Video games and 3D environments have been exploited for their pedagogical potential across academic disciplines, but existing scholarship on humanities project management has only scratched the surface of the complexities of teamwork on such projects. Jacob Abell will describe his NEH grant-funded work in collaboration with a commercial video game company to produce an immersive environment (video game) that allows users to learn medieval French (both oral and written). Using concrete examples, Abell argues that game designers and humanists can amplify and complement each other's skill sets as they innovate digital tools to preserve dead or dying languages—all while employing data-driven SLA theoretical approaches. In particular, Abell will demonstrate the contribution that language teachers may offer to the video game design process. Alongside Abell, the scholarly team identified linguistic and cultural learning goals in conjunction with the video game narrative design team. Abell outlines the process as both teams generate feedback informed by the professional skillsets and priorities of each team. While this process proved quite effective, Abell will also explore the challenges of communicating and working with commercial partners. Overall, the project offers a scalable approach to creating digital tools at a high aesthetic level while prioritizing approaches to teaching medieval languages modeled on contemporary language instruction.

Bryant White's paper explores how natural language processing (NLP) can be used to provide innovative language classroom techniques. He focuses on AI transformers and deep learning to engage students interested in programming and data science in collaborative projects with those from other backgrounds. The ready availability of various AI models on sites like huggingface.co makes classroom use of NLP an attainable goal, providing access to the original code for programmers while maintaining a user-friendly interface on the front end. After a brief overview of NLP and the theory and architecture behind AI transformers, White highlights some of the ongoing debates that surround them. White then presents the various classes of AI transformers and how they might be employed in language learning. His talk includes concrete examples of encoder models that students can train for tasks such as sentiment analysis and text classification, as well as some of the more generative varieties (along the lines of ChatGPT) that can provide interactive teaching moments in the classroom. The more recent availability of multimodal AI transformers also offers an opportunity to address and integrate multiple literacies, such as visual and audio, in the language-learning context.

Per Urlaub and Eva Dessein conclude the session with a reflection on responses of the academic establishment to potentially disruptive technologies, followed by a call for action. Dessein and Urlaub demonstrate that anxieties in reaction to ChatGPT fit within a well-established pattern of skepticism towards innovation that began with Socrates' negative stance towards literacy. Socrates believed that writing and reading would weaken students' minds and promote unruly behavior. They then argue that technological innovations in recent decades—facilitating the writing process (word processors, spelling checkers), communication across languages (user-generated online dictionaries), and research tasks (crowd-generated knowledge repositories such as Wikipedia)—have initially been met with great skepticism before they became less controversial educational technologies. In language education, stances towards Google Translate parallel this development. Dessein and Urlaub suggest that organizations focusing on language and humanities education need to show leadership, proposing the need for an initiative like the 2007 MLA Report to guide curricular rethinking in language and literature programs in response to the accelerating innovations in the field of artificial intelligence.