The future of practice: Enabling teachers to create

What happened

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.

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 number of key pedagogical principles, aligning with those behind the development of LearnLM: These principles come to life in our game-based learning design. , in the earth science example mentioned above, the first level focuses on the temperature, before progressing to harder challenges about rapid warming and storms).

The teacher is at the heart of any classroom and is best placed to understand not only which AI-driven simulations would engage their students, but also when and where they fit into the curriculum. All learning interactives released in the library and available today were vetted and approved by teachers. These include topics from school curriculums such as Kepler's Laws of Planetary Motion, Data Visualization and Projectile Motion.

Why it matters

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. 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.

What to watch

In addition, a collection of learning interactives was evaluated by STEM teachers in the UK. Results show that overall rating is good or excellent with physics and chemistry being the most amenable to simulation creation. Full details and results are available in our tech report. We also conducted an initial study with 12 teachers in the US.

Each of these teachers requested three different custom interactives, which were generated for their specific classroom needs. The feedback was highly positive with an average teacher rating of 8 out of 10 on the interactives’ quality.