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October 2007
Routine vs Adaptive Expertise

_Do we want our students to become experts? What does it mean to become an expert?

In the 1980's some Japanese theorists proposed that we distinguish between two different types of expertise. These are not levels of expertise, but fundamentally different types.

Routine experts know all of the routines of a discipline, profession, game, or whatever, and, in fact, they may know them so well that they might even be considered world class in their expertise. As John Bransford has written "Routine experts have learned a set of routines that can be very complex and sophisticated, and [they] become very skilled at applying them." They may be life-long learners, but, as Bransford points out, they simply become more "efficient at doing what they have always been doing, and perhaps of adding a few new tricks along the way."

Adaptive Experts, in contrast, also know all of the routines, but they also have the attitude and aptitude to recognize and even relish both the opportunity and necessity for invention. They enjoy exploring the unknown and thinking in different kinds of ways. They appreciate their own knowledge, but they also realize how little they know in comparison to all there is to know. They constantly question their own assumptions, and feel comfortable doing so, and they avoid strong emotional attachments to any set of beliefs.

Question: How do we foster adaptive expertise? The traditional approach has been to think of a single road that passes through routine expertise on its way to adaptive expertise. The learner must go down this road, in this traditional thinking, far enough to encounter adaptive expertise. Thus, we offer the learner a “capstone” experience to foster adaptive expertise only after routine expertise has been achieved. The traditional Ph.D. program is a perfect example of such a single road/capstone experience approach to education. The graduate student is first asked to master the field and take qualifying examinations. After conquering all of the set routines of the discipline, the candidate must suddenly become an adaptive expert, an original thinker who does publishable work in the field for the dissertation.

But is the single path model the best approach? Should we think instead about two roads that diverge very early? One leads to adaptive expertise, and the other, no matter how far you go down it, leads only to higher and higher levels of routine expertise. The roads diverge early and the longer one is on the road to routine expertise, the more difficult it becomes to get on the other path.

In that model, the question then becomes, what is the nature of the path to adaptive expertise that makes it special? Bransford and others have suggested that the most distinctive quality of that path is lots of opportunity to speculate. How often do you ask your students, how would you do this, before you tell them what to do or how to think? How can we pose problems and ask students to grapple with those problems? In our study of teachers who have had enormous success in fostering adaptive expertise, we discovered that they often ask students to do a discipline, even before they know how. Thus, Donald Saari prods students to "invent calculus," and Michael Sandel stimulates them to think like political theorists even before they have read much political theory. An ancient text from Aristotle offers some advice. "For the things we must learn before we can do them," Aristotle wrote in the Nicomachean Ethics, "we learn by doing them."

References: John Bransford, “Some Thoughts on Adaptive Expertise,” available on-line at www.vanth.org/docs/AdaptiveExpertise.pdf; MG Pandy, AJ Petrosino, BA Austin, and RE Barr, “Assessing Adaptive Expertise in Undergraduate Biomechanics,” Journal of Engineering Education (July 2004): 1-12; FT Fisher and PL Peterson, “A Tool to Measure Adaptive Expertise in Biomedical Engineering Students,” Proceedings of the 2001 American Society of Engineering Education Annual Conference and Exposition, 2001, available on-line at www.vanth.org/docs/013_2001.pdf

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January 2008
Too many choices and Natural Critical Learning Environments

_Do you recognize any of these situations? You've given your students an opportunity to do some extra credit work to bring up their otherwise lousy performances, but few students take advantage of your offer and those who do, turn in work that is--to put it mildly--below your expectations. Or, you've read some of the literature on the value of giving your students choices in their education to encourage them to take control of their own learning. Accordingly, in one of your key assignments--say, the writing of a research paper--you give them lots of choices, maybe even allowing them to make up their own topics. Anxiously you await the results, expecting that the students will produce superior work. But, alas, they don't, and many of them don't even do the assignment.

Even if the situation is not quite that bad, we all struggle with how best to motivate our students to do their best work, or at least to keep from discouraging them.

Perhaps sometimes we give them too many choices. At least, that's one of the conclusions Mark Lepper and Sheena Iyengar reached from an experiment they did at Stanford University. They gave students in an introductory social psychology class the opportunity to write a "two-page essay" as an extra-credit assignment. They gave one group 6 possible essay topics, and another group 30, and told them that they could get 2 extra points on the next exam if they wrote a short response paper to a film everyone saw. Quality didn't matter, they assured the students. Just write the paper and you'll get the points.

They then counted the percentage of students in each group who did the assignment and had a group of graduate students assess the quality of the submitted papers. The graders didn't know the whole exercise was an experiment or whether any one student had been given 6 or 30 choices of topics. The results: The group that had the fewest choices produced more papers and received higher marks than did the group that had more choices. That finding matches similar discoveries about consumers. Too many choices on the shelf and their less likely to buy a product than if there are only a few.

