1. A computer implemented method for analyzing user performance data from multiple sources, and for providing evaluation and feedback regarding user performance, the method comprising: receiving performance data for evaluating the user with a computer, the performance data resulting from the user performing a first task for evaluating a cognitive ability of the user and a second, different task for evaluating a non-cognitive ability of the user; analyzing the performance data with the computer using mathematical models related to the first and second tasks; wherein the analyzing performance data comprises: identifying construct models as the mathematical models related to the first and second tasks; identifying model-specific evaluation functions for each of the construct models; transforming the performance data onto score scales using the model-specific evaluation functions, resulting in model-specific scaled score data; transforming the model-specific scored scaled data and previously stored model-specific scaled score data into construct-level scores; identifying score scale partition categories based on the construct-level scores; retrieving category-specific diagnostic feedback based on the identified score scale partition categories; generating an evaluation and diagnostic feedback with the computer based upon the analyzing; generating a report regarding user performance using the diagnostic feedback and the evaluation; and transmitting the report.