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Language Teaching Research Quarterly

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Individual Differences in Language Education: An International Journal 

Feedback Research in Second Language 

Management Issues in Healthcare System

Language Teacher Education Research

Artificial Intelligence Knowledge Development

The paper examines the effects of task structure and task immediacy in attentional allocation in the process of engaging with (L2) speech production among international learners of English as an additional language (EAL) in Canada. In a series of four experimental conditions (structural support (structured vs. unstructured)) and immediacy (Here/Now), sixty B2 learners were asked to complete a narrative task. There/Then). Participants provided retrospective verbal reports to establish the sources of dysfluency in their speech. There are four processing stages: conceptualization, lexical encoding, syntactic encoding, and phonological encoding, which were based on the model of speech production proposed by Levelt to code the dysfluency markers. The findings indicated that unstructured tasks produced more pauses associated with conceptualization, suggesting greater requirements for message planning. Conversely, There/Then condition tasks, especially with structural support, had many more dysfluencies that were lexical, syntactic, and phonological encoding in nature, indicating increased focus on the linguistic form. The large effect size across conditions indicates that task design strongly influenced the allocation of attentional resources. Most notably, structured narratives in the past tense, without contextual support, significantly heightened attention to form, as evidenced by increased pauses during lexical, syntactic, and phonological encoding.

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Original Research 

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The Impact of Task Structure and Immediacy on International EAL Learners’ Attention Orientation During Speech Production

Although the literature has recently recognised the significance of suprasegmental features in L2 English perception and production, nuclear accent (NA) placement remains partly terra incognita (Landblom &amp; Ionin, 2022; Nagle &amp; Baese-Berk, 2022). Thus, this study examined the extent to which Spanish L1 learners of English can perceive and produce English NA placement. A total of 53 participants completed NA placement perception (listening and identification) and production tasks based on utterances in unmarked and marked contexts. Also, the role of L2 aptitude, musical ability, and L2 proficiency was analysed using three standardised tests: the Modern Language Aptitude Test (MLAT), the Musical Ear Test (MET), and the Cambridge Placement Test. The results indicate that L2 aptitude was a weak predictor, whereas musical ability, specifically rhythm sensitivity, strongly predicted NA placement perception accuracy across the different sentence types. This effect was positively moderated by English proficiency. The study deepens our understanding of the perception-production link and supports the inclusion of prosodic training in L2 English acquisition.

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On English Language Learners’ Prosody: The Possible Impact of L2 Aptitude, Musical Ability, and Proficiency on Nuclear Accent Placement in Spanish L1 Contexts

<span style="font-size: 12.0pt; font-family: 'Book Antiqua',serif; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-no-proof: yes;">Under Taiwan&rsquo;s Bilingual 2030 policy, the expansion of bilingual education has created new instructional roles in schools, yet the lived experiences of teaching assistants remain underexplored. This study adopts an interpretivist approach to understand how one teaching assistant made sense of her experience in Taiwan&rsquo;s English Language Teaching Assistant (ELTA) program. Using a qualitative single-case design, the study draws on a semi-structured interview to explore how the participant interpreted her role in practice. The findings suggest that she came to understand her work as extending beyond assistance into substantial classroom involvement, including lesson preparation, instructional engagement, and ongoing adaptation. They also indicate that digital support, including generative artificial intelligence, became an important practical resource in helping her manage the demands of the role. Rather than making broader claims beyond the case, this study offers a closely contextualized account of how one participant understood and gave meaning to her work, while inviting closer consideration of how teaching assistantship may be experienced in particular bilingual education settings.

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Research Article

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Beyond Assistance: A Case Study of a Teaching Assistant in Taiwan’s English Language Teaching Assistant (ELTA) Program

<span style="font-size: 12.0pt; font-family: 'Book Antiqua',serif; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-no-proof: yes;">The application of artificial intelligence (AI) in language education has become one of the most significant topics in the field of teaching English as a foreign language (Kashef &amp; Khabazian, 2026; Ke et al., 2026). In language teaching, AI is a helpful tool that can aid instructors in personalizing their lessons, but its real assistance only happens when EFL instructors have digital literacy and know how to use it wisely (Yang &amp; Lou, 2026). As digital tools like ChatGPT and DeepSeek have become increasingly accessible, language instructors and teacher educators are facing some questions about how these technologies might change their practice (Gribiea, 2026). Rod E. Case, Leping Liu, and Joseph Mintz have gathered together a valuable collection of studies in their book titled Integrating Artificial Intelligence Technology into Language Teacher Education, which originally appeared as a special issue of Computers in the Schools.

