From Student Work to Actionable Feedback: AI Applications for Strengthening Monitoring and Evaluation in Education

This session presents AssessClear, a web-based AI prototype that strengthens classroom-level monitoring and evaluation by converting student work into actionable evidence. The system generates structured feedback, identifies misconceptions, and builds a longitudinal database of student responses-drawing on classroom and formative assessments typically unavailable in MEL systems. This enables tracking of learning progress, identification of gaps, and targeted instructional support. The session combines a live demo with reflections on responsible AI use and evidence-informed decision-making while preserving teacher judgment.