Isegoria

Physicist Carl Wieman noted a consistent pattern in the grad students who came to work for him:

New graduate students would come to work in my laboratory after 17 years of extraordinary success in classes, but when they were given research projects to work on, they were clueless about how to proceed. Or worse — often it seemed that they didn’t even really understand what physics was.

But then an amazing thing happened: After just a few years of working in my research lab, interacting with me and the other students, they were transformed. I’d suddenly realize they were now expert physicists, genuine colleagues. If this had happened only once or twice it would have just seemed an oddity, but I realized it was a consistent pattern. So I decided to figure it out.

Does it really take 17-years as a caterpillar before one can become a beautiful (physics) butterfly? No, of course, not; it’s just that those 17 years of classes are largely wasted — as demonstrated by a number of studies:

The first is by Joe Redish, a highly regarded physics professor at the University of Maryland. Even though the students thought his lectures were wonderful, Joe wondered how much they were actually learning. So he hired a graduate student to grab students at random as they filed out of class at the end of the lecture and ask, “What was the lecture you just heard about?” It turned out that the students could respond with only with the vaguest of generalities.

Zdeslav Hrepic, N. Sanjay Rebello, and Dean Zollman at Kansas State University carried out a much more structured study. They asked 18 students from an introductory physics class to attempt to answer six questions on the physics of sound and then, primed by that experience, to get the answers to those questions by listening to a 14-minute, highly polished commercial videotaped lecture given by someone who is supposed to be the world’s most accomplished physics lecturer.

On most of the six questions, no more than one student was able to answer correctly.

In a final example, a number of times Kathy Perkins and I have presented some non-obvious fact in a lecture along with an illustration, and then quizzed the students 15 minutes later on the fact. About 10 percent usually remember it by then. To see whether we simply had mentally deficient students, I once repeated this experiment when I was giving a departmental colloquium at one of the leading physics departments in the United States. The audience was made up of physics faculty members and graduate students, but the result was about the same — around 10 percent.

It gets worse:

Adapting the characterization developed by David Hammer, novices see the content of physics instruction as isolated pieces of information — handed down by an authority and disconnected from the world around them — that they can only learn by memorization. To the novice, scientific problem-solving is just matching the pattern of the problem to certain memorized recipes.

Experts — i.e., physicists — see physics as a coherent structure of concepts that describe nature and that have been established by experiment. Expert problem-solving involves employing systematic, concept-based, and widely applicable strategies. Since this includes being applicable in completely new situations, this strategy is much more useful than the novice problem-solving approach.

Once you develop the tools to measure where people’s beliefs lie on this expert-to-novice scale, you can see how students’ beliefs change as a result of their courses. What you would expect, or at least hope, is that students would begin their college physics course somewhere on the novice side of the scale and that after completing the course they would have become more expert-like in their beliefs.

What the data say is just the opposite.

On average, students have more novicelike beliefs after they have completed an introductory physics course than they had when they started; this was found for nearly every introductory course measured. More recently, my group started looking at beliefs about chemistry. If anything, the effect of taking an introductory college chemistry course is even worse than for taking physics.

If we look at the differences between a novice and expert, we quickly realize that we’re not actually training students to become experts:

The first is that experts have lots of factual knowledge about their subject, which is hardly a surprise. But in addition, experts have a mental organizational structure that facilitates the retrieval and effective application of their knowledge. Third, experts have an ability to monitor their own thinking (“metacognition”), at least in their discipline of expertise. They are able to ask themselves, “Do I understand this? How can I check my understanding?”

A traditional science instructor concentrates on teaching factual knowledge, with the implicit assumption that expert-like ways of thinking about the subject come along for free or are already present. But that is not what cognitive science tells us. It tells us instead that students need to develop these different ways of thinking by means of extended, focused mental effort.
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People learn by creating their own understanding. But that does not mean they must or even can do it without assistance. Effective teaching facilitates that creation by getting students engaged in thinking deeply about the subject at an appropriate level and then monitoring that thinking and guiding it to be more expert-like.

When you put it in those terms, you realize that this is exactly what all my graduate students are doing 18 or 20 hours a day, seven days a week. (Or at least that is what they claim — the reality is a bit less.) They are focused intently on solving real physics problems, and I regularly probe how they’re thinking and give them guidance to make it more expert-like. After a few years in that environment they turn into experts, not because there is something magic in the air in the research lab but because they are engaged in exactly the cognitive processes that are required for developing expert competence.

Why not try a scientific approach to science education?

Wieman’s first strategy for improving teaching is reducing cognitive load — which is a remarkably verbose and unclear way of saying go slow and be clear. It also contradicts much of my own experience. If a lecturer slows things down and simplifies them to reduce cognitive load, the lecture becomes less engaging, not more. The real problem is that most lectures are like early interstates: the path is so straight, you fall asleep at the wheel. You need some curves, some anticipation, some expectations that may or may not be met.

His second strategy is addressing beliefs students have about science. That means explaining why a topic is worth learning, how it operates in the real world, why it makes sense, and how it connects to things the student already knows. Sure, but nothing’s worse than those bulleted lists at the start of the chapter in a modern textbook: “After studying the material in this chapter, the student will be able to…”

The third strategy, the one that appeals to me, involves engaging students, monitoring their thinking, and providing feedback — which is hard to do in a 200-student lecture hall. That’s why Wieman recommends three demonstrably effective technologies:

1. Just-in-time teaching: The technique uses the Web to ask students questions concerning the material to be covered, questions that they must answer just before class. The students thus start the class already engaged, and the instructor, who has looked at the students’ answers, already knows a reasonable amount about their difficulties with the topic to be covered.
2. Clickers: Each student has a clicker with which to answer questions posed during class. A computer records each student’s answer and can display a histogram of those responses. The clicker efficiently and quickly gets an answer from each student for which that student is accountable but which is anonymous to their peers.
3. Simulations: The “circuit construction kit” is a typical example of a simulation. It allows one to build arbitrary circuits involving realistic-looking resistors, light bulbs (which light up), wires, batteries, and switches and get a correct rendition of voltages and currents. There are realistic volt and ammeters to measure circuit parameters. The simulation also shows cartoonlike electrons moving around the circuit in appropriate paths, with velocities proportional to current. We’ve found this simulation to be a dramatic help to students in understanding the basic concepts of electric current and voltage, when substituted for an equivalent lab with real components.

Now that he has offered up his hard-won teaching wisdom, is anyone listening?

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