A couple of days ago on Facebook, by way of crowd-sourcing syllabi preparation for an undergraduate critical thinking course that includes a unit–three to six class sessions–on scientific reasoning, David Grober-Morrow threw out the following query
What do you most wish that undergraduates (science and non-science majors) understood about scientific reasoning?
This is a very good question. I would suggest that for the indicated demographic and unit-length, the most valuable instruction would be in the centrality of ampliative inference in the practice of science. That is, students should learn that scientific reasoning, besides relying on deductive inference of the consequences of scientific laws, also utilizes, in large part, induction and abduction.
Both these forms of inferences ‘go beyond the data’; they enable the bridging of the gap between observations and the conclusions drawn on their basis. In inductive reasoning, the scientist infers statements about future observations after having made a finite set of observations of empirical phenomena. The classic ‘All ravens observed thus far are black, therefore, all ravens, even those unobserved at this point in time, are black’ formulation of this kind of reasoning leads to Nelson Goodman‘s famous riddle of induction; it is a form of prediction, an inference made about the future. In abductive reasoning, in making inferences to the best explanation, the scientist infers backwards, to the past, about the kinds of events that might/must have occurred to make true the observations recorded. A bridge has collapsed; what must have happened to have made this event occur? This might thus be termed postdiction.
Thus after the scientist has made observations at one point in time, using these forms of inference he is able to look backwards and forwards along the timeline.
Introducing students to these forms of inference leads quite naturally to an introduction and explanation of the centrality of probabilistic forms of reasoning in science, the nature of admissible and inadmissible evidence and the confirmations they permit, the formulation of scientific hypotheses and theories, and the nature of scientific laws. It also shows how deductive inference is a relatively minor part of scientific reasoning, one that follows on the heels of these two forms of inference.
It would be a mistake, I think, to introduce students, in a class like the one described above, to the ‘gruesome’ Goodman puzzle of induction. The fairly sophisticated concepts involved in its clearest explication and resolution are likely to be found confusing by the students in the limited time available. (It also has the unfortunate feature of seeming a bit like a parlor trick, a sure-fire method of turning off a student already convinced that philosophers’ examples are a kind of intellectual sandbaggery.) Instead, I would rely on as many colorful examples as possible to show how science is not the mere routine noting down of data in notebooks, how creative and inventive induction and abduction allow scientists to be, and how much of the impressive and awe-inspiring edifices of scientific knowledge are built on the seemingly tenuous foundations provided by these forms of reasoning.