2024/07/22 by Kristina Schaaff, Schaaff, Kristina, Marc-André Heidelmann +1 · 3 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Natural Language Processing Techniques #Online Learning and Analytics #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2408.03945
openalex publication_date 2024/07/22 · openalex created_date 2024/10/16 · openalex updated_date 2026/07/28
Large Language Models (LLMs) are increasingly being used in learning environments to support teaching-be it as learning companions or as tutors. With our contribution, we aim to discuss the implications of the anthropomorphization of LLMs in learning environments on educational theory to build a foundation for more effective learning outcomes and understand their emotional impact on learners. According to the media equation, people tend to respond to media in the same way as they would respond to another person. A study conducted by the Georgia Institute of Technology showed that chatbots can be successfully implemented in learning environments. In this study, learners in selected online courses were unable to distinguish the chatbot from a "real" teacher. As LLM-based chatbots such as OpenAI's GPT series are increasingly used in educational tools, it is important to understand how the attribution processes to LLM-based chatbots in terms of anthropomorphization affect learners' emotions.