Editors
Dr. Wong Wei Lun
Professor Jessie Barrot
Special Issue Overview
Applied Language Sciences invites submissions for a special issue on Assessment and Feedback in the Age of CALL and Generative AI. The rapid development of computer-assisted language learning (CALL) and generative artificial intelligence has begun to reshape assessment and feedback practices across applied language education. AI-enabled tools now support a wide range of pedagogical functions, including formative assessment, automated and semi-automated feedback, writing evaluation, speaking support and learner performance monitoring. These developments create new possibilities for timely, personalised and scalable pedagogical support. At the same time, they raise pressing concerns about validity, fairness, transparency, reliability, learner authorship, teacher agency and academic integrity. Within language education, assessment and feedback are no longer confined to traditional humanled practices. Teachers and learners increasingly interact with AI-mediated systems that generate comments, suggest revisions, evaluate performance and influence learning behaviours. Such changes require careful scholarly attention from practical and pedagogical perspectives. There is a growing need for research that does not merely discuss the promise or risk of AI in abstract terms, but instead examines how CALL and generative AI are being implemented, interpreted, negotiated and managed in real educational contexts. This special issue seeks to bring together empirical, practice-oriented and theoretically informed scholarship that investigates how assessment and feedback are being reconfigured in the age of CALL and generative AI. We particularly welcome submissions that engage with classroom realities, teacher decision-making, learner experiences, responsible design, and contextsensitive implementation across diverse educational settings.
Aims of the Special Issue
This special issue aims to:
• examine how CALL and generative AI are transforming assessment and feedback in language education;
• explore practical and pedagogically meaningful uses of AI in formative and summative language assessment;
• investigate the implications of AI-mediated feedback for teaching, learning, and assessment literacy;
• address ethical, institutional, and disciplinary concerns surrounding validity, trust, fairness, and academic integrity;
• foreground context-sensitive research that offers clear implications for teachers, researchers, curriculum developers, and teacher educators.
Suggested Topics We invite original manuscripts addressing, but not limited to, the following themes:
• AI-supported formative assessment in language classrooms
• AI-generated feedback in second or foreign language writing
• AI-assisted speaking assessment and oral feedback
• Feedback literacy in AI-supported learning environments
• Human–AI feedback comparison studies
• Responsible and ethical use of generative AI in classroom assessment
• Academic integrity and the redesign of language assessment tasks
• Teacher agency in mediating AI-generated feedback
• Learner trust, perceptions, and uptake of AI feedback
• Validity, fairness, and transparency in AI-enhanced assessment
• Automated and semi-automated evaluation in applied language education
• Assessment redesign in response to generative AI
• AI-supported rubric development and scoring practices
• Teacher education and professional development for AI-informed assessment
• Context-sensitive, localised, or low-resource approaches to AI-supported feedback and assessment
• Policy, governance, and institutional responses to AI in language assessment
• Critical perspectives on responsible AI integration in CALL-based assessment Types of Contributions
We welcome submissions employing a wide range of methodological and analytical approaches, including:
• quantitative studies
• qualitative studies
• mixed-methods research
• classroom interventions
• case studies
• action research
• design-based research
• systematic or scoping reviews
• conceptual or position papers with strong pedagogical relevance Submissions may focus on school, higher education, teacher education, professional learning, or informal and self-directed language learning contexts.
Submission Guidelines
Authors are invited to submit original, unpublished manuscripts that are not under consideration elsewhere. All submissions must align with the aims and scope of Applied Language Sciences and will undergo the journal’s standard double-anonymous peer review process. Manuscripts should be prepared in accordance with the journal’s author guidelines, including formatting, referencing style, word limit, and ethical requirements.
Important Dates •
Full manuscript submission deadline: 30 December 2026
• Expected publication of the special issue: 2027
Editorial Statement
This special issue is motivated by the growing need to understand how AI-mediated technologies are reshaping assessment and feedback in applied language education. Although the field has witnessed substantial interest in generative AI, there remains a clear need for research that is grounded in authentic educational practice and that addresses the pedagogical, ethical, and institutional complexities of implementation. This issue therefore prioritises contributions that move beyond technological novelty and instead examine how responsible, meaningful, and contextually appropriate uses of CALL and AI can be developed in language education. The guest editors welcome papers that offer strong pedagogical implications, methodological rigour, and critical insight into the changing relationship between teachers, learners, feedback practices, and assessment systems. Through this collection, the special issue aims to contribute to ongoing debates in CALL and applied linguistics while also supporting more informed and responsible educational practice.
Guest Editors
Dr. Wong Wei Lun Faculty of Education, Universiti Kebangsaan Malaysia colinw@ukm.edu.my
Dr. Wong Wei Lun is a senior lecturer at the Faculty of Education, Universiti Kebangsaan Malaysia (UKM). His expertise includes TESL, applied linguistics, corpus linguistics, computerassisted language learning and AI-mediated language education. He has authored and co-authored over 40 scholarly publications in SSCI, SCIE, ESCI and Scopus-indexed journals, and currently serves as Academic Editor of PLOS ONE and Special Issue Co-Editor of the International Journal of TESOL Studies. He is also an active reviewer for numerous high-impact international journals and leads funded projects on corpus-based pedagogy and generative AI in language education. His work focuses on second language writing, learner corpora, digital pedagogy, teacher education and technology-enhanced language learning.
Professor Jessie Barrot National University, Philippines jessiebarrot@yahoo.com
Jessie Barrot is a Professor and Vice President for Research and Development at the National University, Philippines. He is recognised as one of the World’s Top 2% Researchers by Stanford University in partnership with Elsevier in both the single-year (2023 to 2025) and career-long categories (2025). In single-year category, he is currently in the Top 0.1%. As a distinguished scholar, Dr. Barrot has published over 100 papers in leading journals on linguistics and education, serves as a reviewer for over 160 SSCI/Scopus-indexed journals, scholarly books and conferences, and sits on the editorial boards of prominent publications like RELC Journal, Reading & Writing Quarterly, Computer Assisted Language Learning, TESOL Quarterly, and Assessing Writing, and Journal of English for Academic Purposes. His outstanding contributions have earned him several international accolades and numerous invitations a research fellow or visiting scholar at esteemed universities worldwide. He has also delivered over 260 lectures in workshops, seminars, and conferences across the Philippines and internationally.