Latest Research News
In the education world, fixed mind-set is usually contrasted with growth mind-set. In this context, fixed mind-set refers to students holding the idea that their cognitive abilities, including their intelligence, are set at birth, and they just have to accept their limitations. With a growth mind-set, however, the student recognizes that, although it might be difficult, they can grow their abilities.
A growth mind-set has been associated with a much better approach to learning and improved academic achievement, but new research suggests that this difference has been over-stated.
A recent meta-analysis of growth mind-set research found that
- over half the effect sizes weren't significantly different from zero (157 of 273 effect sizes),
- a small number (16) actually found a negative association between growth mind-set and academic achievement, and
- a little over a third (100) were significant and positive.
Overall, the study found the correlation between growth mind-set and academic achievement was very weak.
Perhaps unsurprisingly, one important factor was age — children and teenagers showed significant effects, while adults did not. Interestingly, neither academic risk status nor socioeconomic status was a significant factor, although various studies have suggested that growth mind-set is much more important for at-risk students.
A second, smaller meta-analysis was carried out to investigate whether growth-set interventions made a significant impact on academic achievement. Such interventions are designed to increase students' belief that intelligence (or some other attribute) can be improved with effort.
The study found that
- 37 of the 43 effect sizes (86%) were not significantly different from zero,
- one effect size was negative, and
- five were positive.
Age was not a factor, nor was at-risk status. However, socioeconomic status was important, in that students from low-SES households were significantly impacted by a growth mind-set intervention, while those from higher-SES households were not.
The type of intervention was important: just reading about growth mind-set didn't help; doing something more interactive, such as writing a reflection, did. The number of sessions didn't have an effect. Oddly, the way the intervention was presented made a difference, with materials presented by computer or by a person not being effective, while print materials were. Interventions administered during regular classroom activities were not effective, but interventions that occurred outside regular activities did have a significant effect.
Taken overall, the depressing conclusion is that mind-set interventions are not the revolution some have touted them as. The researchers point out that previous research (Hattie et al 1996) found that the meta-analytic average effect size for a typical educational intervention on academic performance is 0.57, and all the meta-analytic effects of mind-set interventions in this study were smaller than 0.35 (and most were null).
All this is to say, not that mind-set theory is rubbish, but that it is not as straightforward and miraculous as it first appeared. Mind-set itself is more nuanced than has been presented. For example, do we really have a definite fixed mind-set or growth mind-set? Or is it that we have different mind-sets for different spheres? Perhaps we believe that our math ability is fixed, but our musical ability is something that can be developed. That we can develop our problem-solving ability, but our intelligence is set in stone. That our 'natural talents' can be grown, but our 'innate weaknesses' cannot.
Why would low-SES and high-risk students benefit from a growth mind-set intervention, while higher-SES students did not? An obvious answer lies in the beliefs held by such students. For example, it may be that many higher-SES students are challenged by the idea of a growth mind-set, because they're invested in the idea of their own natural abilities. It is their confidence in their own abilities that enables them to do well, just as other students are undermined by their lack of confidence. Given this different starting point, it would not be in any way surprising if such students responded differently to mind-set interventions.
Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To What Extent and Under Which Circumstances Are Growth Mind-Sets Important to Academic Achievement? Two Meta-Analyses. Psychological Science, 29(4), 549–571. http://doi.org/10.1177/0956797617739704
Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of learning skills interventions on student learning: A meta-analysis. Review of Educational Research, 66, 99–136.
I've reported before on studies showing how gesturing can help children with mathematics and problem-solving. A new Australian study involving children aged 9-13 has found that finger-tracing has a similar effect.
Students who used their finger to trace over practice examples while simultaneously reading geometry or arithmetic material were able to complete the problems more quickly and correctly than those who didn't use the same technique.
In the first experiment, involving 52 students aged 11-13, some students were instructed to use their index fingers to trace elements of worked examples in triangle geometry, involving two angle relationships (Vertical angles are equal; Any exterior angle equals the sum of the two interior opposite angles.). Students were given two minutes to study a short instructional text on the relationships and how they can be used to solve particular problems. They were then given two minutes to study two worked examples. The tracing group were given additional instruction in how to use their index finger to trace out highlighted elements. The non-tracing group were told to keep their hands in their lap. Testing consisted of six questions, two of which were the same as the acquisition problems but with different numbers, and four of which were transfer questions, requiring more thoughtful responses.
A ceiling effect meant there was no difference between the two groups on the first two test questions. The tracing group answered significantly more transfer questions, although the difference wasn't great. There was no difference in how difficult the groups rated the test items.
In the second experiment, involving 54 Year 4 students, the instruction and problems concerned the fundamental order of operations. The tracing group were told to trace the operation symbols. The tracing group did significantly better, although again, the difference wasn't great, and again, there was no difference in assessment of problem difficulty.
