实践的未来：让教师用生成式 UI 创建学习互动内容

Gal Elidan, Research Scientist, and Yael Haramaty, Product Manager, Google Research We explore how we can harness generative UI with learning design guardrails to give teachers the ability to generate guided, interactive simulations for every topic and student. Digital educational tools have transformed how students around the world access information, from online textbooks to video libraries. Yet, for all the remarkable leaps in technology and accessibility, digital learning can often feel like a passive experience. Interactive, engaging, multimodal forms of practice that can encourage students to think for themselves and work through solutions have great potential for learning but remain largely out of reach. They are expensive to create, limited in number, and often require a lot more effort from the teacher. We wanted to see if AI could help close this gap. Today, we’re sharing our latest research which pushes the frontiers of interactive learning. Our new research experiment allows educators to create custom, interactive, and guided educational simulations. These learning interactives are tailored to the teacher’s objectives and curriculum, and are generated dynamically, leveraging a novel application of generative user interfaces (GenUI) that we’ve optimized for learning. Having received initial positive teacher feedback from a trusted tester pool, we’re also releasing a sample library of over 30 learning interactives in English for STEM subjects including physics, chemistry, biology, and math with a focus on middle and high school. These are all generated by AI and reviewed by teachers. Schools using Google Workspace for Education can sign up to provide feedback to improve learning interactives through the Google for Education Pilot Program . This pilot is an early step toward developing more learning interactives for public use. The library is available for public use and includes learning interactives on a variety of biology, chemistry, computer science, earth science, mathematics and physics topics. Learning is not a spectator sport . From the work of John Dewey, a foundational education theorist, who argued back in 1916 that we should “ give the pupils something to do ” to that of Jean Piaget, the influential psychologist whose pioneering work showed how learners construct knowledge , it is well established that students learn better through active engagement. Modern cognitive research, such as the ICAP framework , affirms that interactive behaviors consistently yield deeper schema construction and long-term retention than passive listening or reading. In short, students learn by doing. When students actively experiment, test hypotheses, and solve problems, they build a much more complete mental model. Active learning is one of the key learning science principles that we optimize for in our research. It is fundamental to LearnLM , Google’s family of generative AI models fine-tuned for education released in 2024, and was explored in a 2025 Learn Your Way research experiment that reimagines the classic textbook with generative AI. Building on this earlier research, we set out to explore how the latest advances in generative models could be used to further transform content, helping teachers create digital learning that is much more active and engaging. To make this possible, we turned to generative UI , an active area of research whereby AI models dynamically construct user interfaces rather than requiring those interfaces to be coded in advance. We explored how to optimize generative interfaces for deeper educational journeys as opposed to quick interactions. By using carefully guided instructional design and pedagogical guardrails, we want to empower teachers to create their own interactive environments — tailored to their curriculum and adapted to their contextual inputs. We first sought to determine what good, interactive learning experiences look like. We drew on established learning science to define a