senseproviding

Senseproviding is a concept referring to the deliberate provision of clear, interpretable cues, explanations, or contextual information that helps individuals understand a system, situation, or dataset. The goal is to align perceived input with user expectations, reducing ambiguity and cognitive load while supporting accurate interpretation and decision making.

Used in information design, data visualization, education, and human-computer interaction, senseproviding encompasses practices such as labeling, tooltips, legends, concise explanations, progressive disclosure of detail, and feedback that confirms outcomes.

Effective senseproviding relies on several practices: consistent terminology, appropriate level of detail, accessible language, contextual cues that relate to user goals, and feedback loops. It often interacts with related concepts like sensemaking and sensegiving, explainability in AI, and usability heuristics.

Benefits include improved comprehension, faster learning, greater trust, and better decision-making. Challenges include avoiding information overload, ensuring accuracy, and accounting for diverse user backgrounds and contexts.

Examples: a dashboard with clearly labeled metrics and color coding; tooltips that explain what a metric measures; an AI assistant that provides rationale for its recommendations.

See also: sensemaking; sensegiving; explainable AI; usability.