April 4-5, 2025 (in-person at the University of Arizona) and April 19, 2025 (online)
Registration is still open for the virtual day on April 19. Register here.
Recently, Artificial Intelligence (AI) and online tools have opened new opportunities for how to think about language learning and teaching in a myriad of environments and contexts. In particular, AI has offered personalized and optimized tools and platforms which use chatbots and virtual language tutors to provide real-time feedback, simulate immersive language environments, and engage learners in conversational practice. Educators, learners, and testing agencies are developing pedagogies that can cope with AI-generated tools as invaluable assets. Pedagogy experts have also raised crucial issues about the challenges and risks that need to be carefully considered when these tools are used. This dynamic conversation has made greater progress in commonly taught languages than in the less commonly taught ones, including Middle East Languages, and this workshop will address this disparity. With presentations selected from among submitted proposals asked to focus on Arabic, Hebrew, Persian, Turkish, and other related Middle East Languages, this event addresses classroom projects that explore the potential of AI and online tools in Middle Eastern languages.
Keynote Speakers on April 4 and 5:
Robert Godwin-Jones (Virginia Commonwealth University), Generative AI, Authenticity, and Less Commonly Taught Languages
Abstract
The ability of AI to generate language that resembles closely human-produced speech has led to claims that AI chatbots can “facilitate an authentic, interactional language learning environment” (Chiu et al., 2023). The suggestion here (and in other publications) is that AI output is linguistically authentic enough to supply appropriate learning content, even substitute for human interlocutors. That seems an ideal match for LCTL contexts, where good learning materials are often hard to come by. However, that view ignores the process used by AI systems to repro-duce language and the limitations of that process for the linguistic features and cultural content of its output. The statistical model of language in AI lacks the sociocultural grounding humans have through sensorimotor interactions and from simply living in the real world. Moreover, the training data for AI systems is biased, based on Western, largely English language sources. Studies of AI’s capabilities to engage in culturally appropriate (pragmatic) language use have shown significant limitations. While AI systems can gain pragmalinguistic knowledge and learn appropriate formulaic sequences through the verbal exchanges in their training data, they have proven to be much less effective in sociopragmatic engagement, that is, in generating contextually acceptable speech reflecting an interlocutor’s state of mind, intentions, and emotional status. That limits their usefulness as conversation partners for intermediate/advanced learners. At novice levels, AI chatbots offer considerable benefits, especially in contexts in which local/digital peers are unavailable. For all learners (and teachers), critical AI literacy is needed to have realistic expectations of what AI can provide.
Bio
Robert Godwin-Jones, Ph.D., is Professor in the School of World Studies at Virginia Common-wealth University (VCU). At VCU he has served as Chair of the Department of Foreign Languages, Director of the Instructional Development Center (Office of Information Technology), and Director of the English Language Program (Office of International Education). He has served as a guest lecturer at universities in China, France, Germany, Vietnam, and India. His research is principally in applied linguistics, in the areas of language learning and technology and intercultural communication. He writes a regular column for the journal Language Learning & Technology on emerging technologies. Robert has published five books and over a hundred articles and book chapters, as well as regularly presenting at international conferences. OCID: 0000-0002-2377-3204.
Elsayed Issa (Purdue University), Harnessing the Power of Large Language Models and Speech Technology for Language Learning
Abstract coming soon!
Elsayed Issa is Assistant Professor of Computational Linguistics and Arabic in the School of Languages and Cultures at Purdue University.
This workshop is hosted by the Center for Middle Eastern Studies at the University of Arizona, cosponsored by CERCLL, and held in collaboration with UT-Austin’s Center for Middle Eastern Studies, University of Indiana’s Center for the Study of the Middle East, Georgetown University’s Center for Contemporary Arab Studies, SUNY-Binghamton University’s Center for Middle Eastern and North African Studies.
Questions? Contact Julie Ellison (Associate Director at the University of Arizona CMES)