Tuesday, June 16, 2009

Understanding Great Teaching

An interesting article was recently published by Ken Bain and James Zimmerman entitled Understanding Great Teaching (Peer Review, Spring 2009, vol. 11 (2), 9-12). A link to this article article can be found HERE. Ken Bain is the author of the book What the Best College Teachers Do and this article is based on some observations and principles outlined in the book. Although this is a short article, the authors tackle key questions and issues such as different student approaches to learning, what makes teachers great, how to encourage a deep approach to learning and how to tell the difference between popular teachers and good teachers.

One of my favorite parts of this article is somewhat related to a previous post on the Power of the Question. In the article, the authors state:

"Through the power of the questions they raise, these outstanding teachers engage students in doing the discipline even before they know the discipline...teachers who promote deep learning approaches help students to learn inductively, moving from fascinating and important questions to general principles of the discipline."

I hope you get the chance to read this article about great teaching.

1 comment:

Jim Clinger said...

The article raises a number of interesting questions, although the general argument does not satisfy me. The article begins with a very brief mention of a proposal to reward faculty based on student evaluations. That introduction seems only to be a seque into some consideration of what good teaching is. The view of the authors is that good teaching is what fosters "deep learning". Students are said to appreciate "deep learning" if they have schooling that regularly involves "deep learning". This kind of learning is never defined to my satisfaction, but the authors contend that whatever it is will be fostered by an inductive teaching method. The question of how to measure "deep learning" is not really addressed, which is a significant omission if we consider linking faculty rewards to the amount of "deep learning" that occurs. What worries me the most is the treatment of inductive reasoning. In my graduate school courses that dealt with methodology and the philosophy of science, inductive reasoning is generally considered to be inferior to deductive logic as a means of building testable theory. In fact, some epistemologists would argue that inductivism is not only inferior but impossible, because without a cognitive framework to organize sensory input, the input will never be placed in a format that can be processed. There are no solid standards for inductive logic, as there are for deductive reasoning. Mill's methods are often suggested as a way of reaching conclusions inductively, but they simply will not work without some additional premises about the relevant criteria that must be compared for agreement or disagreement in order to make conclusions about the relationships between variables. In short, I am saying that there is a danger in arguing that inductivism leads to "deep learning" when contemporary epistemology contends that inductivism is a bad way for natural and social scientists to learn anything at all.