the context of daily life does not differ between the two groups. We therefore conclude that learning through experience …

conclude that learning effects are more important than selection effects for explaining differences between inexperienced and …

opportunities to identify learning rules, since on networks (compared to, e.g., random matching) more rules differ in terms of their … information they consult before making their choices. We use these data to estimate learning types using finite mixture models … find that learning depends on network position. Participants in more complex environments (with more network neighbors …

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 …-randomization mechanism to minimize learning and heterogeneity. Existing experiments with repeated real-effort tasks find a performance …

tariff rates as well as ownership proportions. Additionally, we examine convergence and learning in this setting. While …

-Media Learning literature, which aims to find ways to maximize subject understanding from instruction. After the pre … Multi-Media Learning Instructions nor an Incentivized pre-experiment quiz were found to increase subject understanding of …

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 …-randomization mechanism to minimize learning and heterogeneity. Existing experiments with repeated real-effort tasks find a performance …