LARA Review: AI Tool for Education

LARA generates evidence-informed formative feedback for every student's response during a lesson. Teachers set the task and success criteria, students submit their response, and LARA produces structured draft feedback aligned to those criteria. Teachers review every draft before anything reaches a student, then students use the feedback to revise their response in real time. Class-level insights help teachers see patterns across the room and adjust their teaching accordingly. LARA is designed for classroom-based learning with students typically aged 12 and over, across subject areas and year levels wherever teachers want students to improve their responses during a lesson rather than after it. What makes LARA different is the combination of evidence, teacher control, and timing. Feedback follows a three-part structure drawn from research: where the student is going, how they are currently doing, and what specific next steps they can take right now. Nothing is released until the teacher approves it. Professional judgement is not a final check bolted on; it is built into the workflow at every stage. Students are not passive recipients either. They choose their own revision focus, building agency and ownership in the process. Privacy and safety are built into LARA from the ground up, not added on afterwards. Students join via session-only codes with no names, no accounts, and no personal data stored. Codes are deleted after 16 hours. Teachers control what feedback is released and when. LARA is designed so schools can trust it in a classroom without hesitation. LARA is live and available now for teachers and schools. 