What do we really know about how our students generate answers to historical questions? Thanks to Sam Wineberg, Peter Seixas, Bob Bain, Stephane Levesque, and others in their orbits, we know a good bit about how K-12 history students reach their conclusions about the past, but when it comes to higher education, we know far too little. In fact, we’re often puzzled by the answers our students arrive at. Why did they assign great importance to a particular piece of evidence when our view is that this piece of evidence was just a of run of the mill source, not particularly worthy of extra attention? Why is it so hard to shake them from their belief that, say, people in the past wanted the same things that people today want?
To date, too many of our answers to these and other such questions have been based on folk wisdom about “kids today” or an over reliance on what we observe in our classrooms as being representative of “all students.” Real research, based on real data, would surely take us much farther down the road toward understanding how our students think.
Fortunately, scholars in other disciplines than history have done some hard thinking about these issues and, just as fortunately, have done that real research generating real data.
It’s not every day that a historian reads an article with a title like, “The Role of Intuitive Heuristics in Students’ Thinking: Ranking Chemical Substances,” but read it you should. [Science Education, 94/6, November 2010: 963-84] The authors, Jenine Maeyer and Vincente Talanquer, proceed from the assumption that the we better understand how our students think, the better our curricula can be. This is an entirely different approach from one that asks, “What should students who graduate with a degree in chemistry/history/sociology know?” That question needs to be answered in every discipline, but if learning is the goal of our teaching, then we must understand how that learning occurs as we design those curricula. To do otherwise is to waste our time and our students’.
Maeyer and Talanquer begin with a question: What are the cognitive constraints that impede their students’ ability to engage in the kind of careful and complex analysis that they want to induce in their courses? Drawing on 30 year’s worth of research from cognitive science as well as classroom research in the sciences, they describe two constraints and four reasoning strategies arising from those constraints. While they are writing about the analysis of chemical substances, a history teacher could very easily substitute “primary sources” and “history” for “substances” and “chemistry” and learn a lot from their results.
The two cognitive constraints they describe are implicit assumptions and heuristics (short cut reasoning procedures). In history, an implicit assumption would be that during the era of the women’s suffrage movement, all women wanted the vote, because of course women would want the vote. These implicit assumptions are very powerful and difficult to break down, in large part because they are so rooted in a learner’s view of how the world is.
Heuristics are the root of many problems in education in whatever discipline, but the authors argue that if students can learn how these heuristics govern their analytical strategies, they can then begin to learn differently. And once that happens, they are more likely to examine their implicit assumptions about the world.
All of us are beneficiaries and victims of our own heuristics. For example, the quick thinking that results from years of driving experience helps us recognize, without even thinking about it, that the car in front of us is about to do something stupid, so we slow down and give the driver room to do whatever he is about to do. The short cut reasoning procedures we develop as drivers lead us to reasonable conclusions at lightning speed.
But our short cut reasoning can also lead to into errors of analysis. Maeyer and Talanquer identify four heuristics that get in the way of the kinds of learning we want to induce: the representativeness heuristic, the recognition heuristic, one-reason decision making, and the arbitrary trend heuristic.
The representativeness heuristic is one in which we judge things as being similar based on how much they resemble one another at first glance. We see this often in our history classrooms as, for instance, when a student leaps to the conclusion that two works of art separated by both temporal and cultural boundaries must be similar because they kind of look alike.
The recognition heuristic is what happens when we look at a number of pieces of historical evidence, but recognize only one of them, and so assign a higher value to the one we recognize for no reason other than that we recognize it. In the history classroom, this happens when a student is confronted with four or five texts, one of which is familiar, and so focuses all of her attention on that text, to the point of deciding that this text is the most important in the group, even if it is not.
One-reason decision making happens when students make their decisions about evidence based on a single differentiating characteristic of that evidence. So, for instance, in that group of four or five texts, our student might decide that because only one of them actually mentioned something of importance that she is studying, it is somehow more important than the other four when trying to figure out what happened back when the texts were written.
The arbitrary trend heuristic is one we see not only in our students, but in the works of our colleagues. Because several historical sources were generated within a few miles of one another, or within a few weeks of one another, we assume that they must, somehow, be connected to one another, without any evidence to support this hypothesis.
All of these heuristics occur at various moments throughout the semester in our classrooms, regardless of the discipline we teach. Not all students utilize these short cut strategies all the time, but most of them deploy one or the other at some point in semester. Knowing that this is the case, we can then design our courses to address these thinking strategies.
I wish someone had assigned me this article 20 years ago. Of course, it hadn’t been written yet, so that wouldn’t have been possible. But if it had, and I’d read it back before I started teaching history, my life would have been so much easier and my student’s learning would have been so much richer.
This is great Mills, thanks for sharing.
I’m now really curious if some of what we know about the psychology and sociology of memory plays into some of these heuristics. How invested are different individuals in these heuristics, and are some of these more easily challenged than others?
For instance, we know that students carry different types of historical knowledge past with them, as do adults, when encountering history books, lectures, exhibits, et al. And when they are confronted with different versions of the past than what they know there is hesitation and sometimes rejection of these others versions (the history vs memory binary). The recognition heuristic may be the most closely connected to memory: whatever is recognized may come from personal knowledge, their family or other sociological group (collective memory) or acceptance of mass cultural representation (cultural memory), and that overly influences willingness to believe in that evidence. Is it more difficult to overcome representative than say the arbitrary trend heuristic in a class, in a museum, if there is an emotional investment in privileging certain types of sources over the other?
No answers, only questions, but it’s good to be thinking about these things.