2026
EACL
EACL 2026
Linguistics to LLMs: Teaching with and about Chatbots
Abstract
AbstractLLM-based methods supersede many approaches in NLP at high velocity, making it necessary to adapt curricula. We argue that this effort also presents a chance to integrate LLM chatbots as learning support. We demonstrate (a) how we re-conceptualized an existing class segment on digital assistance systems to discuss LLM-based chatbots, (b) how we created a specialized instructional chatbot as a demonstrator that students could directly use for learning and revision and (c) how students’ initial perception of LLM-based AI changed due to instruction.
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio