Artificial Intelligence

CALL FOR PAPERS — SPECIAL ISSUE STUDI DI GLOTTODIDATTICA

The role of Artificial Intelligence in EFL contexts: future prospects and entAIlments Editors: Gaetano Falco, Maristella Gatto, Francesco Meledandri https://ojs.uniba.it/index.php/glottodidattica/call_papers The rapid development of Artificial Intelligence (AI) has begun to reshape educational practices across disciplines, with language teaching and learning emerging as a particularly fertile field for innovation. Over the past decade, research has documented the growing use of digital and AI-driven tools such as intelligent tutoring systems, automated feedback and assessment, speech recognition technologies, adaptive learning platforms, and chatbots (Luckin et al., 2016; Chen et al. 2020; Ouyang & Jiao, 2021; Burudi et al., 2024). More recently, generative AI has expanded the range of possibilities by enabling dynamic content creation, personalized interaction, and real-time linguistic support based on the huge potential offered by Large Language Models (LLMs) (Kohnke et al., 2023). In language education, AI applications have been shown to influence key areas such as learner autonomy, motivation, pronunciation training, vocabulary development, writing support, and formative assessment. Studies have also highlighted the potential of AI to facilitate differentiated instruction and data-informed pedagogical decision-making (Ya, 2025). Yet, some issues have been part of the debate about the relationship between AI and learning environments, focusing not only on possible cognitive loss and decrease in critical thinking abilities (Kosmyna et al. 2025; Gerlich 2025), but also on questions regarding ethical considerations, data privacy, bias, transparency, teacher agency, and the pedagogical reliability of AI-mediated practices (e.g., Holmes et al., 2019; Sousa and Cardoso, 2025; Wang et al., 2025). Despite the growing body of research, the field is still evolving, and there remains a need for both theoretically and empirically grounded, practice-oriented studies that examine how AI solutions are actually being integrated into language teaching contexts. Considering the role of English as a lingua franca in both research and educational settings (particularly focusing on English as a Foreign Language, EFL), and the impact of AI-mediated solutions in English language learning environments (Guzmán Alvarado and Naranjo Andrade, 2025) this special issue seeks to contribute to this discussion by bringing together diverse perspectives on the design, implementation, evaluation, and critical examination of AI-based practices in EFL educational settings. Against this background, the primary aim of this special issue is to explore how AI solutions are being used, adapted, and conceptualized in language teaching practices across EFL educational contexts, determining AI’s role in contemporary and future language teaching practices. The issue seeks to: 1. Examine empirical evidence on the effectiveness and limitations of AI tools in language teaching and learning. 2. Investigate pedagogical models and instructional strategies that meaningfully integrate AI into language education. 3. Explore teachers’ and learners’ perceptions, beliefs, and experiences regarding AI-supported language learning. 4. Critically address ethical, social, and epistemological issues arising from the use of AI in language teaching. 5. Bridge the gap between research, policy, and classroom practice by highlighting innovative, reflective as well as fair and ethical uses of AI. We invite original research articles, theoretical papers, systematic reviews, and practice-based studies addressing, but not limited to, the following themes: • AI-supported language learning and teaching models • Intelligent tutoring systems and adaptive learning in language education • Generative AI (e.g., large language models) for writing, speaking, and interaction • Automated feedback and assessment of language skills • AI and pronunciation, speech recognition, and listening comprehension • Teacher roles, professional development, and AI literacy • Learner agency, motivation, and engagement in AI-mediated environments • Ethical issues, data privacy, bias, and transparency in AI-driven language education • Equity, accessibility, and inclusion in AI-supported language learning • Classroom-based studies and design-based research on AI integration Both qualitative and quantitative methodologies, as well as mixed-methods approaches, are welcome. Submission of proposals Authors wishing to send a contribution are invited to send a proposal (max. 350 words, excluding references) in English to gaetano.falco@uniba.it, maristella.gatto@uniba.it, and francesco.meledandri@uniba.it by April 15, 2026. Notification of acceptance will be sent by April 30, 2026. If accepted for this special issue, final contributions shall not exceed 35,000 characters and shall be sent in an editable format (e.g. Microsoft Word and/or Open Office, preferably in .doc/.docx or .odt) by July 31, 2026. Please refer to the Journal’s Author Guidelines for further information about text length, formatting and reference format. References Burudi S.W., Mugun D. J., Karani G.G.O., Cheptabok M.C., Lihanda M.A. 2024. Integration of Smartphone as an Instructional Resource in Enhancing Teaching of English Grammar. Open Access Library Journal, Volume 11, e12554. https://doi.org/10.4236/oalib.1112554 Chen L., Chen P, and Lin, Z. 2020. Artificial intelligence in education: A review. IEEE Access 8: 75264–75278. Gerlich M. 2025. AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15, 6. https://doi.org/10.3390/soc15010006 Guzmán Alvarado M.V., and Naranjo Andrade S.S. 2025. The Impact of Artificial Intelligence on English Language Learning: A Systematic Review of Tools, Methods, and Outcomes in Language Skills. Runas, Volume 6, no. 12, e250287. https://doi.org/10.46652/runas.v6i12.287 Holmes W., Bialik M., and Fadel C. 2019. Artificial intelligence in education: Promise and implications for teaching and learning. Boston, MA: Center for Curriculum Redesign. Kohnke L., Moorhouse B. L., and Zou D. 2023. ChatGPT for language teaching and learning. RELC Journal, 54(2), 367–371. Kosmyna N. et al. 2025. Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. arXiv:2506.08872. https://doi.org/10.48550/arXiv.2506.08872 Luckin R., Holmes W., Griffiths M., and Forcier L. B. 2016. Intelligence unleashed: An argument for AI in education. London: Pearson Education. Ouyang F., and Jiao P. 2021. Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020 Sousa A. E., and Cardoso P. 2025. Use of Generative AI by Higher Education Students. Electronics 14/1258. DOI: 10.3390/electronics14071258 Wang F., Li N., Cheung A.C.K., and Wong G.K.W. 2025. In GenAI we trust: An investigation of university students’ reliance on and resistance to generative AI in language learning. International Journal of Educational Technology in Higher Education 22/59. DOI: 10.1186/s41239-025-00547-9 Ya B. 2025. Exploring the role and impact of artificial intelligence in personalized foreign language teaching. Discover Artificial Intelligence, Volume 5, 318.

