of use, sometimes only as a proof of concept. Is this due, as many believe, to the high production cost of NLP resources? Is it because of the current quality of NLP results? Is it a consequence of the integration strategy of NLP into these applications?

The goal of this issue of Traitement Automatique des Langues dedicated to “NLP for learning and teaching” is to summarize the contribution of NLP to instructional systems, both at a theoretical level (opportunities, limitations, integration methods) and at the level of learning systems – or parts of systems – production.

Authors are invited to submit papers on all the aspects of the implementation of NLP into Computer-Assisted Instruction (CAI) systems for a given discipline, as well as useful tools for this task, in particular regarding, but not limited to, the following issues and tasks:

  • 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.

Language

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.

Submission guidelines

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

Journal

Traitement Automatique des Langues is an international journal published since 1960 by ATALA (Association pour le traitement automatique des langues) with the support of CNRS. It is now published online, with an immediate open access to published papers, and annual print on demand. This does not change its editorial and reviewing process.

Guest editors

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

Editorial Board

  • Véronique Aubergé, LIG, Université Grenoble-Alpes, France
  • Yves Bestgen, IPSY, Université Catholique de Louvain, Belgique
  • Eric Bruillard, STEF, ENS Cachan, France
  • Cristelle Cavalla, DILTEC, Université Sorbonne Nouvelle, France
  • Thierry Chanier, LRL, Université Blaise Pascal de Clermont Ferrand, France
  • Françoise Demaizière, Université Paris Diderot, France
  • Philippe Dessus, LSE, Université Grenoble-Alpes, France
  • Sylvain Detey, Waseda University, Japon
  • Walt Detmar Meurers, Universität Tübingen, Allemagne
  • Maxine Eskenazi, Carnegie Mellon University, USA
  • Cédrick Fairon, CENTAL, Université Catholique de Louvain, Belgique
  • Dan Flickinger, LinGO Laboratory, Stanford University, USA
  • Nuria Gala, LIF, Aix-Marseille Université, France
  • Sylviane Granger, CECL, Université Catholique de Louvain, Belgique
  • Natalie Kübler, CLILLAC-ARP, Université Paris Diderot, France
  • Jean-Marc Labat, LIP6, Université Pierre-et-Marie-Curie, France
  • Patrice Pognan, PLIDAM, INALCO, France
  • Mathias Schulze, University of Waterloo, Canada
  • Isabel Trancoso, Instituto Superior Técnico, Portugal
  • Stefan Trausan-Matu, Universitatea Politehnica din Bucuresti, Roumanie
  • Elena Volodina , University of Gothenburg, Suède
  • Virginie Zampa, LIDILEM, Université Grenoble-Alpes, France
  • Michael Zock, LIF, Aix-Marseille Université, France

 

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Georges ANTONIADIS

Professeur d’informatique-linguistique

Directeur du Dpt Sciences du Langage & FLE

Responsable du master Industries de la Langue

UFR LLASIC / Laboratoire LIDILEM

Université Grenoble-Alpes, bâtiment Stendhal

CS 40700

38058 Grenoble cedex 9

Tél. : +33/0 4 76 82 77 61 Fax : +33/0 4 76 82 41 26

Mél. : Georges.Antoniadis@univ-grenoble-alpes.fr

http://lidilem.u-grenoble3.fr/membres/