DfE-DB: A systematic database of 3.8 million human decisions across experience-based tasks

Abstract

Abstract Learning from experience is central to human decision making, but progress is limited by heterogeneous task designs and fragmented data formats that hinder systematic comparison across studies. We introduce the Decisions From Experience Database (DfE-DB), a structured, open-access resource comprising 3.8 million trial-level decisions from 11,921 participants across 168 studies and 13 paradigms. By harmonizing raw behavioral data and classifying studies along 13 key design features, the DfE-DB enables quantitative comparisons previously obscured by heterogeneous task and data structures. Using the database, we show that choice tendencies—toward higher risk, expected value, or experienced mean—vary substantially across paradigms and are strongly shaped by core design features such as feed-back type, outcome structure, stationarity, and sampling. These features explain substantial cross-study variability and reveal underexplored paradigm variants. By providing a unified and extensible data infrastructure, the DfE-DB facilitates reproducible research on testing the generality of behavioral phenomena and computational models, fostering a more integrated science of decisions from experience.

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