Q-Module-Bot: A Generative AI-Based Question and Answer Bot for Module Teaching Support

Abstract

Contributions: In this article, a generative artificial intelligence (AI)-based Q&A system has been developed by integrating information retrieval and natural language processing techniques, using course materials as a knowledge base and facilitating real-time student interaction through a chat interface. Background: The rise of advanced AI exemplified by ChatGPT developed by OpenAI, has sparked interest in its application within higher education. AI has the potential to reshape education delivery through chatbots and related tools, improving remote learning and mitigating challenges, such as student isolation and educator administrative burdens. Yet, ChatGPT’s practical applications in education remain uncertain, potentially due to its novel and enigmatic nature. Additionally, current e-learning chatbot systems often suffer from development complexity and a lack of input from key stakeholders, leading to developer-focused solutions rather than user-centered ones. Intended Outcomes: In this manuscript, we introduce a practical implementation of AI in education by creating a system called Q-Module-Bot that is accessible for both technical and nontechnical educators to harness e-learning benefits and demystify generative pretraining transformer (GPT). Application Design: The proposed Q-Module-Bot system has utilized pretrained large language models (LLMs) to build a Q&A system that helps students with their queries and supports education delivery using content extracted from a virtual learning environment (VLE). Findings: The prototype and system evaluation confirm the effectiveness of a scalable cross-departmental tool featuring source attribution and real-time responses. While successful in encouraging wider acceptance of GPT use cases in higher education, refinements are needed for full integration into the VLE and expansion to other modules/courses.