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Call for Papers for the 8th International Translation Symposium University of Palermo, 23–24 April 2026 Artificial Intelligence and Audiovisual Translation: Challenges and New Horizons

Artificial Intelligence (AI) has become a transformative force across domains, reshaping professional practices, academic debates, and user experiences. Audiovisual Translation (AVT), with its multimodal and interdisciplinary nature, stands at the forefront of this transformation. AI-driven tools such as automatic speech recognition, machine translation, text-to-speech systems, synthetic voices and AI dubbing, among others, are redefining how AVT is conceived, produced, and consumed, from dubbing and subtitling to audio description (AD), subtitling for people who are d/Deaf or hard-of-hearing (SDH), voiceover, and live subtitling. The connection between AI and AVT is now central not only to advancing research, but also to forging sustainable ties with the AVT industry. Cloud-based platforms, automated workflows, and AI-enhanced translation environments are revolutionising professional practice while reshaping student training. Preparing the next generation of audiovisual translators requires embedding AI literacy, practical competence, and industry collaboration into curricula to ensure a smooth transition into the professional world. This conference invites scholars, students, practitioners, and industry stakeholders to explore, critically and concretely, the synergies and tensions between AI technologies and AVT. We aim to assess the state of the art, interrogate emerging challenges, and envision the future of AVT in a world increasingly shaped by automation and algorithmic mediation. Particular attention will be devoted to practical applications not only in the media and entertainment industries (film, television, streaming platforms, gaming), but also in the arts and cultural heritage sectors, such as museums, galleries, and live performance, where AI-enhanced AVT practices are opening unprecedented avenues for accessibility and cultural engagement. Focus will be also on the origins of the earliest chat systems within audiovisual and cinematic products. We welcome studies and research that foreground the historical significance of chats both as a digital tool and a writing/narrative device within audiovisual texts. Suggested themes include, but are not limited to:– AI in dubbing and voiceover: neural speech synthesis; synthetic voices; implications for authenticity, authorship, and reception.– AI in subtitling and SDH: automatic speech recognition; MT in subtitling; quality assurance; accessibility challenges.– AI in audio description: multimodal AI for scene understanding; automation in descriptive practice; cultural representation.– AI for the arts and cultural heritage: AVT applications in museums, galleries, and live performance mediation.– Multimodality in AVT research: how AI engages with diverse semiotic resources and reshapes multimodal translation practices.– Cloud-based ecosystems and industry connections: collaborative workflows; training opportunities; professional accreditations; professionalisation of students.– Accessibility and inclusion: AI as driver and/or barrier across global contexts.– Creativity vs automation: tensions between human expertise and machine-generated outputs.– Pedagogy and training: integrating AI in AVT curricula; fostering critical and creative skills; addressing resistance to change. – Ethics, agency, and power: copyright; data and voice ownership; bias in AI systems; socio-cultural consequences.– WhatsApp, iMessage, Telegram, IRC, web chat in films, TV series, animated, films, documentaries, live broadcasts.– Historical perspective of web and digital systems as representative narrative tools in audiovisual products (e.g., IRC logs in 1990s films vs. WhatsApp/iMessage threads today).– Industry perspectives: how streaming platforms, LSPs, and tech providers incorporate AI in large-scale AVT projects.– User experience and reception studies: audience perception of AI-mediated dubbing, subtitling, and AD; impact on immersion and comprehension. Keynote Speakers and Distinguished GuestsThe conference is honoured to welcome leading national and international colleagues, whose presence will foster dialogue between established expertise, emerging research, and innovativepractice, including:Giuseppe Balirano (Università degli Studi di Napoli “L’Orientale”, Italy) – President, Associazione Italiana di Anglistica (AIA)Frederic Chaume (Universitat Jaume I, Spain)Elena Di Giovanni (Università di Macerata, Italy)Jorge Díaz Cintas (University College London, UK)Margherita Dore (Sapienza Università di Roma, Italy)Serenella Massidda (Università di Chieti-Pescara, Italy)Irene Ranzato (Sapienza Università di Roma, Italy) – AIA Board Member Submission GuidelinesWe warmly invite scholars, researchers, practitioners, and industry stakeholders to submit an abstract of up to 300 words (excluding references) and a short bio (max. 150 words) via mail to alessandra.rizzo@unipa.it; gabriele.uzzo@unipa.it; marialuisa.pensabene@unipa.it. Proposals should engage with the conference themes and highlight original research, case studies, or professional experience. Please clearly indicate research objectives, methodology, and expectedresults. Important DatesEXTENDED Deadline for abstract submission: 07 January 2026Notification of acceptance: 31 January 2026Conference dates: 23–24 April 2026 Registration and FeesAccepted presenters and participants are required to register for the conference.Conference fee: €180,00 (includes access to all sessions, conference materials, and coffee/tea breaks).Registration fee applicable to PhD students: €90,00.ESIST members attending the conference as speakers will benefit from a reduced registration fee(€120,00). ESIST members attending as auditors will pay €150,00.Social dinner: €45,00.

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