In another experiment, involving 42 Year 5 students (10-11 years), students were given 5 minutes to study three angle relationships involving parallel lines (vertical angles are equal; corresponding angles are equal; the sum of co- interior angles is 180°). While answers to the 'basic' test questions failed to show significant differences, on the advanced transfer problems, the tracing group solved significantly more test questions than the non-tracing group, solved them more quickly, made fewer errors, and reported lower levels of test difficulty.
In the final experiment, involving 72 Year 5 students, on the advanced test problems, students who traced on the paper outperformed those who traced above the paper, who in turn outperformed those who simply read the material.
The researchers claim the findings support the view that tracing out elements of worked examples helps students construct good mental schemas, making it easier for them to solve new problems, and reducing cognitive demand.
As with gesturing, the benefits of tracing are not dramatic, but I believe the pattern of these results support the view that, when cognitive load is high (something that depends on the individual student as well as the task and its context), tracing key elements of worked examples might be a useful strategy.
Further research looking at individual differences would be helpful. I think greater benefits would be shown for students with low working memory capacity.
(2015). Getting the point: Tracing worked examples enhances learning.
Learning and Instruction. 35, 85 - 93.
(2015). Learning By Tracing Worked Examples.
Applied Cognitive Psychology. n/a - n/a.
A natural experiment involving 5,740 participants in a MOOC ( massive open online course) has found that when students were asked to assess each other's work, and the examples were exceptional, a large proportion of students dropped the course.
In the MOOC, as is not uncommon practice, course participants were asked to write an essay and then to grade a random sample of their peers' essays. Those randomly assigned to evaluate exemplary peer essays were dramatically more likely to quit the course than those assigned to read more typical essays.
Specifically, around 68% of students who graded essays of average quality finished and passed the course, earning a certificate. Among those who graded slightly above average essays (more than one standard deviation above the class mean, 7.5/9), 64% earned a certificate. But among those who graded the best essays (those more than 1.6 SDs above the mean), only 45% earned a certificate.
These numbers can be compared to the fact that 75% of students who wrote an average essay earned a certificate, and 95% of those who wrote a 'perfect' essay, 9/9, earned a certificate. The difference between these numbers is about the same (in fact, slightly less) than the effect of grading average vs top essays.
A follow-up study, involving 361 participants, simulated this setting, in order to delve into what the students thought. Participants, recruited via Amazon's Mechanical Turk, were asked to write a minimum of 500 characters in response to a quote and essay prompt. They were told the best responses would go into a lottery to win a bonus. They were then asked to assess two very short essays (about 200 words) supposedly written by peers. These were either both well-written, or both poorly-written. This was followed by some questions about what they felt and thought, and an opportunity to write a second essay.
Unsurprisingly, those who were given exceptional essays to grade felt significantly less able to write an essay as good as those. They also decided that the ability to write an excellent short answer to such philosophical questions was not very important or relevant to them, and were much more likely not to write another essay (43% of those who read the poor essays went on to try again, while only 27% of those who read the excellent essays did so).
Until now, research has mainly focused on how students respond when peer work is of a standard that the student is likely to see as “attainable”. This research shows how comparisons that are seen as unattainable may do more harm than good.
(2016). Discouraged by Peer Excellence Exposure to Exemplary Peer Performance Causes Quitting.
Psychological Science. 0956797615623770.
A study of 438 first- and second-grade students and their primary caregivers has revealed that parents' math anxiety affects their children's math performance — but (and this is the surprising bit) only when they frequently help them with their math homework.
The study builds on previous research showing that students learn less math when their teachers are anxious about math. This is not particularly surprising, and it wouldn't have been surprising if this study had found that math-anxious parents had math-anxious children. But the story wasn't that simple.
Children were assessed in reading achievement, math achievement and math anxiety at both the beginning and end of the school year. Children of math-anxious parents learned significantly less math over the school year and had more math anxiety by the year end—but only if math-anxious parents reported providing help every day with math homework. When parents reported helping with math homework once a week or less often, children’s math achievement and attitudes were not related to parents’ math anxiety. Reading achievement (included as a control) was not related to parents' math anxiety.
Interestingly, the parents' level of math knowledge didn't change this effect (although this is less surprising when you consider the basic-level of math taught in the 1st and 2nd grade).
Sadly, the effect still held even when the teacher was strong in math.
It's suggested that math-anxious parents may be less effective in explaining math concepts, and may also respond less helpfully when children make a mistake or solve the problem in a non-standard way. People with high math anxiety tend to have poor attitudes toward math, and also a high fear of failing at math. It's also possible (likely even) that they will have inflexible attitudes to how a math problem “should” be done. All of these are likely to demotivate the child.
Analysis also indicated that it is not that parents induced math anxiety in their children, who thus did badly, but that their homework help caused the child to do poorly, thus increasing their math anxiety.
