Minimizing learning behavior in repeated real-effort tasks - Volker Benndorf; Holger A. Rau; Christian Sölch (University of Göttingen, Center for European, Governance and Economic Development Research (cege), 2018)
In this paper, we discuss learning behavior and the heterogeneity of subjects' ability to perform in real-effort tasks. Afterwards, we present a novel variant of Erkal et al.'s (2011) encryption real-effort task which aims to minimize learning behavior in repeated settings. In the task, participants encrypt words into numbers. In our variant, we apply a double-randomization mechanism to minimize learning and heterogeneity. Existing experiments with repeated real-effort tasks find a performance increase of 12-14% between the first and second half. By contrast, our task mitigates learning behavior down to 2% between the first and second half. The data show that subjects show a small heterogeneity in performance.
Keywords: C90; C91; 330; Experimental Methods; Learning Behavior; Real Effort