Slashdot Mirror
Teaching Natural Sciences To Social Science Students?
An anonymous reader writes "As a calculus professor for a small undergraduate institution, I normally lecture students who are majoring in the natural (or 'hard') sciences, such as mathematics, physics, and computer science. In fact, I have done so for almost thirteen years. However, for the first time this fall semester, we have a shortage of professors on our hands. As a result of this, I have been asked to teach a general education statistics class. Such classes are a major requirement for the large psychology student body we have here. I have never lectured social science students in any mathematics-related classes. My question to the Slashdot community is as follows: What are your experiences with teaching natural science classes to social science students? How is the experience the same or different in comparison to natural science students who may be more adept to the nuances of mathematics and other similar fields?"
I have to somewhat disagree with this. In teaching my inorganic chemistry and organic chemistry students, there is a huge difference between the chem majors and the biology majors (in genchem, they are still pretty much the same, as they haven't been "indoctrinated" yet). The chem majors know that do well, they need to practice, practice, practice. The biology students are all about memorization, flash cards, that kind of thing. Most catch on by the end, but for psych students, I strongly suggest that you drill into them from the very first day that the only way they will succeed in the class is by doing practice problems every day.
My sister opened a computer store in Hawaii. She sells C shells by the seashore.
My thoughts exactly.
He might end up losing some of his elitist attitude before the course is over. It would be better if lost the attitude ahead of time, and approached the experience like he was at least teaching the same species.
Indeed. I teach statistics to mathematicians, biologists, psychologists and social scientists and I would say the social scientists 'get' the principles of statistics better than the 'hard' scientists do. The main reason is that soft scientists (which is a horrible term) can think about uncertainty and its consequences, whereas hard scientists (mathematicians included) are unhappy if they don't have a yes/no answer to a question. Obviously this is a generalisation but it may inform your approach to teaching.
Also, statistics is not 'just math'. I know this because I can do statistics but I can't do math(s) any more. :-)
...especially as regards the use of mathematics in the interpretation of 'data' where the soft sciences have such a 'hand wavy' approach to cause and effect.
To me, economics is a prime example. Forgive me if I'm off base in in my belief that economics is both sociological and soft(headed), but tyring to measure human behavior in the absence of an accounting for political corruption within this purely human realm and leaving the so-called black market beyond it's consideration leaves the inclusion of economics within the realm of 'science' suspect.
I would haved greatly appreciated any attempt by a professor to explain the difference between soft science and hard science, especially if it included an math based explanation of the nuance between these different domains.
Soft sciences are typically about trying to solve 'wicked' problems, which are those that are generally impossible to completely solve (end poverty or health inequality, understand crime, migration, or human behaviour in general etc). Hard scientists typically try to solve problems that are relatively much easier because they have a simple concrete goal (put a man on the moon, make a bomb, cure some disease)
Soft scientists need a much stronger theoretical framework to interpret their data, because of the absence of any really testable mechanisms for the effects they observe. This can come across as 'hand wavy' but it really isn't. Your economics example isn't entirely fair, some economic models will include corruption and black markets etc and others wont, just as some physics models include relativistic effects and others don't. A good scientist has to choose the right model to approah any problem, regardless of discipline.
I've been working in an inter-disciplinary group and have had the opportunity to see medics and economists try to work together. The two cultures are very different in their scientific approach, both consider the other to be unnecessarily picky about some aspects of the work while not being rigorous enough in others. Eg economists spend a huge amount of their time trying to prove causation in observational data, while medics will typically wave this away if they think the causal effect is likely enough. On the other hand economists tend not to contextualise their results well enough, while medics will see the bigger picture in terms of building on existing science.
If I had a dollar for every paper published in a peer-reviewed social sciences journal which totally abused statistics, I'd retire and use my extra cash to fund organizations directed at basic logic and math education, trying to help with the situation.
Most social studies students I knew had little understanding of the statistics they were using. It was basically a magic incantation for giving them results and making their conclusions sound more credible to other people who likewise didn't understand statistics. The result is bad statistics and bad science. Yes, these people aren't idiots, but they've become used to being rewarded without having to think rigorously.
The impression I get is that the pattern persists even among those few who make it into the field. There are some psychologists etc who are really trying to do real science- a difficult task since the basic concepts are even more up in the air than the basic concepts of chemistry were in the days of the alchemists. As far as I can tell, however, quite a lot are quite happy to be able to find ways of running a study so it will inevitably vindicate their preexisting biases and will fudge the statistics to match.
For the OP: You're right to be concerned. Students for the GE stats class are usually woefully underprepared. Rather than giving them the rigorous preparation in logic, multivariate calculus, etc they really need to understand statistics, the GE stats class does the equivalent of the Wizard's favor to the Scarecrow.
"I can't give you a brain, so I'll give you a passing grade! Now you understand statistics! Go back to your department now, please. (Phew, they're gone at last. That kind of work may pay the bills here in the Stats dept. but it doesn't do wonders for my sense of academic integrity as an educator.)"