Designing with Intent: A Comparative Analysis of Custom AI Chatbots as UDL-Aligned Tools for Multidisciplinary Instruction

The growing presence of AI in higher education has prompted instructors to move beyond passive adoption, to deliberate theory-grounded design. This session presents two custom AI chatbots (DisneyBot and Rico) developed within a teacher preparation course as the technology-enhanced component of a multidisciplinary instructional unit. DisneyBot is built on the ChatGPT platform to guide learners through an exploration of Disney parks, and Rico, is built on the Gemini platform as an interactive guide to information about Puerto Rico by scaffolding learning across four subject-specific lesson modules – Social Studies, ELA/ENL, Science, and Spanish. Both chatbots were developed to support differentiated and interactive learning for 4th and 5th grade students through a virtual field trip framework, with the broader goal of connecting classroom content to authentic real-world experiences. The design of each chatbot was grounded in UDL principles (CAST, 2018). Rather than serving as static information repositories, the chatbots were intentionally designed to function as interactive instructional mediators which use prompting inquiry, guiding subject-specific exploration, and offering differentiated entry points for learners with varying needs and language backgrounds (Vygotsky, 1978). The differences between the two platforms, in terms of interface architecture, customization depth, persona design, and interaction affordances, form the basis of a comparative analysis that will anchor the session. Participants will interact directly with both chatbots, examine the instructional design decisions behind them, and leave with a working framework for developing purpose-built AI chatbots that can be tailored to their own teaching contexts and disciplines.