Abstract
This paper introduces The Infinite Student, a pedagogical methodology grounded in the “learning by teaching” model, where students deepen understanding by educating human peers and training generative AI chatbots as design collaborators. Drawing from the concept of human-AI superminds (Rick et al., 2023), students operate as both learners and instructors, using AI to enhance problem-solving through collective intelligence. The methodology engages students in structuring data and developing prompt strategies to guide chatbot behavior, aligned with Rogati’s AI Hierarchy of Needs and fostering self-directed learning (Choi & Zhi, 2021). Students build comprehensive knowledge bases through research, which feed into the chatbot training process via prompt engineering, iteration, and reflection. Professors act as mentors, while students assume the role of AI trainers within their project teams. To assess this integration, the study proposes the AI Pertinence Index (AIPI), a composite evaluative tool combining an adapted NASA Task Load Index, the Creativity Support Index, and a novel Capacity Augmentation Index. These metrics measure cognitive workload, creative support, and the balance between human and AI contributions in workflows. Data collected from student surveys quantifies mental demand, creative engagement, and tool effectiveness, producing a score that encourages critical reflection on the effectiveness and utility of AI. Ultimately, this methodology challenges pedagogical norms by positioning students as co-creators with AI, fostering dynamic and iterative learning environments that aim to equip students with skills for a future of human-AI collaboration in design education.
Presenters
Daniel RonderosAssociate Professor, School of Architecture and Design, Universidad de los Andes, Distrito Capital de Bogotá, Colombia
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
Considering Digital Pedagogies
KEYWORDS
Learning by Teaching, Design Education, Human-AI Collaboration, Supermind
