Advanced Critical and Analytical Thinking

 In PhD/Postdoc Blog

Can you tell me the next number in the sequence 1,2, 3?

We were asked this seemingly simple question at the Advanced Critical and Analytical Thinking workshop offered by our BESST program. Most of us thought that the obvious answer is “4”, without even considering otherwise. Then we were told that other alternative answers can be either 5 or 6; if the series is generated by adding the two preceding numbers (5), or all the preceding numbers (6). This workshop taught novel aspects of thinking which helped us STEM professionals revise our experimental design, data analysis, and scientific presentations. The above numerical example educated us on the concept of Induction, which is inferring generality from a pattern. Studying gene regulation, I could immediately relate to this example. We often encounter proteins which have differential roles in gene regulation. Their roles vary depending on the experimental condition, gene targets, and developmental time. Hence, we realized the importance of not assuming one absolute conclusion while ruling out others, based on patterns from a few observations.

We proceeded to insights on hypotheses generation because those are the backbones of our research. We learned that there can be possibilities beyond those which we tend to think of. Our thinking or cognition is often affected by “cognitive sins”, like Cognitive Inertia where we are blind to errors unless interfered by a force or disturbance. There are several other kinds of cognitive sins, like Observational Overconfidence where we assume that observations are true, and Solution Bias when we assume that the present case can be solved as prior cases. To be mindful of cognitive sins, and practice pragmatic thinking, we were made aware of Charles Sanders Peirce, considered the “father of pragmatism”, and his publication called “The Fixation of Belief” in Popular Science Monthly 12 (November 1877), 1-15. Today we know that logical thinking involves careful consideration of all the aspects of validity of a conclusion. In simple words, if the data and evidence are true then the conclusion must be true. Alternatively, if the evidence excludes all possibilities except the concluding possibility, then the conclusion is true.

In the context of our hypothesis and associated errors, we learned about the following terms – Parsimony or a measure of the exposure to error, Fecundity or a measure of how readily a hypothesis can be exposed to be in error, Fruitfulness or a measure of the extent to which a hypothesis/theory would give rise to or support other explanations, and Unification or a measure of pre-existing evidential support. Being mindful of these concepts will help us improve how we structure our oral, and written presentations. Grant proposals and talks which address the maximum possible anticipated results, potential pitfalls, and alternative approaches get the most credits because they answer almost all the questions asked.

Finally, we as scientists work hard on finding mechanisms, either out of love or to address concerns of the reviewers of our manuscripts. In this direction, we were taught about Structural and Mechanistic explanations. A Structural explanation offers the conditions for a phenomenon, being likely independent of any particular mechanistic process. It complements, but does not replace, the mechanistic explanation. A Mechanistic explanation describes a specific causal path to produce an event. Overall, this workshop taught us to the importance of all-rounded thinking regarding our science, and daily life, which will surely offer new opportunities which were previously unseen in the absence of well-informed thinking. In this context, here is some food for thought. Can you distinguish between the valid and invalid among the two examples below? Please feel free to leave your comments.

The cats are happy if Bob is home. Bob is home. So, the cats are happy.

The cats are happy only if Bob is home. Bob is home. So, the cats are happy.

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