LINGUIST List 35.2582

Mon Sep 23 2024

Calls: Applied Linguistics, Computational Linguistics/ CALICO - "Artificial Intelligence in Language Learning and Assessment" (Jrnl)

Editor for this issue: Erin Steitz <ensteitzlinguistlist.org>



Date: 21-Sep-2024
From: Bryan Smith <bryansmithasu.edu>
Subject: Applied Linguistics, Computational Linguistics/ CALICO - "Artificial Intelligence in Language Learning and Assessment" (Jrnl)
E-mail this message to a friend

Call for Papers
Thematic Issue on Artificial Intelligence in Language Learning and Assessment
CALICO Journal 43.3, October 2026

This thematic issue seeks to deepen our understanding of how AI technologies, particularly machine learning and natural language processing (NLP), can enhance language education and impact learner outcomes. We invite original, methodologically rigorous, and empirically sound studies that focus on learner outcomes and demonstrate how AI tools, especially NLP tools powered by large language models, can be strategically employed to meet the evolving demands of language education.

While much of the current research on AI in education has focused on the capabilities and perceptions of these tools, this issue aims to shift the focus toward their tangible effects on learning outcomes and pedagogical practices. With the rise of LLM technologies, language educators have an unprecedented opportunity to reshape instructional methods. We are seeking studies that provide evidence-based insights into the use of such AI applications for achieving language learning goals and improving learner performance.

We welcome contributions that examine the use of NLP tools across various skill areas, including learner engagement, comprehension, proficiency (both written and spoken), and pragmatic development. Studies that specifically explore how LLM-powered NLP applications can be used and combined most effectively (also with other resources) to serve the established learning goals are particularly encouraged (see Chun, Kern, and Smith’s (2016) heuristic #3). Additionally, we seek research on the efficacy of NLP applications in supporting autonomous language learning and how learners interact with these tools. Submissions employing qualitative, quantitative, or mixed methods approaches are welcome. Please note that studies based solely on surveys or questionnaires will not be considered.

Potential areas of focus include, but are not limited to:
● AI for accessibility and support for learners with special needs
● AI tools in collaborative language learning environments
● AI-assisted learning in multilingual contexts
● Autonomous or extramural language learning through AI
● Construction and use of small-language model (SLM) tools in language education
● Development of AI-augmented teaching materials
● Enhancing instructional practices with LLMs
● Learner agency in using AI for language development
● Redefining the role of the teacher in AI-supported classrooms
● Teacher training and professional development in AI integration
● The role of LLMs in L2 assessment
The editors invite expressions of interest for potential inclusion in the thematic issue by October 30th, 2024. Invitations for full manuscripts will be sent to authors by November 15th, 2024. Full manuscripts will be due to the editors on October 15th, 2025. All manuscripts will be double-blind peer-reviewed. Please send your expression of interest to [email protected].

Submission Guidelines for Expressions of Interest:
Title: A provisional title for the proposed manuscript.
Abstract: A brief abstract (250–300 words) outlining the scope, aims, methodology, and potential contribution of the research.
Key Contributions: A statement (1–2 sentences) summarizing the unique contributions the manuscript is expected to make to the field of CALL.
Keywords: Include up to five keywords.
Author Information: Names, institutional affiliations, and contact details of the author(s).

Chun, D. M., Kern, R., & Smith, B. (2016). Technology in language use, language teaching, and language learning. The Modern Language Journal, 100(S1), 64–80. https://doi.org/10.1111/modl.12302




Page Updated: 23-Sep-2024


LINGUIST List is supported by the following publishers: