SDAS, PIE, eAdmin and school decision-making
A mark sheet tells you who scored what; a Student Data Analysis System answers why, what the trend is and what to do next. Eight questions show how standard scores, percentiles, progress rates, multi-year tracking and teacher analysis are used — and how AI natural-language queries let every teacher ask.
Read moreTeachers can spend 8–10 hours a week on paperwork. Six examples show how AI admin agents (eAdmin) draft eNotice, eCircular, parent letters, meeting minutes, event proposals and iPortfolio comments — and why grounding in the school knowledge base and matching the school's voice are the keys.
Read moreEvery school runs Plan–Implement–Evaluate, but "evaluate" often relies on impressions. See how PIE KPIs link directly to platform data — AI usage, objective mastery, teacher training records, SDAS results — so planning has a baseline, implementation has tracking, evaluation has evidence, and grant interim and final reports come out automatically.
Read moreSpecs, pricing, release timelines and platform support status for 15 major model providers
Read more28 lessons of teacher AI literacy: from Transformers and the three training stages to RAG, quantisation and local deployment
Read more18 lessons of classroom prompting: planning, question setting, marking, differentiation and student prompt literacy
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