CoderBot 2.0: Integrating LLM and Prompt Engineering in the Evolution of an Educational Chatbot - Mendes, Andre; Parizotto, Arthur; Garcia, Renato; Garcia, Marcelino; Guedes, Gilleanes; Vilela, Ricardo; Valle, Pedro; Balancieri, Renato; Silva, Williamson (Anais do Simpósio Brasileiro de Informática na Educação (SBIE), 2025)
Teaching programming to beginner students remains a significant challenge, as it requires the development of complex cognitive skills. Given this, this article presents CoderBot 2.0, an evolution of a pedagogical agent designed for introductory programming instruction based on Example-Based Learning (EBL). The new version integrates Large Language Models (LLMs) and prompt engineering techniques to generate both correct and erroneous examples on demand, as well as code explanations and progressive feedback, without relying on fine-tuning. Aligned with Cognitive Load Theory, its architecture promotes metacognitive strategies such as self-explanation, fading, and contextual variation. The system offers adaptive support, adjusting to the student’s level and encouraging engagement, autonomy, and reflection.