37.1031, FYI: Call for Chapters | Data-Driven Language Teaching and Learning: Theory, Research, and Practice (Springer)

[The LINGUIST List]

LINGUIST List: Vol-37-1031. Fri Mar 13 2026. ISSN: 1069 - 4875.

Subject: 37.1031, FYI: Call for Chapters | Data-Driven Language Teaching and Learning: Theory, Research, and Practice (Springer)

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Date: 12-Mar-2026
From: Cansu Akan [cansu.akan at phil.tu-chemnitz.de]
Subject: Call for Chapters | Data-Driven Language Teaching and Learning: Theory, Research, and Practice (Springer)


We are pleased to announce an upcoming edited volume on "Data-Driven
Language Teaching and Learning: Theory, Research, and Practice", to be
published by Springer. With this email, we warmly invite chapter
proposals from researchers, teacher educators, curriculum designers,
and practitioners working across corpus linguistics, applied
linguistics, language education, and educational technology.
TOPIC OVERVIEW
Data-Driven Learning (DDL), first introduced by Tim Johns (1991) as a
method of classroom concordancing, has evolved considerably over the
past three decades. Despite a substantial body of empirical evidence
supporting corpus-based approaches for raising learner awareness,
developing language autonomy, and supporting inductive learning, a
persistent gap remains between research-based insights and everyday
instructional decision-making.
This volume addresses this gap directly. Through empirically grounded
contributions, it demonstrates how data can be used to support
instructional design, materials development, classroom interaction,
and assessment -- enabling more informed and transparent pedagogical
choices without requiring advanced technical expertise. By adopting a
cross-contextual and language-independent perspective, the volume
identifies transferable principles applicable across a wide range of
teaching settings.
We invite chapter proposals addressing topics including, but not
limited to:
- Corpus-based and data-driven approaches to language teaching,
learning, and assessment
- Data-informed instructional design and materials development
- Classroom applications of DDL across educational levels and language
learning contexts
- Learner engagement with corpus tools and concordancing tasks
- AI-assisted feedback, adaptive learning platforms, and intelligent
tutoring systems in DDL contexts
- Learner corpus research and its implications for pedagogy
- Teacher education and professional development through data-informed
practice
- Digital tools, corpus technologies, and blended or online learning
environments
- Challenges and affordances of implementing DDL in multilingual or
under-resourced settings
- Theoretical and methodological frameworks for data-driven language
pedagogy
- Cross-contextual and comparative studies of data-informed teaching
HOW TO CONTRIBUTE
The volume operates a two-stage submission process.
Stage 1 - Abstract Submission
Prospective contributors are invited to submit an abstract of 400-600
words by 1 May 2026. Abstracts should include:
- Title and full names and institutional affiliations of all
contributors
- A clear statement of the chapter’s focus, argument, research
questions, and main contribution
- The theoretical and/or empirical approach to be employed
- The educational context, data, or corpus under investigation (if
applicable)
- The chapter’s relevance to the volume’s overarching themes
- A short bibliography of key references (not counted in the word
limit)
Stage 2 - Full Chapter Submission
Authors of accepted abstracts will be invited to submit full chapters
of 7,000-9,000 words (including references) by October 2026. All full
chapters will undergo double-blind peer review. Authors will receive
detailed reviewer feedback and will be asked to revise and resubmit
accordingly.
IMPORTANT DATES
Abstract submission deadline:     1 May 2026
Notification of outcome:          Within three weeks of deadline
Full chapter deadline:            October 2026
Please submit your abstract by email to the corresponding editor,
using the subject line: Chapter Proposal - Data-Driven Language
Teaching and Learning.
For questions related to the volume’s scope, submission guidelines, or
any other matter, please do not hesitate to contact the editors.
We look forward to receiving your proposals!
Mehrdad Vasheghani Farahani (Corresponding Editor)
submittingpapers at yahoo.com
Cansu Akan
Chemnitz University of Technology, Germany
cansu.akan at phil.tu-chemnitz.de
Sepideh Javdani Esfahani
Chemnitz University of Technology, Germany
sepideh.javdani-esfahani at phil.tu-chemnitz.de

Linguistic Field(s): Applied Linguistics
                     Computational Linguistics
                     Language Acquisition
                     Text/Corpus Linguistics




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