The argument seems to be, I'm paraphrasing, "psych people can't deal with complex stuff" which really boils down to "I can't teach them complex stuff". Taken at face value the argument is psych researchers are not clever — reality of course is not aligned really with that view.
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It has been suggested to me - in the context of curriculum refresh - that psych undergraduate students just don't want to learn coding or stats. I don't think it's an accident that the people saying these things are older men, and the students are mostly women.
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I mean, this is clearly true of *a lot* of psych undergrads (men and women both), and I see no reason to deny it. but the fact that many students don't want to learn statistics is not a reason not to include statistics in the curriculum—and the same should be true for coding.
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Agreed, but I am not sure that combining these in a single course is wise, and I worry about students without coding experience feeling that they start with a handicap (because they do). In their first stats course, I like students to grasp the concepts, not "tapply".
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You might want to see what others do further down the thread:https://twitter.com/dalejbarr/status/1066431058764288000 …
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The thing is all students have a "handicap" in some way or another. I am better than people who just speak Engish at using/naming Greek letters (because I am a native Greek speaking) or knowing prima facie what "prosopagnosia" means etc.
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That doesn't mean we don't teach students. As I said elsewhere:https://twitter.com/o_guest/status/1066649799875796992 …
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Those undergrads knew no coding (only two had coded before and not in Python). By the end, they knew how to do the tasks required for the module. And they all good really good grades.
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Every class introduces "handicaps". I did maths in both English and Greek (literally twice, once in high school and once in private A levels) which really helped when I moved to the UK. I didn't need to relearn all the maths terms in English in computer science.
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Yup, this is what I've heard from faculty as well, along with the argument of "if we teach them coding, what will we have to take out???" And "coding is great, but for nerds like us researchers". Cc
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A lot of my difficulty is in pushing the value proposition. I'm struggling to convince some of the value of computational reproducibility, and the other benefits just don't occur to them.
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Please look down the thread. People have managed to do this.
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By "them" I believe
@lingtax is referring to staff - our students definitely see the value. -
Yes, staff are sharing their stories of changing their courses to include programming modules.
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Scroll up and down this side-thread, for example: https://twitter.com/djnavarro/status/1066404110033813505?s=19 …
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I don't want to speak for
@lingtax but from my point of view the challenge is not in creating the modules or fitting in the content. As you've highlighted there are a lot of excellent people who act as role models in that regard. I'm convinced it's important and worthwhile -
The challenge I have is that I don't run our undergrad research methods program so need to be able to convince my colleagues the same. In the meantime I teach R to all of our research students and bide my time.
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I've been noticing this rhetoric for years... I should probably finish my blog post about this and publish it
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