Information about parental anxiety and how often parents helped their children with math homework was collected by questionnaire. Math anxiety was assessed using the short (25-item) Math Anxiety Rating Scale. The question, “How often do you help your child with their math homework?” was answered on a 7-point scale (1 = never, 2 = once a month, 3 = less than once a week, 4 = once a week, 5 = 2–3 times a week, 6 = every day, 7 = more than once a day). The mean was 5.3.
The finding points to the need for interventions focused on both decreasing parents' math anxiety and scaffolding their skills in how to help with math homework. It also suggests that, in the absence of such support, math-anxious parents are better not to help!
(2015). Intergenerational Effects of Parents’ Math Anxiety on Children’s Math Achievement and Anxiety.
Psychological Science. 0956797615592630.
There's been a lot of talk in recent years about the importance of mindset in learning, with those who have a “growth mindset” (ie believe that intelligence can be developed) being more academically successful than those who believe that intelligence is a fixed attribute. A new study shows that a 45-minute online intervention can help struggling high school students.
The study involved 1,594 students in 13 U.S. high schools. They were randomly allocated to one of three intervention groups or the control group. The intervention groups either experienced an online program designed to develop a growth mindset, or an online program designed to foster a sense of purpose, or both programs (2 weeks apart). All interventions were expected to improve academic performance, especially in struggling students.
The interventions had no significant benefits for students who were doing okay, but were of significant benefit for those who had an initial GPA of 2 or less, or had failed at least one core subject (this group contained 519 students; a third of the total participants). For this group, each of the interventions was of similar benefit; interestingly, the combined intervention was less beneficial than either single intervention. It's plausibly suggested that this might be because the different messages weren't integrated, and students may have had some trouble in taking on board two separate messages.
Overall, for this group of students, semester grade point averages improved in core academic courses and the rate at which students performed satisfactorily in core courses increased by 6.4%.
GPA average in core subjects (math, English, science, social studies) was calculated at the end of the semester before the interventions, and at the end of the semester after the interventions. Brief questions before and after the interventions assessed the students' beliefs about intelligence, and their sense of meaningfulness about schoolwork.
GPA before intervention was positively associated with a growth mindset and a sense of purpose, explaining why the interventions had no effect on better students. Only the growth mindset intervention led to a more malleable view of intelligence; only the sense-of-purpose intervention led to a change in perception in the value of mundane academic tasks. Note that the combined intervention showed no such effects, suggesting that it had confused rather than enlightened!
In the growth mindset intervention, students read an article describing the brain’s ability to grow and reorganize itself as a consequence of hard work and good strategies. The message that difficulties don't indicate limited ability but rather provide learning opportunities, was reinforced in two writing exercises. The control group read similar materials, but with a focus on functional localization in the brain rather than its malleability.
In the sense-of-purpose interventions, students were asked to write about how they wished the world could be a better place. They read about the reasons why some students worked hard, such as “to make their families proud”; “to be a good example”; “to make a positive impact on the world”. They were then asked to think about their own goals and how school could help them achieve those objectives. The control group completed one of two modules that didn't differ in impact. In one, students described how their lives were different in high school compared to before. The other was much more similar to the intervention, except that the emphasis was on economic self-interest rather than social contribution.
The findings are interesting in showing that you can help poor learners with a simple intervention, but perhaps even more, for their indication that such interventions are best done in a more holistic and contextual way. A more integrated message would hopefully have been more effective, and surely ongoing reinforcement in the classroom would make an even bigger difference.
(2015). Mind-Set Interventions Are a Scalable Treatment for Academic Underachievement.
Psychological Science. 26(6), 784 - 793.
Three classroom experiments have found that students who meditated before a psychology lecture scored better on a quiz that followed than students who did not meditate. Mood, relaxation, and class interest were not affected by the meditation training.
The noteworthy thing is that the meditation was very very basic — six minutes of written meditation exercises.
The effect was stronger in classes where more freshmen students were enrolled, suggesting that the greatest benefit is to those students who have most difficulty in concentrating (who are more likely to drop out).
The finding suggests the value in teaching some active self-reflection strategies to freshmen, and disadvantaged ones in particular.
It’s reasonable to speculate that more extensive training might increase the benefits.
And in another recent meditation study, a two week mindfulness course significantly improved both Graduate Record Exam reading comprehension scores and working memory capacity.
The study involved 48 undergrads who either attended the mindfulness course or a nutrition class. Each 45-minute class met eight times over two weeks. Mindfulness training was associated with a 16-percentile boost in GRE scores, on average. Mind wandering also significantly decreased. The healthy nutrition course had no effect on any of these factors.
(Submitted). Meditation in the Higher-Education Classroom: Meditation Training Improves Student Knowledge Retention during Lectures.
Mindfulness. 1 - 11.
(2013). Mindfulness Training Improves Working Memory Capacity and GRE Performance While Reducing Mind Wandering.
