This project will enable cognitive scientists to conclude whether or not the 'Plan Prediction Services'' internet-based app ('Planticipate') can learn to predict, with statistically significant accuracy, which plans different types of people will favor - in ANY problem situation. Previous tests with prototype versions showed that it correctly predicts any individual's favored plan at least 70% of the time. But such performance should greatly improve after many people have used the app in order to contribute their sincere, personal judgements, thereby 'teaching' the app to become, hopefully, more accurate. If and when this occurs, the app will continue to be made freely available for everyone to use. This should improve socially-sensitive planning around the world. In this project participants run the 'Planticipate' app by selecting one of its sample situation and scoring the latter's plans both on twelve criteria and for overall desirability (there are no right or wrong answers). All serious users' scores then become part of a now richer, cloud-based data set which will, hopefully, enable 'Planticipate' to forecast group-specific, plan scores more accurately.
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