Generative AI Tools in Teaching, Learning, and Assessment (NeMLA Roundtable) (NeMLA 2025 in Philadelphia, PA)
Philadelphia, PA
Organization: Northeast Modern Language Association (NeMLA)
Event: NeMLA 2025 in Philadelphia, PA
Abstracts submitted on NeMLA website: https://www.cfplist.com/nemla/Home/S/21235
Roundtable ID 21235
Brief Description: Language educators as well as educators and/or administrators from across various disciplines are invited to discuss the impact of generative Artificial Intelligence (AI) tools on teaching, learning, and assessment. Please submit a presentation title, a 200-300-word abstract, a brief (50-word) biography.
Abstract: Rapid growth and advancements in generative artificial intelligence (AI), coupled with its unprecedented availability through open-access tools such as OpenAI’s ChatGPT, have put educators on high alert, launching discussion around the potential impacts of this technology on teaching, learning, and assessment.
Roundtable participants are invited to provide insights into the effectiveness, limitations, and pedagogical implications of incorporating generative AI tools into language education and/or other disciplines; e.g., presenters may investigate and showcase different approaches (in sample activities, assignments, etc.) to usefully integrating ChatGPT (or similar) in the classroom; remark, if applicable, on navigating institutional guidelines; highlight, if applicable, feedback received from students on the use of AI in presenters’ described practices.
Condensed Literature Review
Recent studies on student engagement with AI tools built on Large Language Models (LLMs), in the form of machine translation, highlight a correlation with improved language proficiency and post-editing skills (Chung 2020), meta-linguistic reflection on syntactic structures (Chung & Ahn 2021), and lexical diversity (Fredholm 2019). Beyond machine translation, Bonner et al. (2023) note that generative AI can help instructors facilitate certain dimensions of language teaching, such as reinterpreting text using level-appropriate diction, correcting grammar in student compositions.
Instructors and students, however, must also navigate the limitations inherent to LLMs, related to the data sets on which they are trained. For the most part, ChatGPT has mainly been evaluated on English data and its success in supporting different tasks in non-English languages is yet uncertain (Lai et al., 2023). Generative AI also seems to struggle with creative expression in its ability to produce natural-sounding language or to replicate “cultural and contextual nuances of language, such as idioms, colloquialisms” (Font de la Vall, R., González Araya, 2022).
https://www.cfplist.com/nemla/Home/S/21235
Teresa Lobalsamo