Quantum computing (QC) is poised to transform fields from information technology to medical science, but early exposure to its foundational concepts remains scarce, especially at the high school and undergraduate levels. Educational bottlenecks stem from limited course offerings, a global shortage of qualified instructors, and a steep conceptual and mathematical learning curve. Existing resources are often either too superficial or too advanced, exacerbating accessibility gaps and impeding the development of a diverse, “quantum-ready” workforce. This paper presents a pilot study of QuantAid, an AI-enhanced, quiz-based learning platform designed to address these challenges by delivering personalized, scalable QC instruction grounded in constructivist pedagogy.

Our platform integrates a light-weight, LLM-powered analogy engine that tailors quantum metaphors to students’ prior knowledge and hobbies, scaffolds abstract quantum ideas to reduce cognitive load, and embeds interactive quizzes with immediate feedback to actively reinforce understanding. A conversational AI tutor, trained on vetted QC content, provides on-demand explanations that align with best practices in trust and transparency for educational AI. In a pilot with N = 21 students, users of the enhanced platform showed higher engagement and modest conceptual gains over peers using static materials. Usability (SUS) and user experience (UEQ) ratings were strong, with particular praise for the platform’s analogical reasoning and interactivity. These findings suggest that a well-designed, AI-augmented constructivist tool can democratize QC education at scale while preserving rigor, addressing the rising demand amid limited teaching resources.