Describe how teaching actually runs
Map a real course from enrolment to follow-up: sessions, materials, assessment, reminders and the workarounds trainers use today. An LMS or learning app succeeds when it models this loop, including its exceptions — batch transfers, resits, learners who join late.
Define the learner's context
Record the devices, connections and attention windows learners actually have — a phone on a commute is a different product than a lab desktop. Decide what happens offline, what must be finished in one sitting and how progress resumes across devices.
Decide what counts as evidence of learning
Agree what completion means for your organisation: quiz scores, submissions, attendance or observed practice. Build assessment and reporting around that definition, so certificates and dashboards remain credible to the people who rely on them.
Scope AI assistance honestly
AI study help can explain, hint and generate practice — grounded in your approved material and evaluated against curriculum questions. Decide early what the AI may answer, when it must decline, and what teachers can see. Label assistance as assistance; keep authority with the curriculum.
Bring this to your project brief.
- A mapped teaching loop with its exceptions
- Learner devices, connectivity and session patterns
- Agreed evidence of learning and reporting needs
- Boundaries for any AI assistance, with oversight views
Use general descriptions or anonymized examples. Do not put credentials, personal records or confidential documents into the brief.
Prepare your project brief