I am doing my PhD in Data Mining / Artificial Intelligence and are at the beginning of my second year. I have had three master students so far, whose performance varies quite a bit. The worst (he already finished) got a very clear, cut and dry task for his thesis and still did not mange to do it as expected. The best so far (close to the end of his thesis) had a very vague task, and still got pretty nice results. The third is in the middle of his thesis.
In each each case, the really creative ideas, the innovation if you will, always came from me. Currently I have this third student in the middle of his thesis who has quite a few ideas how to use existing techniques, but I get the impression he is not really able to invent his own. Possibly I am not creating a good environment?
My students seem to lack quite a bit in technical know-how (pragmatic aspects of programming), mathematical understanding and knowledge of existing machine learning methods. This is understandable – the end of your master is by far not the end of learning and I am happy to help them by explaining those things to them. Still, I struggle a little with that, since this is a road blocker. This is just “learning”, and not yet “creating”.
Now I have new task that I would like to have solved and which would make a fine master thesis topic. However, no solution exists for the problem yet and it pretty challenging, requiring quite a bit of creativity. A more or less completely new algorithm is required.
My questions are:
- Is there a point giving this task to a student or should I forget it and solve it myself?
- More general: What creativity can I expect from master students to create new methods? Am I expecting too much?
- How can I foster creativity in my students?