Summary：IITM Launches Hopeful AI‑VR Tool to Spot Early Learning Gaps in Kids IIT Madras has unveiled a low‑

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IITM Launches Hopeful AI‑VR Tool to Spot Early Learning Gaps in Kids

IIT Madras has unveiled a low‑cost artificial‑intelligence‑powered virtual‑reality system designed to detect learning difficulties in children aged 11 to 12 before they become entrenched. The prototype combines a 15‑minute immersive VR session with a machine‑learning classifier that predicts a student’s performance level with 95 % accuracy, offering educators a rapid, objective screening method that can be deployed in schools with limited resources.

**Key Developments**
Researchers at the Institute’s Centre for Educational Technology built the tool around a lightweight VR headset and a set of gamified tasks that probe numeracy, literacy, and spatial reasoning. As children navigate the virtual environment, the system logs response times, error patterns, and gaze movements. These data streams feed into a gradient‑boosting model trained on anonymized assessment scores from over 2,000 middle‑school students across Tamil Nadu. In validation trials, the AI‑VR pipeline distinguished between learners performing at grade level, those needing remedial support, and those at risk of falling behind with a precision recall balance that surpassed traditional paper‑based screenings. Importantly, the hardware bill of materials stays under ₹5,000, making the solution attractive for government‑run schools where budget constraints often impede early‑intervention programs.

**Industry Analysis**
The launch arrives amid a surge in ed‑tech investments targeting early‑childhood diagnostics, yet most existing products rely on lengthy questionnaires or expensive neuro‑imaging. IIT Madras’ approach bridges the gap by marrying immersive engagement with scalable analytics, a combination that industry analysts say could shift the market toward “experience‑first” assessment tools. Competitors such as BYJU’S and Khan Academy have begun experimenting with AR‑based practice modules