A new study claims to provide ‘some of the strongest evidence yet’ for the benefits of gesturing to help students learn.
The study involved 184 children aged 7-10, of whom half were shown videos of an instructor teaching math problems using only speech, while the rest were shown videos of the instructor teaching the same problems using both speech and gestures. The problem involved mathematical equivalence (i.e., 4+5+7=__+7), which is known to be critical to later algebraic learning.
Students who learned from the gesture videos performed substantially better on a test given immediately afterward than those who learned from the speech-only video (average proportion correct around 42% vs 31% — approximations because I’m eyeballing the graph), and, unlike the speech-only group, showed further improvement on a test 24 hours later (around 46% vs 30%). They also showed stronger transfer to different problem types (35% vs 22%).
(2013). Consolidation and Transfer of Learning After Observing Hand Gesture.
Child Development. n/a - n/a.
In contradiction of some other recent research, a large new study has found that offering students rewards just before standardized testing can improve test performance dramatically. One important factor in this finding might be the immediate pay-off — students received their rewards right after the test. Another might be in the participants, who were attending low-performing schools.
The study involved 7,000 students in Chicago public schools and school districts in south-suburban Chicago Heights. Older students were given financial rewards, while younger students were offered non-financial rewards such as trophies.
Students took relatively short, standardized diagnostic tests three times a year to determine their grasp of mathematics and English skills. Unusually for this type of research, the students were not told ahead of time of the rewards — the idea was not to see how reward improved study habits, but to assess its direct impact on test performance.
Consistent with other behavioral economics research, the prospect of losing a reward was more motivating than the possibility of receiving a reward — those given money or a trophy to look at while they were tested performed better.
The most important finding was that the rewards only ‘worked’ if they were going to be given immediately after the test. If students were told instead that they would be given the reward sometime later, test performance did not improve.
Follow-up tests showed no negative impact of removing the rewards in successive tests.
Age and type of reward mattered. Elementary school students (who were given nonfinancial rewards) responded more to incentives than high-school students. Younger students have been found to be more responsive to non-monetary rewards than older students. Among high school students, the amount of money involved mattered.
It’s important to note that the students tested had low initial motivation to do well. I would speculate that the timing issue is so critical for these students because distant rewards are meaningless to them. Successful students tend to be more motivated by the prospect of distant rewards (e.g., a good college, a good job).
The finding does demonstrate that a significant factor in a student’s poor performance on tests may simply come from not caring to try.
A review of 10 observational and four intervention studies as said to provide strong evidence for a positive relationship between physical activity and academic performance in young people (6-18). While only three of the four intervention studies and three of the 10 observational studies found a positive correlation, that included the two studies (one intervention and one observational) that researchers described as “high-quality”.
An important feature of the high-quality studies was that they used objective measures of physical activity, rather than students' or teachers' reports. More high-quality studies are clearly needed. Note that the quality score of the 14 studies ranged from 22%! to 75%.
Interestingly, a recent media report (NOT, I hasten to add, a peer-reviewed study appearing in an academic journal) spoke of data from public schools in Lincoln, Nebraska, which apparently has a district-wide physical-fitness test, which found that those were passed the fitness test were significantly more likely to also pass state reading and math tests.
Specifically, data from the last two years apparently shows that 80% of the students who passed the fitness test either met or exceeded state standards in math, compared to 66% of those who didn't pass the fitness test, and 84% of those who passed the fitness test met or exceeded state standards in reading, compared to 71% of those who failed the fitness test.
Another recent study looks at a different aspect of this association between physical exercise and academic performance.
The Italian study involved138 normally-developing children aged 8-11, whose attention was tested before and after three different types of class: a normal academic class; a PE class focused on cardiovascular endurance and involving continuous aerobic circuit training followed by a shuttle run exercise; a PE class combining both physical and mental activity by involving novel use of basketballs in varying mini-games that were designed to develop coordination and movement-based problem-solving. These two types of physical activity offered the same exercise intensity, but very different skill demands.
The attention test was a short (5-minute) paper-and-pencil task in which the children had to mark each occurrence of “d” with double quotation marks either above or below in 14 lines of randomly mixed p and d letters with one to four single and/or double quotation marks either over and/or under each letter.
Processing speed increased 9% after mental exercise (normal academic class) and 10% after physical exercise. These were both significantly better than the increase of 4% found after the combined physical and mental exertion.
Similarly, scores on the test improved 13% after the academic class, 10% after the standard physical exercise, and only 2% after the class combining physical and mental exertion.
Now it’s important to note is that this is of course an investigation of the immediate arousal benefits of exercise, rather than an investigation of the long-term benefits of being fit, which is a completely different question.
But the findings do bear on the use of PE classes in the school setting, and the different effects that different types of exercise might have.
First of all, there’s the somewhat surprising finding that attention was at least as great, if not better, after an academic class than the PE class. It would not have been surprising if attention had flagged. It seems likely that what we are seeing here is a reflection of being in the right head-space — that is, the advantage of continuing with the same sort of activity.
