Snorkl

Snorkl is a K-12 classroom tool that asks students to explain their thinking aloud and on a whiteboard, then returns AI formative feedback on those explanations — celebrating the approach and prompting a next step, rather than issuing a grade. The design choice is the point: the student produces the reasoning, and the model responds to it, the opposite of an answer-generating tutor.

What you can do with it

Students record a voice explanation while drawing on a whiteboard. Feedback returns within seconds on that multimodal response. Teachers create their own activities or draw on a library of standards-aligned ones, so the feedback criteria follow the curriculum rather than the vendor's: the FAQ says the tool supports all K-12 subjects and ages, and lists 64 languages for feedback, in either the student's spoken language or one the teacher chooses. A teacher dashboard surfaces class-level patterns such as common misconceptions and exemplars; assignments go out by LMS link or join code, with Google, Microsoft, or Clever sign-in.

Who it is for

K-12 teachers who want to hear the reasoning behind an answer, and administrators buying at school or district level. The free teacher tier requires an account, and the FAQ caps it at 20 activities and excludes Snorkl Coach. School and district plans are quote-based — no prices are published — and add unlimited activities, a school dashboard and library, support, and professional development.

Notes and caveats

Every capability claim here is the vendor's own marketing, including "trusted in 10,000+ schools worldwide", which a district should check against its data processing agreement. The vendor states that it strips personal identifiers before sending work to OpenAI under an agreement not to retain or train on it, shows students no advertising, never sells data, and holds iKeepSafe and Common Sense Privacy certifications. Snorkl also states plainly that it does not grade: it scores explanations against teacher-specified criteria as formative feedback, and the teacher keeps grading. Treat those AI judgments as formative signals subject to the usual validity and bias questions, and the environmental commitment as stated intent, not a measured offset.

Connected Concepts

Formative Assessment, AI Feedback Quality, Feedback, Multimodal AI, Speech and Voice Technologies, Learning Analytics, K-12