Online Course Improvement Through GPT-4: Monitoring Student Engagement and Dynamic FAQ Generation

Artificial Intelligence (AI), specifically in language processing, is increasingly recognized as an invaluable educational tool. The Large Language Model (LLM) GPT, developed by OpenAI, is an advanced machine learning tool that utilizes deep learning for human-like text comprehension and generation. This study uses OpenAI's GPT-4 to enhance an online Internet of Things (loT) course at Linnaeus University. We analyzed 12,000+ messages on an online communication platform spanning four years. We compare traditional Natural Language Processing (NLP) techniques to Generative AI for understanding student feedback and issues, inspiring project ideas, and promoting student engagement. We provide a combined approach to monitor the sentiment or mood of the students' communications over the timeline of the course. Moreover, we show how to use LLM to refine the FAQ generation and decipher student feedback for course refinement. We demonstrate how to generate optimal prompts and prepare the data to apply LLMs effectively. Our research reinforces that strategic use of LLMs, like GPT-4, can revolutionize remote learning by lessening lecturer workload and boosting student satisfaction and engagement. Our future work aims to further leverage AI models across remote engineering education. One potential direction is developing an AI-powered bot for online platforms to facilitate real-time interaction, manage queries, encourage engagement, maintain FAQs, and enhance course outcomes.