Cover Image by Tima Miroshnichenko from Pexels
By Althea Need Kaminske
This week I had the opportunity to teach a guest lecture for medical students interested in AI in Medicine. In preparing for the talk I was, once again, struck by how challenging learning, and especially learning in medicine, can be. Many of the most effective study strategies that we know of through cognitive psychology are somewhat counter-intuitive at first. When you compare retrieval to re-reading, spacing to massed practiced, and interleaving to blocking, the more effective long-term strategy (retrieval, spacing, or interleaving) is almost always harder at first. The less effective long-term strategy (re-reading, massed practice, or blocking) leads to faster improvement and tends to feel easier. This makes it difficult for learners to know whether their learning strategy is working. It’s hard. It requires persistence and patience to figure out how learning works. So, once again, I found myself coming back to a piece I wrote a few years ago on thinking. The more I work with students doing the hard work of thinking and learning, the more I am heartened by the fact that yes, thinking is hard, but we do it anyways.
Originally posted September 5, 2024
Thinking is hard. As someone whose career is more or less based on thinking thoughts, and communicating those thoughts effectively, I have a love-hate relationship with thinking. There are days when I’m excited to work through tough problems and read interesting and relevant research. Most days I’m genuinely excited to talk about those things with other people. There are even days when I delight in writing about those things. But, there are also a lot of days when I am exhausted and overwhelmed and might cry if asked to think one more thought. When I have no more opinions to give. No more thoughts on the topic. No ideas about what to have for dinner. According to a recent meta-analysis – “The unpleasantness of thinking: A meta-analytic review of the association between mental effort and negative affect” (1) – I am not alone.
There is a long history of research in psychology that suggests that people, and animals, generally do not like to do more than is necessary. This has been called the “law of less work” (2) or the “law of minimum effort” (3). These “laws” followed from research on animal behavior in the 1930s and 40s that found that animals will generally try to expend as little effort as possible when given the choice. Later research on human reasoning and decision making found that people tend to adopt heuristics as opposed to algorithms. Heuristics are simple, and therefore easier, processes that yield correct results most of the time, while algorithms are complex, and therefore more effortful, processes that yield correct results all of the time (4). We also tend to only exert mental effort when we think the rewards are attainable and sufficiently valuable (5). When presented with choices that require different amounts of effort, there are a variety of factors that influence whether or not we’ll choose to do something that requires more effort. Sleep, fatigue, and information about the reward all impact our choice (1). All of these findings support the idea that cognitive effort (i.e. “thinking”) is resource-intensive and we like to conserve our resources.
