An interactive micro-lesson that adapts to your role and experience level. Personalized framing, active recall, role-specific scenarios, and a designer's annotation track running alongside. This is what behavior-driven learning design looks like in practice.
Tell the system who you are and how you work. Watch the content adapt in real time: different framing, different depth, different scenario.
Most digital learning is one-size-fits-all: same content, same depth, same examples regardless of who the learner is.
How a micro-lesson can adapt its framing, depth, and scenarios in real-time based on a few simple learner inputs: role and experience level.
Branching logic, text-based personalization, tap-to-reveal active recall, role-specific scenarios, and open-ended reflection with contextual framing.
Watch for the designer's notes alongside each step: they surface the design decision and its rationale. This is the thinking behind the thing.
Adapts by role and experience, but doesn't yet adjust based on learner performance within the session (true adaptive learning).
Tap-to-reveal tests recognition. Genuine retrieval practice would ask learners to generate answers before seeing them.
One scenario per role. Real mastery requires varied practice across multiple contexts and situations.
The reflection is open-ended. A stronger design would include a concrete action plan tied to the learner's actual work.
Behavior change over checkbox training. Send the shape of your problem and I'll tell you whether training is the answer, and what works better if it isn't.
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