Before jumping to any rapid conclusions about your next assignment, however, consider another study, this one from a group of psychologists from four universities in the United States and Canada. They concluded that more or fewer choices had different influences on different people. If you are a "maximizer," that is, you have a strong desire to pick the best choice, more choices will probably drive you nuts. More choices mean more chances you won't pick the very best one. But if you are a "satisficer," that is, you are satisfied with just making a good choice, more choices will tickle your fancy because you improve your chances of finding a good choice.

If you have a class full of "maximizer," limit their choices, this work seems to suggest. But if you have room full of "satificers," the more, the merrier.

Students, of course, aren't that simple, and finding the right combinations of choices and limitations for any particular student can be extraordinarily difficult. In my study of college teachers who have had enormous success in fostering deep learning, I found that the most successful of them did consciously try to give their students a sense of control over their own education. And they did pay attention even to small details like the number of choices they might give students, but in general they relied on far more than such manipulations to win the enthusiastic participation of their students. In general, they raised interesting questions. They often created what I call a Natural Critical Learning Environment. That is, they first found questions that already interested their students, and then they tried to find ways to connect those questions to the questions of the course.

Let say, for example, that you want your students to take an interest in how Reconstruction after the American Civil War influenced political, economic, and cultural developments in the South and nationally. You could begin the course with questions about such matters. But that's not what Princeton University professor Melissa Harris-Lacewell did in a course she taught in the fall of 2006. Instead, she began with the national fascination with what went wrong when Katrina hit New Orleans. In her course, she then helped students move from that question to the question, when did the disaster begin, when the storm struck land or in 1866 when Reconstruction policies began to shape the historical landscape in the Bayou City, or some other place along the way? The result: students took to the course like a duck to water.

Human motivation is highly complex, defying easy generalizations. But research on the subject has shed some important light on the topic, and in that light we may be able to find at least some tentative answers to the difficult business of keeping our students focused, or at least avoiding any inadvertent discouragement of their efforts.

If you want to read more, you might begin with the two articles noted above:

S. S. Iyengar and M. R. Lepper, “When Choice is Demotivating: Can One Desire Too Much of a Good Thing,” Journal of Personality and Social Psychology 79, no. 6 (2000).

Barry Schwartz et al., “Maximizing versus satisficing: happiness is a matter of choice,” Journal of personality and social psychology 83, no. 5 (November 2002).

Both are available in the Research Academy. On November 9, 2007, Professor Harris-Lacewell gave a talk about her course to a standing-room-only crowd on the Montclair campus. We have a video recording of that talk.

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May 2008
Rubrics and Feedback

_When David Kanter went off to college at the University of Pennsylvania, he expected his professors would give him "extensive feedback" on each assignment. Many students, he surmised, are "interested in intellectual growth," and "only constructive feedback can foster such growth." Kanter, a freshman from East Falmouth, Massachusetts, reported that instead he got a "few perfunctory, illegible comments. . . scribbled in the margins." Writing in the student newspaper , The Daily Pennsylvanian, he concluded "that unmarked papers and vague comments were the norm" for students at this Ivy League school.

In a recent informal survey of Montclair students, we found similar sentiments: a strong desire for feedback on their work. But they didn't just want feedback along with their grade. They wanted something their professors regularly enjoy on their own scholarship, a chance to receive feedback and to resubmit their work before any final judgment is made about its worth. When Richard Light surveyed students at Harvard nearly two decades ago, he also found the same views. Light was trying to identify the qualities of those courses at Harvard that students found most intellectually satisfying. After interviewing thousands of current and former students in the late 1980's, he concluded that such courses had two major qualities: high but meaningful standards, and "lots of opportunity to try, fail, receive feedback, and try again" before any grade was put on the work.

Instinctively, professors have always known that students would learn best and most deeply if they had that kind of opportunity for revision, but practical considerations have frequently prevented it from happening. David Kanter concluded that the lack of feedback he was getting might be "inevitable given that a single course can have over 100 students who are each turning in a 10- to 15-page paper." While classes at Montclair are generally smaller than the one's Kanter encountered, most professors here teach more classes than do the faculty members at Penn. "How can I even think about assigning major papers in a class," one Montclair faculty member asked in frustration, "let alone give students feedback on their work before it counts for a grade."

To do so, a growing number of Montclair faculty members are using rubrics to provide feedback to their students. If the number of new books on rubrics is any indication, so are other professors across the country. One of the most popular such books is Introduction to Rubrics: An Assessment Tool to Save Grading Time, Convey Effective Feedback and Promote Student Learning , by Dannell Stevens and Antonia Levi. The Research Academy has a copy of that book in its library.