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Book Review

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Book Review: Integrating Artificial Intelligence Technology into Language Teacher Education, Edited by Rod E. Case, Leping Liu, Joseph Mintz (Routledge, 2025)

<span lang="EN-GB" style="font-size: 12.0pt; font-family: 'Book Antiqua',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi; mso-ansi-language: EN-GB; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Standard language teacher education (LTE) programs have mainly prioritized technical skills, focusing on practical aspects such as curriculum design, classroom management, and instructional techniques. Although these elements contribute to the teacher&rsquo;s professional development, they often leave sociocultural and ideological factors underexplored. Foundational elements within training programs, including teachers&rsquo; professional identity, the role of mother tongue, and broader views of culture, are often overlooked as the programs prioritize step-by-step instruction. Furthermore, hierarchical institutional systems frequently restrict teachers&rsquo; pedagogical autonomy and embed them within broader frameworks of monitoring and evaluation (Uysal &amp; Gao, 2026). To address these shortcomings, Jaber Kamali&rsquo;s Language as Power in the Language Teacher Education Ecosystem (2026) responds to these gaps by highlighting language as a central domain where authority and professional expectations are negotiated within the LTE ecosystem.

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Book Review: Language as Power in the Language Teacher Education Ecosystem, by Jaber Kamali (Cambridge University Press, 2026)

This article argues for a reframing of AI literacy in MA TESOL education from a compliance-driven competency to a co-constructed process of inquiry, reflection, and critical engagement. The discussion is prompted by a classroom activity in which an AI-generated annotated bibliography, which contained entirely fabricated references, was initially judged by postgraduate students to be credible and academically appropriate. Whilst the exercise exposed challenges associated with verifying AI-generated academic content, it also highlighted broader questions about how AI literacy is conceptualised and developed within TESOL. Drawing on thematic analysis of interviews with two international MA TESOL students, the study explores how students understand, use, and evaluate AI following institutional guidance and targeted classroom input. Findings reveal emerging but cautious forms of AI literacy characterised by scepticism, risk awareness, verification practices, and anxiety regarding plagiarism and academic integrity. Despite explicit instruction, participants positioned AI primarily as a source of potential error rather than as a pedagogical resource. This article therefore proposes a co-constructed model of AI literacy that values dialogue, shared inquiry, scaffolded experimentation, and process-oriented assessment that enables students to develop reflective, context-sensitive, and professionally relevant AI practices.

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Practitioner Inquiry

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Reframing AI Literacy in MA TESOL Education as Co-Constructed

The present study investigates how pre-service and in-service primary EFL teachers in Germany consider individual differences (IDs) when making long- and short-term planning decisions. Participants were presented with two vignettes designed to initiate prospective reflection processes typical of (professional) planning. The resulting written reflections were analyzed alongside qualitative content analysis with a focus on the nature and degree of learner referencing. Results indicate that learner references were predominantly generic, while differentiated references occurred less frequently. When differentiation was present, it was primarily performance-based. Although references to ID dimensions appeared comparatively rarely and unsystematically, they addressed a broad variety of ID dimensions. The study discusses the implications of these findings for teacher education, arguing for more structured and supported opportunities to practice knowledge-based, heterogeneity-sensitive prospective reflection.

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“All Learners will Enjoy this!” The (Limited) Integration of Individual Differences in Primary EFL Teachers’ Task Planning

The rapid advancement of digital technologies has transformed language assessment in the past several decades, bringing both benefits and challenges for second language (L2) teachers, who need to advance their language assessment literacy (LAL) in response to the drastic changes. In this reflective essay, drawing on ancient Chinese philosophy, particularly the Shu (the Technique) and Dao (The Way) binary, I first narrate my LAL development from 2010 to 2022, from a pre-service teacher to an in-service teacher-assessor, by emphasizing how my assessment practices (Shu) have changed in response to digital technologies. Then, I reflect on the unchanging Dao of my LAL crystallized during my PhD studies from 2022 to 2025 as a teacher-researcher investigating teachers&rsquo; LAL, namely, using language assessment to achieve students&rsquo; holistic development. Finally, I advocate a vision in which L2 teachers can respond to the constantly evolving technological environment by grounding their future technology-assisted assessment practices in the unchanging principles of the Dao through human-AI collaboration.

