TailorED: generative AI-powered personalized learning

Abstract

Traditional education systems often employ a one-size-fits-all approach that fails to address the diverse learning needs of individual students. Adopting personalized education methods is crucial for ensuring the effective learning of university students by catering to their individual learning needs and bridging gaps in understanding. The advent of generative AI models has revolutionized the field of natural language processing and enabled the development of AI-powered applications that incorporate AI generated human-like text. Recent advancements in generative AI have opened up new opportunities to integrate generative AI-driven solutions into educational systems to facilitate personalized learning experiences. To capitalize on these advancements and address the limitations of traditional education systems, I present TailorED, an AI study companion that leverages generative AI to provide a more effective and accessible personalized education experience for university students. TailorED consists of a context-aware chatbot, multiple-choice question (MCQ) practice tool, short-answer question (SAQ) practice tool, summarizer, and study plan generator, together with multimodal capabilities. Designed to facilitate self-directed personalized learning, it allows students to engage in the revision of course content more effectively. Results from the evaluation indicated that it can effectively enhance university students’ learning by being able to generate responses across its tools with high accuracy and relevance with respect to the course material for university level education, and provide a high level of personalization to students’ needs and preferences. This shows great potential for TailorED to enhance the personalized education experience for university students by acting as a 24/7 supplementary tool that can perpetually provide personalized learning support and feedback, while being locally hosted to ensure data privacy and security.