AI-Powered Micro-Learning Platform
Product requirements case connecting EdTech domain knowledge with AI product design and technical architecture.
Long-form learning can be generic and poorly matched to a learner's goal, skill level and available time, increasing the risk of disengagement when learners struggle.
What I saw, and how I got to the solution.
Model the user jobs
Defined learner, instructor/content creator and platform admin personas, then translated their needs into user stories and a feature matrix.
Design the personalization engine
Proposed intent-based onboarding, an AI Dynamic Course Stitcher that assembles reusable micro-segments, and adaptive remediation that serves alternate explanations after a failed quiz.
Make content reusable
Defined a metadata-first creator workflow so 30–90 second learning objects can be reused across paths while drop-off analytics pinpoint weak segments.
Think like a technical PM
Specified API-first microservices, separate document/relational data responsibilities, async processing, performance targets, privacy/consent and graceful degradation.
What changed or what I would validate next.
Created a detailed product/technical blueprint for scalable personalized micro-learning. No production adoption or learning-lift result is claimed because this was a coursework case.