For the last few semesters, I have taught a graduate-level course (mixture of Master's and PhD students) that has a very substantial data analysis component in which every assignment involves analyzing data based on what was covered in the prior 1-2 week's worth of lectures. The prerequisite is my university's introductory statistics course, which teaches students basic statistics (t-tests, z-tests, linear regression, etc). We recommend a particular statistical language to use and provide coding suggestions in that language, but students are also free to use whatever they feel most comfortable using.
Increasingly, I am finding that students in the course rely on me to solve every coding error or problem they encounter, and in many cases, the top hit of a Google search for the error/problem suggests more or less what I would have as well. Some students are "repeat offenders" in that even when I show them how to use Google to look for debugging help, they still come to me with Google-able questions.
I want to be sympathetic to students who may not have much statistical computing experience beyond the introductory statistics course we teach, but at the same time, I feel that graduate-level students need to be able to solve these sorts of questions on their own. In my field, you cannot survive without knowing how to write code to analyze data, and part of that is knowing how to debug your code when inevitable errors/bugs arise.
Has anyone run into this sort of issue before, and what, if anything, helped?