Uncategorized

AI for VE and ELT

AI for VE and ELT

Authors in alphabetical order: Asuman Asik, Barbara Simoneli, Carlos Hildeblando, Ester Quiroz Uribe, Juliana Salvadori, Kyria Finardi, Lucas Kohnke, Luciana Cabrini Calvo, Marina Orsini-Jones

Division of labor:

AI - Lucas, Ester, Asuman

Implications for ELT - Carlos, Marina, Kyria

VE - Juliana, Barbara, Luciana 

Abstract

As artificial intelligence (AI) technologies and Virtual Exchange (VE) become increasingly integrated into higher education, their implications for English Language Teaching (ELT) and other languages warrant critical examination. This chapter explores how AI—particularly generative AI like ChatGPT—shapes language learning dynamics, intercultural communication, and linguistic equity within VE contexts. By examining the intersection of AI, language, and culture, the study investigates how AI tools can both facilitate and hinder meaningful cross-cultural exchange, language acquisition, and the production and dissemination of knowledge, particularly for underrepresented linguistic and cultural groups. Drawing on recent scholarship that addresses digital inequality, linguistic hegemony, and epistemic exclusion, the chapter reports on the authors’ experience with AI, VE, and ELT to uncover how AI can be leveraged to promote inclusive, multilingual, and culturally responsive VE initiatives. It also identifies potential risks of reinforcing existing power asymmetries and linguistic dominance in global academic interactions. Additionally, the chapter considers how AI-mediated VE projects can serve as a platform for exploring the complexities of language use in diverse cultural contexts, fostering more nuanced understandings of language learning and intercultural communication. Through targeted VE projects, the study aims to amplify marginalized voices, promote diverse linguistic representations, and inform pedagogical strategies that align AI use with equitable and inclusive ELT practices. By critically engaging with AI applications in language education, the chapter contributes to ongoing discussions about the ethical, cultural, and pedagogical implications of AI in the evolving landscape of Computer-Assisted Language Learning (CALL). It underscores the potential for AI to act as both a bridge and a barrier in the pursuit of more inclusive and accessible global academic networks, urging educators and researchers to consider how AI can be harnessed to foster greater linguistic diversity and cultural understanding in VE, ELT and education in general.

Introduction

The integration of Artificial Intelligence (AI) technologies into educational contexts is rapidly transforming the landscape of higher education. As AI becomes increasingly integrated into education in general and in higher education in particular, the ability to effectively and critically engage with AI tools is becoming a crucial skill for teachers, students and researchers (Pessin & Finardi, 2025).

Notwithstanding the potential of AI for global development, there is a serious language and digital divide that must be addressed first.

The language divide refers to those who have access to English and other strong languages whereas the digital gap refers to access to technologies and digital literacy. AI works very well for certain languages but it may increase the language and digital divide for languages other than English (Zhu & Wang, 2025).

According to Zhu and Wang (2025), AI requires initiatives that address diversity, equity, and inclusion (DEI) in education in general and in language education in particular, especially considering that Large Language Models (LLMs) may work very well for English but not necessary for low-resource languages. Zhu and Wang (2025) found that research on AI for language education has predominantly favored quantitative and mixed methods with a noticeable shortfall in qualitative research efforts. More qualitative studies are needed to shed light on the socio-cultural aspects of AI-assisted language learning to provide richer and deeper insights into the specific and individual learning processes and differences.

Results of Zhu and Wang (2025) showed that scholars have used different perspectives to investigate the role of teachers in AI-integrated language teaching and although there is an extensive discussion on the benefits of AI-integrated classrooms, there remains a notable paucity of empirical evidence outlining specific strategies for leveraging AI-human teacher collaboration to support teachers in enhancing their teaching efficiency. So as to address this gap, this paper argues that Virtual Exchange (VE) is one way to stimulate teacher collaboration across different contexts both for research and teacher education purposes.

According to O’Dowd (2018) VE refers to a range of online intercultural exchange and interaction activities that promote intercultural learning, language development, and global citizenship education among students from different countries and cultures. VE has a considerable potential for teacher education and intercultural development. During the COVID19 pandemic, VE was also used as a substitute to international academic mobility (Finardi & Guimarães, 2020) and it has been used since then as a strategy to calibrate relationships between the Global South and the Global North (Guimarães, Finardi & Amorim, 2021), as a way to develop Global Citizenship (Guimarães & Finardi, 2021, Finardi, Salvadori & Werhli, 2024), so as to promote Internationalization at Home (Finardi & Asik, 2024), as a way to promote digital critical literacy and intercultural development in teacher education (Orsini-Jones, Cerveró-Carrascosa & Finardi, 2021), as a Third Space to promote alternative ways of knowing, being and relating (Wimpenny et al., 2022), as a way to promote reflection and change in habitus in teacher education (Simoneli, Finardi, 2023), as a more cooperative and inclusive  internationalization (Mendes & Finardi, 2023) and as a postdigital, connected, embodied, relational socio material Third Space (Orsini-Jones et al. 2025).

Since the pandemic, VE is gaining momentum as a scalable, cost-effective, and inclusive alternative to traditional physical mobility and also as a relevant space for teacher and researcher collaboration. At the intersection of these trends the growing use of AI and VE in higher education lies both an opportunity and a challenge: how can AI be meaningfully leveraged to enhance VE experiences while promoting linguistic diversity, intercultural understanding, and equity? Following this intersection there are also important considerations for teacher education in general and English language teaching (ELT) in particular.

