36.1277, Calls: Routledge Handbook of AI and World Language Learning (Jrnl)
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LINGUIST List: Vol-36-1277. Thu Apr 17 2025. ISSN: 1069 - 4875.
Subject: 36.1277, Calls: Routledge Handbook of AI and World Language Learning (Jrnl)
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Date: 15-Apr-2025
From: Chris Shei [C-C.Shei at Swansea.ac.uk]
Subject: Routledge Handbook of AI and World Language Learning (Jrnl)
Journal: Routledge Handbook of AI and World Language Learning
Routledge Handbook of AI and World Language Learning – call for
chapters
Editors: Weixiao Wei and Chris Shei
The Routledge Handbook of AI and World Language Learning will explore
the transformative role of artificial intelligence in language
education, offering a critical and comprehensive analysis of how AI is
expected to reshape the ways languages are taught, learned, and
assessed.
Preliminarily divided into six thematic sections, the handbook will
bridge theory, research, and practice to establish AI-driven language
learning as a rigorous academic field. It is intended to serve as a
vital resource for researchers, educators, ed-tech developers,
policymakers, and postgraduate students.
The section and chapter titles listed below are intended as
illustrative examples. Contributors are invited to adopt similar
titles or propose new ones that reflect their individual research and
expertise. We particularly encourage exploration of world language
learning beyond, though not excluding, English.
Section 1: AI and Language Learning
Foundations of AI in Language Learning
AI-Powered Language Learning Applications
Machine Learning and Second Language Acquisition
AI and Personalized Language Learning Pathways
Adaptive Learning Systems in Language Education
The Role of AI in Informal Language Learning
AI and Language Learning Motivation
Virtual Reality and AI in Language Learning
AI and Multilingual Education
Ethical Considerations in AI-Enhanced Language Learning
Section 2: AI and Language Teaching
AI as a Teaching Assistant: Opportunities and Challenges
AI and Automated Language Instruction
AI-Driven Feedback Mechanisms in Language Teaching
AI and Data-Driven Language Pedagogy
AI for Teacher Training and Professional Development
Chatbots and Conversational AI in Language Instruction
AI-Integrated Blended Learning Approaches
AI in Curriculum and Lesson Planning
Gamification and AI in Language Teaching
AI in Language Teacher Education Programs
Section 3: AI and the Context of Language Learning and Teaching
The Socio-Cultural Implications of AI in Language Learning
AI and Language Learning in Multicultural Contexts
The Role of AI in Language Policy and Planning
AI and the Digital Divide in Language Learning
AI and Equity in Language Education
Ethical AI and Bias in Language Learning Technologies
AI and Language Learning for Migrants and Refugees
AI and Accessibility in Language Learning
The Role of AI in Preserving Endangered Languages
Future Directions in AI and World Language Education
Section 4: AI and Language Testing and Assessment
AI in Language Testing: An Overview
Automated Essay Scoring and
AI-Based Speech Recognition for Language Assessment
Adaptive AI-Driven Language Testing
AI and Standardized Language Proficiency Exams
AI for Diagnostic and Formative Assessment
Bias and Fairness in AI-Driven Language Testing
AI for Feedback and Error Correction in Assessment
The Role of AI in High-Stakes Language Testing
AI and Blockchain in Secure Language
Section 5: AI, Future Trends, and Policy in Language Education
AI and the Future of Language Learning
AI, Language Learning Analytics, and Big Data
AI and Ethical Considerations in Educational Policy
AI-Powered Virtual Teachers and Tutors
The Role of Governments and Institutions in AI and Language Education
AI for Lifelong Language Learning and Workplace Training
AI and Personalized Learning Models in Language Education
AI and Collaboration Between Human and Machine Intelligence
The Role of AI in Enhancing Intercultural Competence
Research Agenda for AI and World Language Learning
Section 6: Developing AI Programs for Language Learning
Designing AI-Powered Language Learning Systems
Natural Language Processing (NLP) in Language Learning
Building Adaptive Language Models for Individual Learners
AI for Pronunciation and Speech Recognition
Machine Learning Techniques for Vocabulary Acquisition
Gamification and AI: Enhancing Engagement in Language Learning
AI-Powered Writing Feedback Systems
Emotional AI in Language Learning: Tracking Learner Sentiment
Data-Driven Insights for Personalized Learning Paths
Ethical Considerations in Developing AI for Language Education
Submission Guidelines:
Proposals should be submitted as an abstract (200-300 words) outlining
the main argument, scope, and structure of the chapter.
The submission should include a brief biography (50-100 words) of the
author(s), highlighting relevant expertise. Maximum Numbers of authors
allowed per chapter: 3.
Proposals should be submitted as soon as possible and no later than
May 15, 2025.
Full chapters (7,000-9,000 words) will be expected by March 1, 2026.
Please send all inquiries and submissions to Dr Chris Shei at
C-C.Shei at Swansea.ac.uk or ccshei at gmail.com.
Linguistic Field(s): Applied Linguistics
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