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Learning Strategies Outperform IQ in Predicting Achievement

The views expressed are those of the author and are not necessarily those of Scientific American.

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In the 1960s, the legendary psychologist Albert Bandura rejected the view that learning is passive. Instead he emphasized the importance of the active use of learning strategies. Today, Bandura’s legacy lives on, and has been extended in exciting new directions.

Grounded in Bandura’s pioneering research, in 1986 Barry Zimmerman and Martinez Pons published a paper that helped spur an entire new field of study on self-regulated learning strategies. Zimmerman and Pons interviewed 40 tenth-grade students who were on a “high achievement track” and compared their responses against those of 40 tenth-graders who were in “lower achievement tracks.” Specifically, they asked the students about the learning strategies they used to participate in class, study, and complete their assignments. Through the course of their interviews, they identified fourteen self-regulated learning strategies. They found that the high-achieving students differed from the low-achieving students in regard to whether they used these strategies, how much they used the strategies, and their consistency in using the strategies.

Over the past few decades there have been multiple studies showing the effectiveness of the self-regulated learning strategies approach using a variety of methodologies (e.g., think-aloud protocols, diaries, observation). In one recent large review, John Dunlosky and colleagues evaluated the relative utility of ten learning strategies. While some of the learning strategies (e.g., highlighting, rereading) were found to have low utility in benefitting learning outcomes, the following strategies were assessed as having moderate to high utility: practice testing (high), distributed practice (high), elaborative interrogation (medium), self-explanation (medium), and interleaved practice (medium). Practice testing had the most evidence supporting its benefits for learning across context and over time.

Researchers have also recently begun to integrate the learning strategies approach with the expert performance approach. A plethora of research shows that a very deliberate type of practice involving the active use of strategies to maximize performance and overcome limitations is essential to greatness across many domains, including the arts, sciences, and sports. Excitedly, recent research suggests that the expert performance approach can also be applied to increase our understanding of the acquisition of school-based knowledge.

In one study, Kiruthiga Nandagopal and K. Anders Ericsson investigated the use of self-regulated learning strategies among advanced undergraduate bioscience majors. Because these students “made active decisions to embark on the road to acquiring expertise in the biological sciences,” they met the expert performance approach criteria. Adopting one of the key methodologies of the expert performance approach, they analyzed student diaries over the course of three weeks, estimating the presence, frequency, and duration (in terms of total number of hours) of self-regulated learning strategies. They grouped fourteen self-regulated learning strategies into six main categories: self-regulating (self-assessing, goal-setting, planning, and so on), organizing, seeking information, mnemonic usage, seeking social assistance (for instance, seeking assistance from peers, tutors, and professors), and reviewing (reviewing prior problems, notes, textbook, and such). Then they compared the diary responses among the following three groups of achievers based on their GPA before entering the course: high-achieving students (GPA > 3.7), average-achieving students (GPA ≥ 3) and low-achieving students (GPA < 3).

Comparing the diary responses of the different groups of achievers, they found that the high-achieving students reported employing a larger number of different strategies. The high-achieving students were particularly more likely to engage in organizing and transforming, seeking information, and reviewing strategies compared to the low-achieving students. Timing was also critical. While students engaged in organizing, transforming, and reviewing notes more frequently and for longer stretches of time during the midterm week than other weeks, high-achieving students sought more assistance from their peers and spent more time studying during midterm weeks compared to low-achieving students. In contrast, low-achieving students engaged in these strategies more than average-achieving students toward the end of the semester. High-achieving students also spent more time overall in study-related activities earlier in the semester compared to average and low-achieving students, whereas there was no such difference between the groups later on in the semester.

The most important learning strategies for predicting end-of-semester GPA were (1) seeking information, (2) reviewing the textbook, and (3) seeking assistance from peers during the midterm week. While the correlation between prior SAT scores and semester GPA was significant, once the most predictive learning strategies were considered, prior SAT scores didn’t explain any additional variation in end of semester GPA. Considering  IQ scores (which are highly correlated with SAT scores) are known to be excellent predictors of academic achievement, this finding is actually quite striking! While these findings certainly don’t invalidate the predictive value of IQ tests, they do suggest that one of the crucial reasons why those with higher general cognitive ability tend to do so well across so many learning situations is due, in large part, to their use of efficient learning strategies that maximize learning outcomes.