Generative AI tools like ChatGPT have shown promise in facilitating language learning and intercultural communication, offering immediate feedback, customized practice, and simulated dialogues. However, their deployment in VE settings also raises critical concerns regarding linguistic hegemony, epistemic exclusion, and digital inequity. AI is often shaped by dominant linguistic and cultural norms, which may marginalize underrepresented voices and languages reinforcing global power asymmetries.

This paper examines the dynamic interplay between AI, language, and culture in the context of VE, focusing on the affordances and limitations of AI for fostering inclusive and culturally responsive ELT practices. Drawing from current scholarship in teacher education and informed by the authors’ experiences with VE projects and ELT, this study aims to contribute to the ethical and pedagogical discourse surrounding AI use in language education in general and in ELT in particular. It argues that, if critically and creatively harnessed, AI can act not only as a pedagogical tool but also as a transformative agent for inclusion and intercultural development in global academic collaborations.

AI - Lucas, Ester, Asuman

Implications for ELT - Carlos, Marina, Kyria

VE - Juliana, Barbara, Luciana

References

Finardi, K. R., & Guimarães, F. F. (2020). Internationalization and the Covid-19 pandemic: challenges and opportunities for the global south. Journal of Education, Teaching and Social Studies2(4), 1-15.

Finardi, K., & Aşık, A. (2024). Possibilities of virtual exchange for Internationalization at Home: Insights from the Global South. Journal of Virtual Exchange7, 1-22.

Guimarães, F. F., Finardi, K. R., & Amorim, G. B. (2021). From pandemic to paradigm shift: recalibrating Brazil’s relationships with the Global North. In EAIE Forum Magazine (Vol. 1, No. 1, pp. 28-29).

Guimarães, F. F., & Finardi, K. R. (2021). Global citizenship education (GCE) in internationalisation: COIL as alternative Thirdspace. Globalisation, Societies and Education19(5), 641-657.

Guimarães, F. F., Mendes, A. R. M., Rodrigues, L. M., dos Santos Paiva, R. S., & Finardi, K. R. (2019). Internationalization at home, COIL and intercomprehension: for more inclusive activities in the global south. SFU Educational Review12(3), 90-109.

O'Dowd, R. (2018). From telecollaboration to virtual exchange: State-of-the-art and the role of UNICollaboration in promoting research and practice. Journal of Virtual Exchange, 1, 1-23.

Orsini-Jones, M., Jacobs, L., Finardi, K., & Wimpenny, K. (2025). Collaborative online international learning as a postdigital connected, embodied, relational & (socio) material Third Space: female voices. Higher Education Research & Development44(1), 237-252.

Wang, C., & Canagarajah, S. (2024). Postdigital ethnography in applied linguistics: Beyond the online and offline in language learning. Research Methods in Applied Linguistics3(2), 100111.

Wimpenny, K., Finardi, K. R., Orsini-Jones, M., & Jacobs, L. (2022). Knowing, being, relating and expressing through third space global South-North COIL: Digital inclusion and equity in international higher education. Journal of Studies in International Education26(2), 279-296.

Zhu, M., & Wang, C. (2025). A systematic review of artificial intelligence in language education: Current status and future implications. Language Learning & Technology, 29(1), 1–29.

https://hdl.handle.net/10125/73606

Introduction to the Editors’ Group and today’s presentations: GRAEME PORTE

Introduction to the Editors' Group and today's presentations: GRAEME PORTE

 1 MARTA ANTON PRESENTING:  CRITERIA FOR EVALUATING A JOURNAL

  (to include getting to know what journals are most pertinent to the enquiry, Open Access journals, Scientific Rigor. A key indicator of journal quality is the scientific rigor of the publications published in the journal. ... Editorial Quality. ... Peer Review Process. ... Ethics. ... Editorial Board Members. ...Journal Reputation/Business Model. ...Author Rights and Copyright. ... Indexing Status.

 2 MARTIN EAST PRESENTING:  WRITING FOR A SPECIFIC JOURNAL OR SECTION IN THE JOURNAL

 (to include doing your homework on what typically gets accepted; tergetting tha readership specifically; examples of how certain journal strands require different approaches to presentation/style etc.) 

 3: WAYNE WRIGHT PRESENTING:  COMMON MISTAKES THAT CAN LEAD TO REJECTION

(to include Editorial (form and preparation) mistakes: Not paying attention to/ following guidelines in Information for Authors (IFA); Not using good grammar/proper English; Including poor quality tables/figures/illustrations; Submitting a topic that is outside the journal’s scope; Submitting a manuscript that lacks novelty/scientific significance; Using poor methodology and making poor/inappropriate statistical analysis; Ethical mistakes: Submitting your manuscript to more than one journal at once; Submitting a paper partially published elsewhere, etc.  REASONABLE USE OF AI

 4JIM McKINLEY PRESENTINGREVIEWING FOR A JOURNAL. 

Based around Masatoshi's original request that “We could talk about the importance of peer reviews (academic citizenship?) so as to raise people’s awareness of and contribution to the academic publishing practices? I say this partly because I am aware that some universities bluntly discourage faculty members from reviewing papers (and instead encourage spending time on publishing, of course).” 

 5. MASATOSHI SATO PRESENTING: UNDERSTANDING JOURNAL DECISIONS (to include understanding how to re-submit and what to write in a cover letter, understanding rejection, resubmission and replying to feedback and SUBMISSION DANGERS/"WARNINGS" (to include similarity indices, ChatGPT attitude to, use of paper mills etc.).