Generative artificial intelligence (GenAI) and large language models (LLMs) have simultaneously opened new avenues for enhancing human learning and increased the prevalence of poor-quality information in student response - termed Botpoop. This study introduces Professor Leodar, a custom-built, Singlish-speaking Retrieval Augmented Generation (RAG) chatbot designed to enhance educational while reducing Botpoop. Deployed at Nanyang Technological University, Singapore, Professor Leodar offers a glimpse into the future of AI-assisted learning, offering personalized guidance, 24/7 availability, and contextually relevant information. Through a mixed-methods approach, we examine the impact of Professor Leodar on learning, engagement, and exam preparedness, with 97.1% of participants reporting positive experiences. These findings help define possible roles of AI in education and highlight the potential of custom GenAI chatbots. Our combination of chatbot development, in-class deployment and outcomes study offers a benchmark for GenAI educational tools and is a stepping stone for redefining the interplay between AI and human learning.

翻译：生成式人工智能与大语言模型在开辟人类学习新途径的同时，也加剧了学生反馈中低质量信息——即“学术垃圾”——的泛滥。本研究介绍了专为提升教育质量并减少学术垃圾而设计的定制化、支持新加坡式英语的检索增强生成聊天机器人“Leodar教授”。该机器人于新加坡南洋理工大学部署应用，展现了人工智能辅助学习的未来图景，可提供个性化指导、全天候服务及情境化相关信息。通过混合研究方法，我们考察了Leodar教授对学习成效、参与度及考试准备的影响，97.1%的参与者报告了积极体验。这些发现有助于界定人工智能在教育中的潜在角色，并突显定制化生成式人工智能聊天机器人的应用前景。本研究集聊天机器人开发、课堂部署与成效评估于一体，为生成式人工智能教育工具建立了基准，并为重新定义人工智能与人类学习的互动关系奠定了基石。