Interpretation of mean absolute error in rpart I ran rpart on my dataset (3000x9) to predict adolescent GPA (continuous), made predictions on test data, and found the mean absolute error to be in the range of 0.45-0.48. Does this mean that the error is small? How do I interpret this? The train-test split is 70-30.

The question is not limited to the rpart model, basically you are asking what is the interpretation of mean absolute error.
Assume your GPA is ranging from 0 to 4 and the error is 0.45, it means on average your prediction is 0.45 different from ground truth.
For example, there is a student, the ground truth is 3.0 GPA for him/her, your  model can predict 3.45 or 2.55. Of course, this is the average performance, the model can be very good on this data point, e.g., producing perfect prediction or be very bad at this data point, make much more error than 0.45.