At Penn, Kramer also found a few instructors who use a "nifty technological tool" called Waypoint Outcomes to employ rubrics. Let's say you want to make the same comment to twelve students. With Waypoint, you simply type it in once, and then each time after that requires only a checked box. Furthermore, the comment can be kept and offered to other students the next semester. The brainchild of Andrew McCann, an engineer and writing instructor at Drexel, Waypoint allows professors to offer better comments in far less time.

While Waypoint helps speed up the process, it alone can't guarantee good comments. There is also a growing body of research literature on what kinds of comments will work best in helping and stimulating students to make those revisions. When Joshua Aronson spoke on our campus in March as part of the Provost's Series on University Teaching and Learning, he noted some of that research. As Aronson mentioned, some of it challenges some widely held notions about how to provide good feedback to students. It also points to a somewhat maddening conclusion: social forces can help shape what kinds of feedback will work best, but since different groups of students face different social winds, the same kind of feedback might have completely opposite influences on any two students. In one case, it might encourage students to do revisions; in another, the same comments could demoralize a student, producing apathy and defeat.

Maddening, yes, but with dedication and study we can learn more about our students and about what kinds of feedback and comments will work best. As Kanter wrote in his op-ed piece, "students don't get insightful feedback simply because [the professor] uses a fancy computer program. They get it instead because of the dedication of their professor."

If you want more information on rubrics and the scholarship on providing feedback, contact the Research Academy. Among other items, we have a video recording of Aronson's talk. The Research Academy is currently exploring the possibility of bringing Waypoint Outcomes to Montclair State. If you have any interest in or experience with this tool, please contact us. Furthermore, please contact us if you have done research on feedback to students.

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August 2008
Can You Improve Your Intelligence?

_Want to help your students increase their fluid intelligence, and maybe yours too?   No, fluid intelligence has nothing to do with how much someone understands about fluid mechanics or even how much beer they can consume on Saturday night.   Fluid intelligence (or gF for you technical folks), Wikipedia tells us, "is the ability to find meaning in confusion and solve new problems.   It is the ability to draw inferences and understand the relationships of various concepts, independent of acquired knowledge."   It includes "such abilities as problem-solving, learning, and pattern recognition," and "correlates with measures of abstract reasoning and puzzle solving."

In other words, it's the sort of grey matter ability that one needs to engage in deep learning.    You need high portions of it if you want to analyze, synthesize, and evaluate well.   Students who do have lots of fluid intelligence, so the theory goes, can make connections within the subject area, but they can also generalize and transfer the principles of a particular problem beyond the discipline to new situations.   They are good problem solvers, and are likely to develop adaptive expertise, that is, the ability and attitude that allows them both to recognize and relish the opportunity and necessity for invention.

For decades, the "IQ fundamentalists," as Malcolm Gladwell calls them, have believed that fluid intelligence apparently isn't very fluid.    You are born with a certain amount of it, so the conventional wisdom goes, and that's what you will have for the rest of your life (or at least until dementia sets in).   In the hard version of this "truth," we could just stamp it on the transcripts (or foreheads) of our students when they enter our university and dispense with all those bothersome grading of papers and exams.   Even in the soft version, many faculty members believe that their job is simply to help determine who possesses and is willing to use such intelligence ("put out the effort").

"You can't increase their IQ," one of my colleagues used to say, "so our job is to find out who the really smart one's are and get them to apply themselves."

I must confess.    I never subscribed to such fundamentalism about IQ's, and I have found appealing a variety of critics who have raised questions about it.   Most compelling for me has been the work of people like Carol Dweck, who has found that people who have such fixed views of intelligence (and, correspondingly, their own intelligence) are generally less successful (in school and out) than those people who believe that intelligence is not some central quality, a gF or Fg, but a variety of abilities, each one subject to improvement with lots of the right kind of hard work.   In other words, even if the fundamentalists are right, believing that they are right, can lead to a sense of helplessness in the face of any failure.

There have been other attacks on IQ fundamentalism, of course, including the so-called "Flynn effect," named for James Flynn, a New Zealander, who noticed that average IQ test scores have been going up for decades in every part of the world.   If IQ is something you are born with, how could the human average change so significantly in the course of a few decades?

Now comes the biggest challenge yet.   For IQ fundamentalists it may be like the kid who believes in Santa Claus and spends years trying to find a way to the North Pole, only to discover that the jolly elf isn't real.   A group of researchers have discovered a way to improve performance on measures of fluid intelligence without just giving subjects an opportunity to practice on the test.

