CEUR Validation Dataset v1.0: A Synthetic Benchmark Dataset for Future Empirical Evaluation of the Cognitive Efficiency–Uncertainty Reduction Theory

This repository contains CEUR Validation Dataset v1.0, a synthetic benchmark dataset developed to facilitate future empirical evaluation of the Cognitive Efficiency–Uncertainty Reduction (CEUR) Theory proposed in the associated conceptual article. The dataset consists of simulated participant-level observations representing AI-assisted decision-making under multiple explanation modalities. It is intended exclusively for methodological development, statistical workflow testing, experimental design, teaching, and future validation studies. The dataset was not analyzed in the associated conceptual manuscript and should not be interpreted as empirical evidence supporting the proposed theory