What Information Hinders or Promotes Subjects’ Meaningful Learning in a Bandit Experiment for Weighted Voting?: Mouse Tracking Evidence

In this experiment of learning, subjects were asked to choose one of two weighted voting games repeatedly. The payoffs for subjects were determined by a latent stochastic payoffgenerating function. The vote apportionments and quotas of those games were hidden from them in windows on their computer screens. We mouse-tracked what information subjects viewed on the screens. After subjects had experienced a binary choice problem in rounds for learning something, we examined whether those subjects increased the number of choosing the answer which would give a higher expected payoff (subjects meaningfully learned the underlying structure of weighted voting) in a similar but different binary choice problem in the subsequent rounds. Our main results are as follows. (1) The information on subjects’ cumulative payoffs might promote meaningful learning, whereas the information on their own current payoffs did not, or even hindered it. (2) It would be plausible that even if subjects paid more attention to their cumulative payoff, they would fail in meaningful learning when they chose the runs of options randomly, unlike algorithms in machine learning.