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Perspective Article

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“Respond to Change with the Unchanging”: A Second Language Teacher’s Reflective Journey in Transforming Language Assessment Literacy in the Digital Era

Guest-editor: 
Hassan Mohebbi 
European Knowledge Development Institute, Turkey

Special Issue:  Language Assessment Literacy in the New Era: New Concerns, Same Solutions?

Inspired by Coombe et al.&rsquo;s (2020) conceptualization of Language Assessment Literacy (LAL) as a recursive process of learning, unlearning, and relearning, we reflect on how teachers&rsquo; LAL is socially and technologically mediated in using DeepSeek&rsquo;s DeepThink function. Through reflective analysis of Wenwen&rsquo;s supervisory interactions with her MA student in China, and Steve&rsquo;s in-service teacher education practices in Cambodia, this reflective paper contributes to the discussions about LAL in the age of AI. We present our successes and failures with promoting the use of AI as a tool for the development of LAL in teachers and learners. Our experiences with LAL and AI are framed in Coombe et al.&rsquo;s (2020) recursive cycle of LAL development.

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DeepThink-Mediated Language Assessment Literacy: EFL Teachers’ Practices and Insights from China and Cambodia

This paper explores the construct of Language Assessment Literacy in Vietnam. A mixed methods approach was adopted to understand the classroom-based assessment practices of English language teachers at all stages of education. Classroom observations with follow up interview, focus group discussions and a survey were the methods deployed to understand the teachers&rsquo; assessment practices, their attitudes towards assessment and the challenges they encountered when assessing their students. The results revealed that the teachers used a range of assessment practices, and they were able to clearly articulate the rationale for the chosen practices. The teachers used the results of the assessments to inform their teaching decisions and lesson planning. Based on the range of assessment practices observed and discussed the participant teachers demonstrated high levels of Language Assessment Literacy. They were able to implement competence-based assessment which was a feature of a recent nationwide curriculum reform project. The challenges faced by the teachers included large class sizes, heavy teaching load and, for teachers in rural areas, resourcing issues. The teachers expressed a strong desire to have more autonomy in their teaching and assessment practices and for the teacher voice to be given greater weight when considering and implementing curriculum reform.

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Language Assessment Literacy in Vietnam: Practices, Attitudes and Challenges

This paper integrates the discussion of current digital innovations, their uses for academic writing instruction, and its implication for language assessment. Using the revisited New Literacy Studies (NLS) framework (Pegrum et al., 2018, 2022), I suggest considering a structural organization to guide practices of academic writing and their assessment: A typology of AI-Assisted Writing that includes Original, Augmented, and Synthetic texts. By connecting digital literacy studies to seminal work on textual typology (Reiss, 1970, 1989), this reflection calls for interdisciplinary discussion and the use cross-curricular approaches to align educational policies for AI-assisted writing in language assessment practices. The suggested frames serve as pedagogical anchors to ignite ideas on meaningful classroom design environments, but also as points of departure for the construction of professional development plans and teacher language assessment literacy programs that address current skills and principles when LLM-based writing steps as a disruptive tool in academic writing. The paper closes with a conclusion in the line of promoting studies that embedded digitally mediated strategic academic literacy informed by empirical evidence from diverse classrooms and across stages of Language Assessment Literacy that stakeholders may have.

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Textual Typologies for AI-Assisted Writing: Integrating New Literacy Studies and Language Assessment Practices

Language Assessment Literacy (LAL) has long been central to teachers&rsquo; professionalisation, yet the field has given relatively little attention to digitalisation. The rapid emergence of generative AI in language teaching and assessment now compels a reconceptualisation of teacher LAL to incorporate AI related knowledge, skills and ethical awareness. This paper maps key affordances&mdash;automated item generation, scalable scoring, and timely individualised feedback&mdash;alongside critical challenges including overreliance, academic integrity threats, bias, data protection and equity concerns. It argues that teachers require prompting skills, critical evaluation of AI output, understanding of automated scoring systems, and pedagogical strategies to redesign assessments, and that these competences must be embedded in initial and in service teacher education. Sustainable implementation demands coordinated action by policymakers, researchers, test developers, teacher educators and school leaders to provide localised frameworks, professional development, and time for practice. New conceptions of teacher LAL have to integrate a dynamic AI component, with AI literacy and related requirements representing a moving target and LAL levels being underdeveloped in many educational contexts.

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Generative AI Technology and Teacher Language Assessment Literacy – Can Language Teachers Keep up?