From my short time at University of Hohenheim, but mostly from learning alongside other students from five continents, I’ve had a rare opportunity to witness and discuss several varying teaching styles in different countries.
Two general categories of teaching styles seemed to be reoccurring themes. Surely there are other categories, and also places and subjects that fit somewhere into both, but I think these two extremes are an interesting place to start this discussion. One is the Traditional (Top Down) approach, where the prof lectures at the students. This is very hierarchical, and usually involves slides full of text and complicated figures. This is the old, classic method, and based on discussions here, it is found more commonly in countries such as Germany, Ghana, and China.
To paraphrase from the introduction of a German presenter, “Since I’m a PhD student, and am not yet a doctor, I am on the same level of you, and will hope that you will participate, and ask questions, instead of having me giving a lecture”. I can’t imagine hearing something like this in Canada (where I’m from) – I wasn’t sure if I should laugh or not.
This leads to the second style, which I’m going to call Modern (Flexible), is more flat in terms of power-structure and allows for more ‘imaginative’ methods. I think we can find these styles more frequently in places such as US and Canada. My bias towards this teaching method means that I find the traditional style boring enough that I have chosen to spend the last hour during a particularly boring (to me) German lecture to write this blog post.
What is interesting to me is that children who are brought up under one style develop preferences for that style. So the question of ‘which style is better’, depends partly on where the learner is from (in addition to individual personality differences). There has been a number of comparative studies by Thomas Oakland on this topic. I still think it would be interesting to do a well-controlled study comparing the effectiveness of different teaching methods, but this would probably be exceedingly difficult.
What style do you think your country most identifies with? I would love to hear your views on this based on where you’re from!
Just found out that I get to particpate as a North American finalist in the Euraxess Science Slam competition in Toronto this Oct 22nd. Pretty excited to share my science, and meet other passionate science communicators. The video I entered in the first round, a 3-minute music video about my MSc thesis, can be viewed here:
So you do a lot of amazing research, whatever. Your research will not matter to anyone else on Earth – at least, not until you make it accessible to them. If we’re not making it available, we’re just wasting science.
The number of research projects that are sitting in desk drawers waiting to be written and published, or those that get published but remain behind paywalls is saddening. But with the boom of open-access journals, that is rapidly changing. There are some growing pains – including the high rate of fake and falsified papers.
If you do a lot of amazing research, and publish it in an open access journal, there is still a chance that a lot of your work is being wasted. Looking through a few papers I recently read (this is called a biased sample), the average journal article has roughly about 5-10 tables and figures. I’ve seen enough of other researcher’s excel sheets to know that this summary is hardly the tip of the iceberg. This isn’t the print era anymore, publishing data is very possible. But, well, where is all the data?
In most cases, it is sitting on aging hard-drives under file names that quickly forget their ways into obscurity. Some lucky files manage to make their way onto websites like FigShare and Research Gate, while some Big Datasets (like genomics data) are too big to have a home anywhere on the internet.
There are a number of astonishing recent studies, meta studies, that use the results from hundreds or thousands of papers to come to fascinating conclusions. These papers are just a glimpse into what the future of meta-analysis has at hand. They are a glimpse at how essential making data accessible is going to be in just a few years.
Researchers are all about getting publications, and that is understandable, given the pressures that they are under. However, a lot of signs indicate that those pressures are changing. We are on the brink of a revolution in science. If you want to stay competitive you would just be silly not to start making your data available now.