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Language Teaching Research Quarterly

European Journal of Studies in Management and Business

International Journal of Behavior Studies in Organizations

Studies in Educational Management

New Challenges in Accounting and Finance

Language Testing in Focus: An International Journal

Marketing and Branding Research

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

<p style="text-align: justify;">With the rapid advancement of generative AI technology using large language models, various AI tools have emerged for educational use. Among these tools, ChatGPT has gained traction in second language (L2) writing due to its significant potential as a writing assistant for ESL/EFL learners. This study explored how young EFL students interact with and utilize feedback generated by GPT-4 for their writing. Conducted within the context of developing an automated writing feedback tool to support potential TOEFL Junior Writing test users, this article reports on our small-scale prototyping study, detailing the development of the prototype tool. Building on the extensive work by Carol Chapelle on the use of technology in L2 learning and assessment, our study offers new insights into young EFL students&rsquo; use of generative AI technology in their L2 writing development. The implications of our findings for further research and practice for using generative AI technology in language assessment and learning for young learners are discussed.</p>

ltrq.2025.50.07.pdf

Original Research 

ltrq.2025.50.07    .xml

Language Assessment and Learning through AI Technology: An Exploratory Study on Using GPT for Young EFL Learners’ Writing

Guest-editors: 
Christine Coombe 
Higher Colleges of Technology, Dubai, UAE 
Tony Clark 
Cambridge University Press & Assessment, UK 
Hassan Mohebbi 
European Knowledge Development Institute, Turkey


Special Issue: In Honour of Carol A. Chapelle’s Contributions to Language Assessment and Learning (Volume 50-First Part)

<p style="text-align:justify;">Drawing from a larger CIPP program evaluation (Context, Input, Processes, Products) comprised of 11 analyses of the ETS online teacher training course titled Teaching Academic English with the TOEFL iBT® Test (TAE), this paper triangulates three qualitatively different data sets and seeks to understand how participants responded to the TAE course. The research team considered self-reported data (closed- and open-answer survey questions), engagement data, and learning data. The self-reported data were strongly positive and illustrated the value participants reported having about the course content, especially ETS-created materials. Some gaps were indicated: calls were made for more materials—especially additional resources participants could use when teaching—and for increased interactions during the course workshop. In partial juxtaposition, the engagement data indicated that participants were engaging the course less than anticipated. The learning data simultaneously indicated that some assessments were quite easy for participants while elsewhere participants did not have the desired uptake of some topics. Viewing the three data sets together, the research team arrived at a more nuanced conclusion: despite participant satisfaction, development processes should continue, to ensure the highest quality teacher training program possible, in terms of its content, resources, and interactions.</p>

ltrq.2023.37.15.pdf

ltrq.2023.37.15.xml

Program Evaluation and Triangulation: What Three Data Sets Show about How Participants Respond to the Course Teaching Academic English with the TOEFL iBT® Test

Guest-editors: 
Christine Coombe, PhD, Higher Colleges of Technology, Dubai, UAE
Tony Clark, PhD, Cambridge University Press & Assessment, UK
Hassan Mohebbi, PhD, Independent Researcher, Turkey


Special Issue: In Honour of James Dean Brown’s Five-Decade Contribution to Language Testing