This idea is consistent with a fascinating study conducted by Nandagopal, Roy Roring, and Jeanette Taylor. They had twins think aloud while they were taking three cognitive tests that are significantly correlated with IQ–  associative learning, working memory, and processing speed. After analyzing the thought processes of the participants, the researchers found that performance on all three cognitive tests was heavily influenced by cognitive strategies (e.g., mnemonic encoding techniques). Most compellingly, differences in strategy use on the associative learning task (which was most amenable to the use of strategies) explained a significant amount of the genetic influences on performance. While there certainly needs to be more research on the development of learning strategies, this study is the first to demonstrate that the heritability of performance on cognitive tasks is due, in part, to the use of specific cognitive strategies.

Another recent study further supports the importance of learning strategies for predicting long-term growth and achievement. Kou Murayama and colleagues investigated the simultaneous prediction of motivation, learning strategies and IQ for explaining the long-term growth in mathematics achievement from Grades 5 to 10 among a sample of German students. Their measure of math achievement tested competencies such as arithmetic, algebra, and geometry. At the start of their study, IQ, motivation, and learning strategies significantly predicted math performance, with motivation and learning strategies adding additional prediction above IQ.

A different story emerged, however, once they looked at the predictors of long-term growth. IQ was not related to growth in mathematics achievement after taking into account demographic information. In contrast, perceived control (e.g., “When doing math, the harder I try, the better I perform”), intrinsic motivation (e.g., “I invest a lot of effort in math, because I am interested in the subject”), and deep learning strategies (e.g., “When I study for exams, I try to make connections with other areas of math”), significantly predicted growth of mathematics knowledge. What’s more, surface learning strategies (“For some math problems I memorize the steps to the correct solution”) negatively predicted mathematics growth.

The researchers related their findings to The Matthew Effect: those with high intrinsic motivation and effective learning strategies will tend to increase their ability, while those without those characteristics will tend to decrease their ability. Over time, the gap between those with higher ability and those with lower ability will widen. Which is all the more reason why we ought to set up the right conditions for active engagement for everyone, and teach people the proper strategies for success.

If you’d like to learn more about different kinds of minds and the many paths to greatness, you may be interested in my forthcoming book “Ungifted: Intelligence Redefined, coming out this summer from Basic Books.

© 2013 Scott Barry Kaufman, All Rights Reserved

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Scott Barry Kaufman About the Author: Scott Barry Kaufman is Scientific Director of The Imagination Institute in the Positive Psychology Center at the University of Pennsylvania. Follow on Twitter @sbkaufman.

The views expressed are those of the author and are not necessarily those of Scientific American.

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  1. 1. jstevewhite 12:43 pm 04/8/2013

    I don’t know that I think the research described says what the author seems to think it says – or even the researchers. Saying, for instance, that someone who has a marginally lower IQ and works harder will outperform someone who has a marginally higher IQ and doesn’t work as hard doesn’t seem surprising at all, *nor* does it invalidate the concept of IQ or “g”. It *does* appear to indicate that certain learning strategies and cognitive strategies perform better than others (another big non-surprise).

    To achieve the result this article is looking for, I would suggest a study where people of disparate IQ are all taught the specific, beneficial cognitive and learning strategies discovered by these studies. If, in this instance, the cognitive performance ceases to be differentiated by IQ, then one can certainly claim that those strategies are “more important than IQ” in determining cognitive performance. If the IQ related differentiation remains, then one cannot rationally make that claim.

    The upshot of this article seems to me to be roughly equivalent to “Athletes that train properly outperform those who don’t train properly.”

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  2. 2. rshoff 1:05 pm 04/8/2013

    Perhaps it’s not the learning strategies at all that lead to the higher GPA. Perhaps it is that higher cognitive functioning students are more prone to cognitive driven behaviors, that when grouped, are viewed as ‘learning strategies’.

    In other words, birds fly because they can. You cannot teach horse to fly regardless of ‘strategies’ you encourage them to employ. A horse is a horse, of course.

    Although I enjoyed reading the article, being a cow for now, I’m not sure what point the article is making… Is the thesis that learning is an active process? Isn’t that something we already know? Or is the article trying to say that instead of using our best resources to better educate high cognitive functioning students we should waste more resources trying to encourage low performing students to employ self-regulated active learning strategies so they can also be mediocre contributors.

    I think a win-win is to appropriately educate youth. There is no reason to artificially close the gap between the high functioning and the low functioning students. Appropriately educated individuals will find a productive life whether it be labor, trades, leadership, sciences, etc. It’s all good.

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  3. 3. rshoff 1:10 pm 04/8/2013

    Ok, the thesis may be in the title. But titles and headlines have been used in such meaningless ways by editors, that they are misleading as to the content of the article.

    So, if someone has a child, or responsibility for educating a child, then they should look at what learning strategies are being employed by that child to predict achievement. Then what?