But the main finding is the, also somewhat unexpected, relative drop in attention after the PE class that combined mental and physical exertion.
It seems plausible that the reason for this lies in the cognitive demands of the novel activity, which is, I think, the main message we should take away from this study, rather than any comparison between physical and mental activity. However, it would not be surprising if novel activities that combine physical and mental skills tend to be more demanding than skills that are “purely” (few things are truly pure I know) one or the other.
Of course, it shouldn’t be overlooked that attention wasn’t hampered by any of these activities!
(2012). Physical Activity and Performance at School: A Systematic Review of the Literature Including a Methodological Quality Assessment.
Arch Pediatr Adolesc Med. 166(1), 49 - 55.
(2012). Effects of Varying Type of Exertion on Children’s Attention Capacity.
Medicine & Science in Sports & Exercise. 44(3), 550 - 555.
First study: http://blogs.edweek.org/edweek/schooled_in_sports/2012/01/strong_evidenc...
Second study: http://blogs.edweek.org/edweek/schooled_in_sports/2011/11/students_fitne...
Third study: http://news.yahoo.com/exercise-might-boost-kids-academic-ability-1602081...
Students come into classrooms filled with inaccurate knowledge they are confident is correct, and overcoming these misconceptions is notoriously difficult. In recent years, research has shown that such false knowledge can be corrected with feedback. The hypercorrection effect, as it has been termed, expresses the finding that when students are more confident of a wrong answer, they are more likely to remember the right answer if corrected.
This is somewhat against intuition and experience, which would suggest that it is harder to correct more confidently held misconceptions.
A new study tells us how to reconcile experimental evidence and belief: false knowledge is more likely to be corrected in the short-term, but also more likely to return once the correction is forgotten.
In the study, 50 undergraduate students were tested on basic science facts. After rating their confidence in each answer, they were told the correct answer. Half the students were then retested almost immediately (after a 6 minute filler task), while the other half were retested a week later.
There were 120 questions in the test. Examples include: What is stored in a camel's hump? How many chromosomes do humans have? What is the driest area on Earth? The average percentage of correct responses on the initial test was 38%, and as expected, for the second test, performance was significantly better on the immediate compared to the delayed (90% vs 71%).
Students who were retested immediately gave the correct answer on 86% of their previous errors, and they were more likely to correct their high-confidence errors than those made with little confidence (the hypercorrection effect). Those retested a week later also showed the hypercorrection effect, albeit at a much lower level: they only corrected 56% of their previous errors. (More precisely, on the immediate test, corrected answers rose from 79% for the lowest confidence level to 92% for the highest confidence. On the delayed test, corrected answers rose from 43% to 70% on the second highest confidence level, 64% for the highest.)
In those instances where students had forgotten the correct answer, they were much more likely to reproduce the original error if their confidence had been high. Indeed, on the immediate test, the same error was rarely repeated, regardless of confidence level (the proportion of repeated errors hovered at 3-4% pretty much across the board). On the delayed test, on the other hand, there was a linear increase, with repeated errors steadily increasing from 14% to 23% as confidence level rose (with the same odd exception — at the second highest confidence level, proportion of repeated errors suddenly fell).
Overall, students were more likely to correct their errors if they remembered their error than if they didn’t (72% vs 65%). Unsurprisingly, those in the immediate group were much more likely to remember their initial errors than those in the delayed group (85% vs 61%).
In other words, it’s all about relative strength of the memories. While high-confidence errors are more likely to be corrected if the correct answer is readily accessible, they are also more likely to be repeated once the correct answer becomes less accessible. The trick to replacing false knowledge, then, is to improve the strength of the correct information.
Thus, as recency fades, you need to engage frequency to make the new memory stronger. So the finding points to the special need for multiple repetition, if you are hoping to correct entrenched false knowledge. The success of immediate testing indicates that properly spaced retrieval practice is probably the best way of replacing incorrect knowledge.
Of course, these findings apply well beyond the classroom!
(2011). The hypercorrection effect persists over a week, but high-confidence errors return.
Psychonomic Bulletin & Review. 18(6), 1238 - 1244.
Is there, or is there not, a gender gap in mathematics performance? And if there is, is it biological or cultural?
Although the presence of a gender gap in the U.S. tends to be regarded as an obvious truth, evidence is rather more equivocal. One meta-analysis of studies published between 1990 and 2007, for example, found no gender differences in mean performance and nearly equal variability within each gender. Another meta-analysis, using 30 years of SAT and ACT scores, found a very large 13:1 ratio of middle school boys to girls at the highest levels of performance in the early 1980s, which declined to around 4:1 by 1991, where it has remained. A large longitudinal study found that males were doing better in math, across all socioeconomic classes, by the 3rd grade, with the ratio of boys to girls in the top 5% rising to 3:1 by 5th grade.
