Zilong Pan, Yiwen Wu, Adam Wax, Benjamin Rainey, Faatiha Kalam, Jolie Goldstein, Zilu Jiang, Chenglu Li
Iterative usability testing with both teachers and students ensures that generative AI learning tools align with real classroom needs.
This study investigated the user-centered development of MathPal, a generative AI agent built to offer conceptual and metacognitive math support for high schoolers. Researchers conducted two rounds of usability testing involving both students and teachers to iteratively refine the agent's interaction design. The findings demonstrate that co-designing with educators and learners helps align AI behaviors with actual classroom environments and user expectations.
When designing generative AI learning agents, instructional designers should include both educators and learners in iterative usability testing cycles. Rather than relying solely on technological capabilities, focus on how the AI's dialogue flow supports specific metacognitive and pedagogical goals. This dual-user feedback loop ensures the tool is both practical for teachers to implement and intuitive for students to use.
Integrating generative AI into 3D educational game design enables rapid prototyping of personalized and adaptive learning experiences.
Grounding GenAI training in hands-on, playful experimentation helps faculty build literacy, but some still crave structured guidance.
Generative AI is rapidly reshaping higher education, forcing institutions to rethink teaching, learning, and institutional strategy.
As AI automates entry-level jobs, instructional designers must shift focus from teaching basic answers to cultivating deep inquiry skills.
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