Leveraging Fine-Tuned Large Language Model Chatbots for Critical Thinking Development in Education Erna Piantari, Enjun Junaeti, Wendi Kardian
Universitas Pendidikan Indonesia
Abstract
The rapid advancement of artificial intelligence, particularly Large Language Models (LLMs), has created new opportunities in education. This study aims to implement a fine-tuned LLM-based chatbot to support the development of students^ critical thinking skills. Through the fine-tuning process, the language model is adapted to specific learning contexts, enabling it to provide more relevant and reflective feedback. The developed chatbot functions as an interactive learning partner that facilitates open-ended questioning and idea exploration during the learning process. The results indicate that using a fine-tuned LLM chatbot enhances student engagement and promotes higher-order thinking processes. This research contributes to the growing field of AI in Education, particularly in fostering 21st-century critical thinking skills through intelligent conversational systems.
Keywords: chatbot, Large Language Models, critical thinking, learning adaptive, fine-tuning model.
Topic: Computer Science and Computer Science Education
