University of Waterloo students showcase AI prototypes for more accessible learning

Google and the University of Waterloo showcased student-built AI prototypes from the Google-funded Futures Lab, with projects aimed at making learning and feedback more accessible.

A student lab for applied AI ideas

According to Google’s article on The Keyword, the Futures Lab brought together University of Waterloo students to build working AI prototypes focused on education, accessibility and everyday learning. The University of Waterloo described the program as an AI and user-experience prototyping workshop that used Google tools including Gemini Canvas and Google AI Studio.

Waterloo said the initiative was part of its partnership with Google, and that students presented prototypes exploring how AI might support learning in areas such as language, physical training and skill development. The university’s coverage named projects including SignFluent, Kanji Garden and MuscleMemory.

SignFluent focuses on sign language practice

One of the highlighted projects, SignFluent, is described by the University of Waterloo as a tool for learning American Sign Language. Waterloo said the prototype uses AI to help users practice signs and receive feedback, with the broader goal of making sign language learning more accessible.

Google’s account also identified SignFluent as one of the Futures Lab prototypes, describing it as an example of student work aimed at AI-assisted learning and feedback. The sources do not present the tool as a commercial product; they describe it as a working prototype developed in the lab setting.

Kanji Garden and MuscleMemory target different learning needs

Waterloo’s mathematics faculty article described Kanji Garden as a prototype designed to support kanji learning. The same source said the project was part of the Futures Lab’s exploration of AI-enabled educational experiences, alongside other student-built tools.

Another named prototype, MuscleMemory, focuses on physical learning and feedback. Google’s article and Waterloo’s coverage both list MuscleMemory among the showcased projects. Waterloo described the broader showcase as an example of students using AI prototyping tools to explore new forms of learning support, including feedback for movement-based skills.

The projects point to a common theme across the Futures Lab: students were not only building chat-style applications, but experimenting with AI systems that respond to practice, performance or user input in specific learning contexts.

A partnership framed around education and prototyping

The University of Waterloo said the Futures Lab was connected to its collaboration with Google and presented the program as a way for students to apply AI and UX methods to real-world learning challenges. Google’s article similarly framed the lab as a space where students could turn ideas into working prototypes.

The available sources do not provide independent testing results, deployment timelines or evidence that the prototypes have been adopted outside the showcase context. They do, however, document the projects, the Google-Waterloo partnership and the educational focus of the student work.

For now, the Futures Lab examples are best understood as early prototypes rather than finished products. Still, the projects show how university students are applying current AI tools to practical learning scenarios, from sign language practice to kanji study and physical-skills feedback.