Evidence presented in Salmon (2001; Econometrica 69(6) 1597) indicates that typical tests to identify learning behavior in experiments involving normal form games possess little power to reject incorrect models. This paper begins by presenting results from an experiment designed to gather alternative data to overcome this problem. The results from these experiments indicate support for a learning-to-learn or rule learning hypothesis in which subjects change their decision rule over time. These results are then used to construct an adaptive learning model which is intended to mimic more accurately the behavior observed. The final section of the paper presents results from a simple simulation based analysis comparing the performance of this adaptive learning model with that of several standard decision rules in reproducing the choice patterns observed in the experiment.