Regardless of the extent of any gender differences in the U.S., the more fundamental question is whether such differences are biological or cultural. The historical changes mentioned above certainly point to a large cultural component. Happily, because so many more countries now participate in the Trends in International Mathematics and Science Study (TIMSS) and the Programme in International Student Assessment (PISA), much better data is now available to answer this question. In 2007, for example, 4th graders from 38 countries and 8th graders from 52 countries participated in TIMSS. In 2009, 65 countries participated in PISA.
So what does all this new data reveal about the gender gap? Overall, there was no significant gender gap in the 2003 and 2007 TIMSS, with the exception of the 2007 8th graders, where girls outperformed boys.
There were, of course, significant gender gaps on a country basis. Researchers looked at several theories for what might underlie these.
Contradicting one theory, gender gaps did not correlate reliably with gender equity. In fact, both boys and girls tended to do better in math when raised in countries where females have better equality. The primary contributor to this appears to be women’s income and rates of participation in the work force. This is in keeping with the idea that maternal education and employment opportunities have benefits for their children’s learning regardless of gender.
The researchers also looked at the more specific hypothesis put forward by Steven Levitt, that gender inequity doesn’t hurt girls' math performance in Muslim countries, where most students attend single-sex schools. This theory was not borne out by the evidence. There was no consistent link between school type and math performance across countries.
However, math performance in the 29 wealthier countries could be predicted to a very high degree by three factors: economic participation and opportunity; GDP per capita; membership of one of three clusters — Middle Eastern (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia); East Asian (Hong Kong, Japan, South Korea, Singapore, Taiwan); rest (Russia, Hungary, Czech Republic, England, Canada, US, Australia, Sweden, Norway, Scotland, Cyprus, Italy, Malta, Israel, Spain, Lithuania, Malaysia, Slovenia, Dubai). The Middle Eastern cluster scored lowest (note the exception of Dubai), and the East Asian the highest. While there are many cultural factors differentiating these clusters, it’s interesting to note that countries’ average performance tended to be higher when students attribute less importance to mastering math.
The investigators also looked at the male variability hypothesis — the idea that males are more variable in their performance, and their predominance at the top is balanced by their predominance at the bottom. The study found however that greater male variation in math achievement varies widely across countries, and is not found at all in some countries.
In sum, the cross-country variability in performance in regard to gender indicates that the most likely cause of any differences lies in country-specific social factors. These could include perception of abilities as fixed vs malleable, attitude toward math, gender beliefs.
A popular theory of women’s underachievement in math concerns stereotype threat (first proposed by Spencer, Steele, and Quinn in a 1999 paper). I have reported on this on several occasions. However, a recent review of this research claims that many of the studies were flawed in their methodology and statistical analysis.
Of the 141 studies that cited the original article and related to mathematics, only 23 met the criteria needed (in the reviewers’ opinion) to replicate the original study:
- Both genders tested
- Math test used
- Subjects recruited regardless of preexisting beliefs about gender stereotypes
- Subjects randomly assigned to experimental conditions
Of these 23, three involved younger participants (< 18 years) and were excluded. Of the remaining 20 studies, only 11 (55%) replicated the original effect (a significant interaction between gender and stereotype threat, and women performing significantly worse in the threat condition than in the threat condition compared to men).
Moreover, half the studies confounded the results by statistically adjusting preexisting math scores. That is, the researchers tried to adjust for any preexisting differences in math performance by using a previous math assessment measure such as SAT score to ‘tweak’ the baseline score. This practice has been the subject of some debate, and the reviewers come out firmly against it, arguing that “an important assumption of a covariate analysis is that the groups do not differ on the covariate. But that group difference is exactly what stereotype threat theory tries to explain!” Note, too, that the original study didn’t make such an adjustment.
So what happens if we exclude those studies that confounded the results? That leaves ten studies, of which only three found an effect (and one of these found the effect only in a subset of the math test). In other words, overwhelmingly, it was the studies that adjusted the scores that found an effect (8/10), while those that didn’t adjust them didn’t find the effect (7/10).
The power of the adjustment in producing the effect was confirmed in a meta-analysis.
Now these researchers aren’t saying that stereotype threat doesn’t exist, or that it doesn’t have an effect on women in this domain. Their point is that the size of the effect, and the evidence for the effect, has come to be regarded as greater and more robust than the research warrants.
At a practical level, this may have led to too much emphasis on tackling this problem at the expense of investigating other possible causes and designing other useful interventions.
Kane, J. M., & Mertz, J. E. (2012). Debunking Myths about Gender and Mathematics Performance. Notices of the AMS, 59(1), 10-21.
(2012). Can stereotype threat explain the gender gap in mathematics performance and achievement?.
Review of General Psychology;Review of General Psychology. No Pagination Specified - No Pagination Specified.