As Robert Sternberg noted in his introduction to the research in the May 13, 2008, edition of PNAS (he was not involved with the research), the experiment demonstrates that "fluid intelligence is trainable to a significant and meaningful degree; (ii) the training is subject to dosage effects, with more training leading to greater gains; (iii) the effect occurs across the spectrum of abilities, although it is larger toward the lower end of the spectrum; and (iv) the effect can be obtained by training on problems that, at least superficially, do not resemble those on the fluid-ability tests."

So what is this wonderful training?   It is designed to help people improve what psychologists call "working memory," which theory and research have suggested is connected to gF.   No, that doesn't mean asking students to memorize blindly some list of material helps them improve their fluid intelligence.   It does suggest just one more in a growing series of discoveries that point to things that can make a difference in how well our students learn to think.   Our job is not simply to judge who can do well but to create those conditions that will foster deep learning, adaptive expertise, and all of the abilities associated with fluid intelligence.

I believe strongly that we can all learn how to create those conditions and that the ability to do so is no more ingrained at birth than is the ability to think wisely.   Great teaching requires diligent and proper work, not the lucky inheritance of the teaching gene.

If you would like to "play the game" that led to the improved fluid intelligence, go to www.soakyourhead.com.   You will also need to download and install some operating software from Microsoft (yes, even for Mac users like me), but if you don't have that already installed, the soakyourhead Web site will alert you and lead you to the right place to get it.   It all operates inside a browser like Firefox. Soakyourhead will also link you to the original research article.

Good luck

Ken Bain

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December 2008
Gender Equity in Learning

_The gender gap in math perceived to exist between girls and boys has long been contested. New research published in the journal Science adds clarity to the debate and demonstrates that girls perform better in mathematics in more gender equal societies, in some cases besting male peers.

The research, led in part by Kellogg School of Management Professor Paola Sapienza, sought to address the issue of whether social and cultural factors influence women’s success in math and science. Sapienza and her colleagues Luigi Guiso (Instituto Universitario Europeo) and Ferdinando Monte and Luigi Zingales (University of Chicago), empirically investigated whether a global gender gap exists in math to understand the relative importance of biology and culture on the development of basic mental attributes that are valuable for conducting math and science.

“The so-called gender gap in math skills seems to be at least partially correlated to environmental factors,” says Sapienza. “The gap doesn’t exist in countries in which men and women have access to similar resources and opportunities.”

In search of bridges across the math gender gap, Sapienza and her colleagues analyzed data from more than 276,000 children in 40 countries. The large number of subjects and broad range of social systems represented were key to the validity of the study. Each child took the 2003 Organisation for Economic Co-operation and Development Programme for International Student Assessment (PISA), an internationally standardized assessment of math, reading, science and problem-solving ability.

Based on the PISA analysis, Sapienza and her colleagues determined that while the global pattern shows that boys tended to outperform girls in math (on average girls score 10.5 points lower than boys), this advantage was not always the case. In a few countries, including Iceland, Sweden and Norway, girls scored as well as boys or better.

Sapienza and colleagues examined social features that might explain the variance from country to country. The team used four tools to measure how well women were integrated into each society compared with men. These tools were the 2006 Gender Gap Index (GGI) developed by the World Economic Forum (WEF); the World Values Survey; the percentage of women aged 15 or older who are eligible to work in each country’s labor force; and the WEF political empowerment index, which measures the representation of women in government.

Sapienza’s team found that, in more gender equal societies, the gender gap in math disappears. For example, the math gender gap almost disappeared in Sweden (GGI = 0.81), while girls scored 23 points below boys in math in Turkey. Not only did average girls’ scores improve as equality improved, but the number of girls reaching the highest levels of performance also increased.

Math and science rates for girls in the U.S., which ranks 23rd on the GGI scale, fell in the middle of the pack. On average, U.S. girls score almost 10 points lower than U.S. boys in mathematics, which is around the average for all countries analyzed in the study.

The research also found a striking gender gap in reading skills. In every country girls perform better than boys in reading. In more gender equal societies, the girls’ advantage in reading over boys increases further. On average, girls have reading scores that are 32.7 points higher than those of boys (6.6 percent higher than the mean average score for boys). In Turkey, this amounts to 25.1 points higher and in Iceland, girls score 61.0 points higher.

To read more about this research, go here: Full article.

Related research:
Allport's Legacy and the Situational Press of Stereotypes. Fall, 1999. Journal of Social Issues. David M. Marx, Joseph L. Brown, Claude M. Steele.

Thin ice: Stereotype threat and Black college students. August 1999. The Atlantic Online. Claude M. Steele

Gender Differences in Beliefs and Achievement: A Cross-Cultural Study. March 1990. Developmental Psychology. Max Lummis, Harold W. Stevenson.

Stereotype threat and the intellectual test performance of African Americans. November 1995. Journal of Personality and Social Psychology. Claude M.Steele; Joshua Aronson.

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