Using generative AI in language learning tasks offers potential benefits, such as enabling personalized learning and fostering autonomous learning. However, if students are unaware of GenAI’s full potential as a learning tool—treating it as an “answering machine” rather than an interactive assistant—certain task formats may inadvertently encourage AI use for answer retrieval rather than cognitive engagement. To ensure students develop effective AI literacy, teachers must be prepared to address concerns about AI use and guide students in employing GenAI to support learning. To do so effectively, teachers themselves need a clear understanding of how LLMs work, enabling them to address concerns about students’ overuse without imposing overly restrictive policies.

This poster presentation reports on ongoing efforts to raise both teachers’ and students’ awareness of GenAI’s underlying mechanisms—an essential step in preventing misconceptions and overreliance—while promoting its use as a personalized, interactive learning tool. Through hands-on engagement with practical applications, the study explores how AI can be effectively integrated into beginning EFL learning and teaching at the university level. The study involves preliminary observations of language teachers and beginning EFL learners, examining their responses to AI awareness-raising efforts between 2024 and 2025, and students’ engagement with GenAI-integrated tasks during the early stages of implementation in Fall 2024 and Spring 2025. These tasks are designed to help students make use of AI’s learning support while actively engaging with the content, rather than relying on it for passive answer retrieval.

This preliminary report will discuss teacher concerns regarding plagiarism and overuse, their influence on instructional decisions, and the need for professional development to foster AI-literate educators. As teacher perceptions of GenAI also shape instructional practices and policy decisions, addressing misconceptions—such as the belief that AI directly copies text rather than generating it probabilistically—is crucial to ensuring informed AI integration rather than unnecessary restrictions. It will also present emerging patterns related to shifts in student perceptions of AI, responses to task design adjustments, and unintended effects of AI integration, raising new questions for further investigation. Findings will inform strategies for designing AI-integrated assignments that support beginning EFL learners across different course formats, promoting personalized learning over passive answer-seeking—an aspect that teachers must also fully understand.

Keywords: AI Awareness, Task Design, Language Learning.