MOERID: Design and Implementation of a GPT-3-Based Generative Chatbot for Personalized Open Educational Resource Recommendations in Teaching

The integration of technology into education has produced major changes in teaching and learning. Open Educational Resources (OER) have played a role in this transformation enabling educators to enhance course development by utilizing existing educational materials. However the main challenge lies in locating OERs that meet the users’ educational needs and goals. To tackle this issue we introduce MOERID, a chatbot powered by GPT 3 that offers recommendations for OERs. MOERID integrates GPT 3 for its natural language processing (NLP) abilities utilizing deep learning algorithms to comprehend context and produce text with minimal adjustments. Key features of MOERID include an interface, customized recommendation systems, scalability and continuous learning mechanisms to ensure performance and user satisfaction when delivering tailored OER suggestions. This chatbot is designed to assist educators in streamlining the process of searching for resources so they can focus on enhancing the learning journey. The study investigates the context and challenges of OER use, gives an overview of Language Models (LLMs), and describes the MOERID implementation, with a focus on integrating NLP and machine learning technologies. This research contributes to advance AI-powered educational tools by providing actionable recommendations for future research.