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Criterion
Surveys method illustration showing its working structure
UX Research
Surveys
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Purposedifferent
When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal.ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.
Complexitydifferent
MediumMediumLowLow
Timedifferent
3-14 Tage2–4 h review as a planning range; preparation and evaluation additional30-60 min25-40 min
Participantsdifferent
50+Designers, developers as users, and facilitation1-51-5
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Survey Results, Charts, Segment InsightsPrioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsCompleted Experiment Canvas, Success MetricLearning Card with evidence and next action
Tags1 shared
QuantitativeResearchValidation
ArchitectureEngineeringFeedbackValidationTasks
ExperimentsValidationDiscoveryHypothesis
ExperimentsValidationDiscoveryLearning
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