Table 6 Performance comparison of all models on the training and testing set. The \(R^{2}\) score and root mean squared error (RMSE) indicate how well we can fit the true reading progress. Accuracy measures if the direction of progress is correctly predicted and the f1 score is a combination of precision and recall. Since both, accuracy and f1 score are the same, we know that precision (positive predictive value) and recall (sensitivity) have the same value. For all, except RSME, holds that higher values indicate a better fit. Test and train values are close to one another, which suggests that no strong over-fitting occurred. We finally chose linear regression and ridge regression as final models

From: Both sides of the story: comparing student-level data on reading performance from administrative registers to application generated data from a reading app