Data from parents and teachers of 2000 randomly selected children has revealed that only 29% of children with attention problems finished high school compared to 89% of children without such problems. When it came to hyperactivity, the difference was smaller: 40% versus 77%. After taking account of factors such as socioeconomic status and health issues that are correlated with ADHD, inattention was still a highly significant contributor, but hyperactivity was not.
Yearly assessments of the children were taken from age 6 to 12, and high school graduation status was obtained from official records. Attention problems were evaluated by teachers on the basis of behavior such as an inability to concentrate, absentmindedness, or a tendency to give up or be easily distracted. Hyperactivity was identified by behavior such as restlessness, running around, squirming and being fidgety.
The researchers make the excellent point that those with attention difficulties are often forgotten because, unlike hyperactive children, they don't disturb the class.
The findings point to the need to distinguish inattention and hyperactivity, and to provide early preventive intervention for attention problems.
(2011). Childhood Trajectories of Inattention and Hyperactivity and Prediction of Educational Attainment in Early Adulthood: A 16-Year Longitudinal Population-Based Study.
Am J Psychiatry. appi.ajp.2011.10121732 - appi.ajp.2011.10121732.
It must be easier to learn when your textbook is written clearly and simply, when your teacher speaks clearly, laying the information out with such organization and clarity that everything is obvious. But the situation is not as clear-cut as it seems. Of course, organization, clarity, simplicity, are all good attributes — but maybe information can be too clearly expressed. Maybe students learn more if the information isn’t handed to them on a platter.
A recent study looked at the effects of varying the font in which a text was written, in order to vary the difficulty with which the information could be read. In the first experiment, 28 adults (aged 18-40) read a text describing three species of aliens, each with seven characteristics, about which they would be tested. The control group saw the text in 16-point Arial, while two other versions were designed to be harder to read: 12-point Comic Sans MS at 60% grayscale and 12-point Bodoni MT at 60% grayscale. These harder-to-read texts were not noticeably more difficult; they would still be easily read. Participants were given only 90 seconds to memorize the information in the lists, and then were tested on their recall of the information after some 15 minutes doing other tasks.
Those with the harder-to-read texts performed significantly better on the test than those who had the standard text (an average of 86.5% correct vs 72.8%).
In the second experiment, involving 222 high school students from six different classes (English, Physics, History, and Chemistry, and including regular, Honors, and Advanced Placement classes), the text of their worksheets (and in the case of the physics classes, PowerPoint slides) was manipulated. While some sections of the class received the materials in their normal font, others experienced the text written in either Haettenschweiler, Monotype Corsiva, Comic Sans italicized, or smeared (by moving the paper during copying).
Once again, students who read the texts in one of the difficult conditions remembered the material significantly better than those in the control condition. As in the first study, there was no difference between the difficult fonts.
While it is possible that the use of these more unusual fonts made the text more distinctive, the fonts were not so unusual as to stand out, and moreover, their novelty should have diminished over the course of the semester. It seems more likely that these findings reflect the ‘desirable difficulty’ effect. However, it should be noted that getting the ‘right’ level of difficulty is a tricky thing — you need to be in the right place of what is surely a U-shaped curve. A little too much difficulty and you can easily do far more damage than good!
(2011). Fortune favors the (): Effects of disfluency on educational outcomes.
Cognition. 118(1), 111 - 115.
Whether IQ tests really measure intelligence has long been debated. A new study provides evidence that motivation is also a factor.
Meta-analysis of 46 studies where monetary incentives were used in IQ testing has revealed a large effect of reward on IQ score. The average effect was equivalent to nearly 10 IQ points, with the size of the effect depending on the size of the reward. Rewards greater than $10 produced increases roughly equivalent to 20 IQ points. The effects of incentives were greater for individuals with lower baseline IQ scores.
Follow-up on a previous study of 500 boys (average age 12.5) who were videotaped while undertaking IQ tests in the late 80s also supports the view that motivation plays a part in IQ. The tapes had been evaluated by those trained to detect signs of boredom and each boy had been given a motivational score in this basis. Some 12 years later, half the participants agreed to interviews about their educational and occupational achievements.
As found in other research, IQ score was found to predict various life outcomes, including academic performance in adolescence and criminal convictions, employment, and years of education in early adulthood. However, after taking into account motivational score, the predictiveness of IQ score was significantly reduced.
Differences in motivational score accounted for up to 84% of the difference in years of education (no big surprise there if you think about it), but only 25% of the differences relating to how well they had done in school during their teenage years.
In other words, test motivation can be a confounding factor that has inflated estimates of the predictive validity of IQ, but the fact that academic achievement was less affected by motivation demonstrates that high intelligence (leaving aside the whole thorny issue of what intelligence is) is still required to get a high IQ score.
