Changes

Project will advise user on how to optimize their studying by comparing what actually happened with what would have happened if they had done something different, according to a machine learning model. Effects will be illustrated using Partial Dependence Plots and ICE<ref>Visualizing ML Models with LIME · UC Business Analytics R Programming Guide (uc-r.github.io)</ref>. To help user conduct experiments, project will compare one part of time series with another or progress on one set of cards with another. User may have to do some analysis on their own.     

Project will advise user on how to optimize their studying by comparing what actually happened with what would have happened if they had done something different, according to a machine learning model. Effects will be illustrated using Partial Dependence Plots and ICE<ref>Visualizing ML Models with LIME · UC Business Analytics R Programming Guide (uc-r.github.io)</ref>. To help user conduct experiments, project will compare one part of time series with another or progress on one set of cards with another. User may have to do some analysis on their own.     

Any decent skill test will detect when subject is severely sick. For a test to be useful for improving the skill, it must detect more subtle patterns. Statistical tests detect plenty of patterns in target data that are subtle enough and obviously not generated by the same process as the rest of the data. Unfortunately, those patterns could easily be artifacts of the analysis or of the test taking process. Adding the confounders to a machine learning model and then using the error / residuals as the actual test results should help, but is not guaranteed to remove everything.         

Any decent skill test will detect when subject is severely sick. For a test to be useful for improving the skill, it must detect more subtle patterns. Statistical tests detect plenty of patterns in target data that are subtle enough and obviously not generated by the same process as the rest of the data. Unfortunately, those patterns could easily be artifacts of the analysis or of the test taking process. Adding the confounders to a machine learning model and then using resulting error / residuals as actual test results should help, but is not guaranteed to remove everything.         

=== Cognitive Test ===

=== Cognitive Test ===