The problem
Edtech developers often wonder if the AI-generated feedback they’re delivering to students is actually good coaching. Feedback can be warm but generic, accurate but overwhelming, clear but off-task. Feedback quality encompasses multiple dimensions, making a single quality score for a piece of feedback misleading. As AI-generated feedback enters classrooms at scale, these dimensions can fail independently and quietly.What we’re building
Our Feedback evaluators surface feedback quality as a multidimensional profile, rather than a verdict. Edtech developers can see the qualities that a piece of AI-generated feedback exhibits, which it’s missing, and what to adjust. This helps them measure, monitor, and improve the quality of educators’ feedback to students at scale. Our Feedback evaluators are anchored in the Productive Coaching rubric developed by Quill.org ↗ and Leanlab Education ↗, in partnership with Anastasiya A. Lipnevich ↗.Scope and limitations
Related topics
Quickstart
Run an evaluator in the Evaluators playground, a Python notebook, or with
the SDK.
Python SDK
Integrate Feedback evaluators into your Python project.
TypeScript SDK
Integrate Feedback evaluators into your TypeScript project.