During this week’s GEDI seminar, one of the discussions concentrated on the merit of “seven pervasive myths, or mindsets” (Langer 1998, chap. Introduction). One of the seven myths that stood out most to me is:

1. The basics must be learned so well that they become second nature.

I find this myth very puzzling because the question of what is meant by “the basics” is largely unanswered. For one thing, what is meant by “the basics” cannot be generalized to education as a whole, but instead must be relative to a particular topic or research area. Even within a specific research area (e.g., statistics[1], biology, aerospace engineering, history), there seems to be little to no agreement on what counts as being “basic.” For instance, my thesis research is pertinent to establishing what is basic or fundamental to learning about statistical inference; namely, it argues that how we define the concept of “evidence” affects the formalism[2] a statistician uses to solve a research problem. Thus, the mathematics used in statistics is secondary to learning more basic concepts (e.g., evidence), at least according to my perspective. Whereas statistics has been treated for many years as a mathematical subject, which means the mathematics were what counted as being “the basics.” I would be interested to hear about the progress (or lack thereof) in other research areas concerning what is meant by “the basics.” Moreover, I will end by asking[3] readers the following questions: what counts as being “the basics” in your research area? How well do you think the basics must be grasped before moving on to other topics within your research area?

References

Langer, Ellen J. 1998. The Power of Mindful Learning. Cambridge, MA: Da Capo Press.

“Statistic.” 2013. Merriam-Webster Online Dictionary. Accessed September 2. http://www.merriam-webster.com/dictionary/statistic.