RPLTL@AILED2026: Special Issue on “Generative AI in Language Education: Pedagogical Innovations and Empirical Insights”

Special Issue on 

“Generative AI in Language Education: Pedagogical Innovations and Empirical Insights”

Guest Editors: 

Dr. Maria Perifanou, SMILE Lab, University of Macedonia and Aristotle University of Thessaloniki

Dr. Athanasios Karasimos, Aristotle University of Thessaloniki

Focus and Scope

Generative Artificial Intelligence (GenAI) is rapidly transforming the landscape of language education by introducing new ways to personalize instruction, facilitate learner engagement, and automate instructional tasks. With the rise of generative tools such as ChatGPT, AI-powered chatbots, and adaptive learning platforms, educators now have the opportunity to create dynamic, learner-centered environments that respond to students’ needs in real time. These technologies are reshaping how students develop language skills, offering real-time feedback, automated support, authentic conversational practice, collaborative learning opportunities, and reduced anxiety in language communication through non-judgmental interaction with AI partners (Crompton et al., 2024; Huang et al., 2023; Kohnke et al., 2023). Among the most promising applications are tools that support speech recognition and pronunciation training, helping learners refine fluency, intonation, and accuracy through immediate, individualized feedback (Belda-Medina & Calvo-Ferrer, 2022). As these tools become more accessible, educators are challenged not only to explore their affordances but also to engage in pedagogical reflection, designing models that embed AI meaningfully into language curricula, ensuring innovations are implemented with intention, inclusivity, and ethical foresight.

GenAI is also playing a growing role in language assessment, with applications that enable automated scoring, adaptive testing, and intelligent analysis of learner performance. While such innovations can enhance the efficiency and precision of evaluation, they also raise important concerns regarding fairness, transparency, and validity. Moreover, the integration of AI tools generates vast amounts of learner data, creating opportunities for data-driven insights into student progress, learning behaviors, and pedagogical effectiveness (Belda-Medina & Calvo-Ferrer, 2022). The potential of AI to inform both formative and summative assessment is immense, but it requires thoughtful implementation, digital literacy among educators, and a strong commitment to learner privacy and autonomy.

This special issue of the “Research Papers in Language Teaching and Learning” journal invites empirical studies, classroom-based investigations, and pedagogical innovations that explore how generative AI can be ethically, effectively, and meaningfully integrated into language education. We especially welcome papers that describe real-world applications, explore teacher and learner perspectives, or present evidence-based practices involving generative AI in instruction, assessment, or data analysis. Submissions that address ethical considerations, innovative teaching strategies, and measurable learning outcomes are particularly encouraged. By fostering a dialogue that bridges technology, pedagogy, and practice, this issue aims to support language educators and researchers in shaping the future of AI-powered language learning with rigor, responsibility, and relevance.

References

Belda-Medina, J., & Calvo-Ferrer, J. R. (2022). Using Chatbots as AI Conversational Partners in Language Learning. Applied Sciences, 12(17), 8427. https://doi.org/10.3390/app12178427 

Crompton, H., Edmett, A., Ichaporia, N., & Burke, D. (2024). AI and English language teaching: Affordances and challenges.  British Journal of Educational Technology, 55, 2503–2529. https://doi.org/10.1111/bjet.13460

Huang, X., Zou, D., Cheng, G., Chen, X., & Xie, H. (2023). Trends, Research Issues, and Applications of Artificial Intelligence in Language Education. Educational Technology & Society, 26(1), 112-131. https://doi.org/10.30191/ETS.202301_26(1).0009

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for Language Teaching and Learning. RELC Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868 

List of Topics

We welcome submissions on topics including, but not limited to: 

• Practical AI Integration in Language Classrooms:

• Empirical studies on the use of AI tools to support language teaching and learning.
• Classroom-based applications of generative AI (e.g., ChatGPT) to enhance student engagement.
• Pedagogical strategies for integrating AI into everyday language instruction.
• Case studies highlighting teacher and learner experiences with AI-powered tools.

• Developing Core Language Skills with AI:

• Using AI to support writing, listening, speaking, reading, and vocabulary development.
• AI-driven tools for pronunciation and fluency practice.
• Interactive speaking activities using chatbots or virtual language partners.
• The role of AI in supporting grammar, syntax, and language accuracy.

• Language Teaching Resources and Content Creation:

• Using AI to generate or adapt instructional materials and exercises.
• Teacher-designed activities that leverage AI-generated prompts, tasks, or models.
• Evaluating the appropriateness and accuracy of AI-generated content for different learner levels.

• Language Assessment, Feedback, and Learning Insights:

• AI-supported formative and summative assessment in language learning.
• Personalized feedback from AI tools: benefits, limitations, and teacher mediation.
• Tracking learner progress and outcomes using data from AI-enhanced systems.
• Reflections on validity, reliability, and classroom utility of AI assessments.

• Ethical, Inclusive, and Reflective Practice:

• Ensuring ethical use of AI in classroom contexts (e.g., privacy, bias, authorship).
• Supporting language teachers’ digital and AI literacies.
• Designing inclusive and equitable language learning experiences with AI.
• Critical reflections on the impact of AI tools on learner autonomy and motivation.

Publication Schedule

Submission Guidelines

Double-blind review process:

Submissions should be original and not previously published. All papers submitted to this special issue will be reviewed through a double-blind review process, meaning that authors’ names are not disclosed to the reviewers, and reviewers’ names are not disclosed to the authors.

For this purpose, authors must submit their manuscript:

• without any reference to themselves and their institutions;
• without any URLs to projects, products, or self-developed systems;
• with relevant self-references blinded or written in the third person.

Manuscript types: 

1. Empirical Research Papers (5000-6000 words) 

2. Discussion Papers or Theoretical Papers (4000-5000 words) 

Please feel free to contact the guest editors at the above address if you have any questions about the issue. 

Preparing Your Submission:

All authors must consult RPLTL's authors’ guidelines. 

Upload your submission to the special issue EasyChair submission system (https://easychair.org/conferences/?conf=ailed2026_rptl) before the official deadline (20 August 2025, 23:59 CET).

About the Journal

Research Papers in Language Teaching and Learning (RPLTL) is a peer-reviewed electronic journal dedicated to publishing research in the domains of TESOL (Teaching English to Speakers of Other Languages) and Applied Linguistics.

Its mission is two-fold:(a) to promote efficient dissemination of the best of the research that is carried out by students and graduates of the M.Ed. in TESOL of the Hellenic Open University, and(b) to facilitate academic exchange between the students and faculty of that programme and members of the wider professional and academic community on a world-wide basis.

The official languages of the journal are English and Greek.

All articles in this Journal are published under the Creative Commons License Deed, Attribution 3.0 Unported (CC BY 3.0)

Contact

For this special issue, please submit your inquiries directly to the guest editors:

Dr. Maria Perifanou: mariaperif@gmail.com

Dr. Athanasios Karasimos: akarasimos@enl.auth.gr