We took Daughter to the Experimentarium today. Lots of fun stuff to experiment with, like water basins, light, Olympic sports, soap bubbles and plenty more. So much so that it was a bit overwhelming at first. Nonetheless a fun afternoon.
Though talking from the viewpoint of the US, I really enjoyed listening to Allie Ward’s episode Quarantinology. Covid-19 regulations are being lifted, now what? Ward talked to several researchers covering the history of quarantine, what to expect in the near future regarding infection rates and how to deal with settling in to our new lives. Indeed, we’re not getting back to normal. Normal is dead, according to Cole Imperi. Imperi also talks about ‘shadow losses’, things we lost during the pandemic, and our need to grief for them. That part really made sense to me. I highly recommend listening to this episode of Alli Ward’s excellent show.
Now that I’m a student again, and subject to a substantial online course which has some elements that feel to me like a waste of time, I got curious about the latest insights in how we learn best. I spent my first year at university studying educational science and I still have some fascination for the design of courses and workshops, both online and offline.
The element that I found (very) inefficient was watching a teacher code in SQL for a full day, without much interaction other than asking questions via chat. During that same week we got assigned three modules to practice with SQL in Datacamp, starting from the very basic level and then moving on to more complicated stuff. I felt a bit frustrated with this set up as it seemed to me like first spending a day learning nothing, before the real work could commence in a week where I was already strapped for time.
So last week I spent the whole of Monday watching the teacher. During the morning the speed of all the basics felt too slow. By 14:30 my mind switched off, my body started yearning for movement and fresh air, and the teacher ramped up his speed to show more complex stuff leaving my mind wonder why I signed up for this course anyway. Now I don’t want to sound too critical here, as most of the course is wonderful, despite the use of MS teams to keep track of all the assignments and building a sense of community. But scheduling a session like this felt like backwards thinking, not in line with the things I know about how people learn. Nevertheless, going through the Datacamp modules went much faster than expected (and projected by Datacamp), so perhaps I learned more during that first day than I want to acknowledge.
This made me curious about what recent insights about learning are. How can I help myself over the coming months to not just tick of the assignments and move on, but actually store what I’ve practised in my long-term memory? And give some constructive feedback towards the academy?
I found some interesting resources. For instance this article published by Princeton University.
Most people believe that repeated exposure to material, such as “going over” notes, “re-reading” are the main and most important ways to learn and “absorb” information. In fact, research shows that memorizing in this way has significant shortcomings. Such methods are not only highly time-consuming and less than optimally effective, they are often rather boring. There are not only more effective and efficient methods of learning, but alternative approaches are often more engaging, interesting, and enjoyable.
Learning the basics of programming is all about doing, not memorising the exact code. That’s the message my academy sent out. Rightfully so. However, it is important not to effortlessly sail through the assignments. The article also states that “effortful learning usually signals not only deeper learning, but more durable long-lasting knowledge.” I found the SQL modules in Datacamp easy, as most of the challenges were heavily pre-scripted, stating line by line what to write. That could mean that I learned less than I did with the Python modules, where I sometimes was struggling with some concepts. Fellow students report many more issues in grasping the material and take twice as long to go through the assignments. They might be learning more and better than I am as it’s more challenging to them. I therefore will try to do some of the extra challenges in Datacamp to up the “desirable difficulties” for me.
Rushing through the modules might not be the best strategy either. It is important to “interleave” studying, or leaving space between study sessions. This can be a bit hard to do given the fact that I need to finish certain modules within a week. Nevertheless I could try spreading the work between the days and within the week. If the mandatory online sessions allow me to.
There are more principles in the article, but some of them are less applicable to the practical data science skills I’m learning right now. Or simply impossible due to current restrictions like varying locations where you’re learning.
Elsewhere I read it is important to practise extensively. “overlearning reduces the amount of mental effort required, leading to better performance”, according to this article.
According to that same author the key to learning is knowing how learning works. I’m well on my way to learn more effective then.
One other resource I’d like to mention is The Science of Learning. This is a more practical guide to translate cognitive principles to classroom situations.
None of the articles I read mentioned watching a teacher do something on a screen for a full working day as a good teaching strategy, though. I’m glad it was only one day, not the five day training the teacher mentioned doing too. I guess I just found writing SQL statements easier than writing Python.
If you have any good recent references on learning, please share them with me in the comments. I always have an appetite for learning more.
A study was done in the use of positive words in research papers.
Male scientists are more likely than female ones to publish work that describes itself as “excellent”, “unique” or “novel”, experts have found – a swagger that appears to reap dividends in respect of how often others reference the research.The Guardian
This is yet another subtle way how a seemingly insignificant difference in the words men and women use could have a big impact in the long run.
“Here is another example when gender differences, probably imposed by unconscious cultural norms on both authors and editors, lead to divergent outcomes,” she said. “Because publishing itself has so much impact on career progression, this finding has significant implications. Academic processes and institutions need to pay much more attention to what gets published where, why and by whom.”Prof Athene Donald, University of Cambridge in The Guardian