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  4. 4. string_beery 3:46 pm 04/8/2013

    good article, but as one of the reference papers noted, teaching effective learning techniques is only one part of a solution for student learning…before they can be taught effective learning techniques, students must first be ready to learn…

    i’d like to see (a lot) more on the motivational component, in particular for pre-college students – how do you teach anything to a student who arrives at school with little to no sign of motivation? attempts to teach such students learning techniques seems unlikely to be any more successful than attempts to teach them anything else…i’m not trying to blame these students, just looking to address an all-too-common reality…

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  5. 5. EvolvingApe 4:46 pm 04/8/2013

    This is another piece of “feel good” science, attempting to obfuscate the fact that not all humans perform equally at a given task and that IQ result are a significant predictor.

    As others pointed above, the basic conclusions are fairly obvious, but the spin and presentation of the results are basically a messy, blinding and ultimately confusing “word-storm.”

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  6. 6. cvalvarez 6:07 pm 04/8/2013

    Interesting article! Thanks for pulling together these studies relating basic cognitive abilities and metacognitive strategies. The good news is that I think people do have more control over the latter, and direct instruction of learning strategies could help students who haven’t yet discovered them on their own.

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  7. 7. jtdwyer 12:01 pm 04/9/2013

    I suspect these findings reflect mostly on the bases of the grade point system than any long term learning realized. It’s long been known by achievement motivated students that focused memorization of study materials is the most reliable method of attaining immediate grade point objectives.

    So this posting seems simply to argue that success in school (at least at elementary levels) is more a function of motivation and effort than intellect. I’m flabbergasted!

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  8. 8. bucketofsquid 4:43 pm 04/9/2013

    The very concept of IQ is idiotic. First there was 1 kind of general IQ now there are several kinds of IQ and yet, many people with supposedly less than optimal scores in one or more of the areas of IQ do quite well in life which is odd since IQ is the general ability to acquire and apply knowledge for survival and prosperity. I know a brick layer that is academically on par with a fence post but he out earns me somewhat and I write software for a living at a decent salary.

    I guess the real take away from this article is that children that are taught to value education and are taught good learning strategies will do better than children that only have one or neither learned component. The genetic component is primarily assumed without evidence because children learn their initial behavior patterns from the people around them. Well off families that value education tend to end up with motivated children that value education. These same families tend to use good study practices so the children learn those strategies.

    I did find one study that compared twins adopted by different families but based on the era it was done in and the obvious racial bias I doubt it was at all accurate.

    On IQ tests I tend to score upper genius to lower super genius (or gifted to very gifted). When I look at my life over all, I’m pretty sure there isn’t much genius in there but there seems to be a fair amount of nitwit. I’ve been able to ace tests on subjects I know very little about simply by careful word analysis and selecting terms that sound likely. I’m pretty sure I couldn’t do that on a graduate student level of test. I got out of high school with a 3.25 and undergrad college with a 3.9 GPA. I did this mainly by gaming the tests (not cheating) and consolidating other people’s ideas into my projects so I did more than my class mates.

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  9. 9. JoeJeffrey 12:16 pm 04/14/2013

    The research is interesting and provocative. Most important, it is practical: though couched in the unfortunate educator jargon of “learning strategies,” the core idea is an old and well-understood one: if you want someone to learn something, get them to **do the things requiring the concept or skill.** That’s what practice and work sheets have always been about. Look at the results and set the interpretation aside: in every case, it’s the students **doing** the thing: seeking help, asking friends, asking professors, etc. The downside of the article is the clear bias against the idea the people have different levels of ability, or abilities. I never had the ability to play major league baseball, though I loved baseball and played it at every opportunity as a kid. I’ll never have the math ability of a Richard Feynman (nor will most of us). In their well-meaning effort to get everyone to achieve all they can, many education researchers push their agenda that if you have the right “strategy” and get treated right by teachers, you’ll be as good as anyone. The really bad effect of their bias is that it gives everyone reason to distrust their results, even when those results are valuable.

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  10. 10. gmarcjj 3:05 pm 01/22/2015

    g is a theoretical and psychometric construct, and as such, rarely contributes useful insight in the applied setting or for clinicians, practitioners or educators who are charged with designing interventions for learning. this is great for diverse learners, whether struggling verbally or with language, developmentally, self-regulatory strategies are learned and acquired behaviors and there is extant research to suggest that teaching strategies to high achieving students is a complete waste of time as they benefit the LEAST from strategy development, making marginal or insignificant improvement on any learning task whether its recall, comprehension, or fluency, you name it. Unlike g which is largely inheritable, students are not born knowing how to regulate their own learning and those that are weaker can be strengthened

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