new kids on the block

La Defense, Dec. 10, 2010This summer, for the first time, I took three Dauphine undergraduate students into research projects thinking they had had enough R training (with me!) and several stats classes to undertake such projects. In all cases, the concept was pre-defined and “all they had to do” was running a massive flow of simulations in R (or whatever language suited them best!) to check whether or not the idea was sound. Unfortunately, for two projects, by the end of the summer, we had not made any progress in any of the directions I wanted to explore… Despite a fairly regular round of meetings and emails with those students. In one case the student had not even managed to reproduce the (fairly innocuous) method I wanted to improve upon. In the other case, despite programming inputs from me, the outcome was impossible to trust.  A mostly failed experiment which makes me wonder why it went that way. Granted that those students had no earlier training in research, either in exploiting the literature or in pushing experiments towards logical extensions. But I gave them entries, discussed with them those possible new pathways, and kept updating schedules and work-charts. And the students were volunteers with no other incentive than discovering research (I even had two more candidates in the queue).  So it may be (based on this sample of 3!) that our local training system is missing in this respect. Somewhat failing to promote critical thinking and innovation by imposing too long presence hours and by evaluating the students only through standard formalised tests. I do wonder, as I regularly see [abroad] undergraduate internships and seminars advertised in the stats journals. Or even conferences.

2 Responses to “new kids on the block”

  1. I wanted to improve upon. In the other case, despite programming inputs from me, the outcome was impossible to trust.
    It is painful but the statement is true. Students need to understand that it has taken the Prof some 30 years of committed work (with enough mistakes, and blunders on the way) and must work honestly and hard, but many dont

  2. Mark Girolami Says:

    I hosted an IIT second year computer engineering undergrad for an 8 week internship at Glasgow. I gave him a very specific project, compare empirically the Bayesian K-Nearest Neighbour method (Adams & Holmes, JRSS-B) with cross-validation. So a bit of programming and lots of experiments and then some critical evaluation and analysis of the results. He did a very good job enough for me to encourage him to write a short paper and send it to Pattern Recognition Letters. It was published and you actually cited it in your JASA paper on a – proper – Bayesian KNN. I did the same the folioing year with another second year comp eng student – he ended up as a co-author on a Clinical Cancer Research paper. I found these lads to be bright and very determined – the latter characteristic being important.

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