This is not unexpected — from the beginning of intelligence testing, psychologists have been aware that test-takers vary in how seriously they take the test, and that this will impact on their scores. Nevertheless, the findings are a reminder of this often overlooked fact, and underline the importance of motivation and self-discipline, and the need for educators to take more account of these factors.
(2011). Role of test motivation in intelligence testing.
Proceedings of the National Academy of Sciences.
In a study involving 44 young adults given a rigorous memorizing task at noon and another such task at 6pm, those who took a 90-minute nap during the interval improved their ability to learn on the later task, while those who stayed awake found it harder to learn.
The degree to which the nappers were refreshed correlated with the amount of stage 2 non-REM sleep they experienced. This sleep phase is characterized by sleep spindles, which are associated with brain activity between the hippocampus and prefrontal cortex. Spindle-rich sleep occurs mostly in the second half of the night, so those who don’t get their quota of sleep are probably getting less.
The finding confirms the idea that learning ability decreases the more time you spend awake.
(2011). Wake deterioration and sleep restoration of human learning.
Current Biology. 21(5), R183-R184 - R183-R184.
A number of studies have provided evidence that eating breakfast has an immediate benefit for cognitive performance in children. Now a new study suggests some “good” breakfasts are better than others.
A Japanese study of 290 healthy, well-nourished children, has revealed that those whose breakfast staple was white rice had a significantly larger ratio of gray matter in their brains, and several significantly larger regions, including the left superior temporal gyrus and bilateral caudate. Those who habitually ate white bread had significantly larger regional gray and white matter volumes of several regions, including the orbitofrontal gyri, right precentral gyrus and postcentral gyrus. Overall IQ scores, and scores on the perceptual organization subcomponent in particular, were significantly higher for the rice group.
One possible reason for the difference may be the difference in the glycemic index (GI) of these two substances; foods with a low GI are associated with less blood-glucose fluctuation than are those with a high GI. There is also a difference in fat content, with those eating white bread typically consuming more fat than those eating a rice-based breakfast. High levels of fat have been shown to reduce the expression of BDNF.
Regardless of the reason for the difference, the fact that breakfast staple type affects brain size and cognitive function in healthy children points to the importance of good nutrition during the years of brain development.
(2010). Breakfast Staple Types Affect Brain Gray Matter Volume and Cognitive Function in Healthy Children.
PLoS ONE. 5(12), e15213 - e15213.
Five years ago I reported on a finding that primary school children exposed to loud aircraft noise showed impaired reading comprehension (see below). Now a small Norwegian study has found that playing white noise helped secondary school children with attention problems, but significantly impaired those who were normally attentive.
The adolescents were asked to remember as many items as possible from a list read out either in the presence or absence of white noise (78dB). The results were consistent with a computational model based on the concepts of stochastic resonance and dopamine related internal noise, postulating that a moderate amount of external noise would benefit individuals in hypodopaminergic states (such as those with ADHD). The results need to be verified with a larger group, but they do suggest a new approach to helping those with attention problems.
The previous study referred to involved 2844 children aged 9-10. The children were selected from primary schools located near three major airports — Schiphol in the Netherlands, Barajas in Spain, and Heathrow in the UK. Reading age in children exposed to high levels of aircraft noise was delayed by up to 2 months in the UK and by up to 1 month in the Netherlands for each 5 decibel change in noise exposure. On the other hand, road traffic noise did not have an effect on reading and indeed was unexpectedly found to improve recall memory. An earlier German study found children attending schools near the old Munich airport improved their reading scores and cognitive memory performance when the airport shut down, while children going to school near the new airport experienced a decrease in testing scores.
(2010). The effects of background white noise on memory performance in inattentive school children.
Behavioral and Brain Functions. 6(1), 55 - 55.
(2005). Aircraft and road traffic noise and children's cognition and health: a cross-national study.
Lancet. 365(9475), 1942 - 1949.
Two independent studies have found that students whose birthdays fell just before their school's age enrollment cutoff date—making them among the youngest in their class—had a substantially higher rate of ADHD diagnoses than students who were born later. One study, using data from the Early Childhood Longitudinal Study-Kindergarten cohort, found that ADHD diagnoses among children born just prior to their state’s kindergarten eligibility cutoff date are more than 60% more prevalent than among those born just afterward (who therefore waited an extra year to begin school). Moreover, such children are more than twice as likely to be taking Ritalin in grades 5 and 8. While the child’s school starting age strongly affects teachers’ perceptions of ADHD symptoms, it only weakly affects parental perceptions (who are more likely to compare their child with others of the same age, rather than others in the same class). The other study, using data from the 1997 to 2006 National Health Interview Survey, found that 9.7% of those born just before the cutoff date were diagnosed with ADHD compared to 7.6% of those born just after.
The two findings suggest that many of these children are mistakenly being diagnosed with ADHD simply because they are less emotionally or intellectually mature than their (older) classmates.
(2010). The importance of relative standards in ADHD diagnoses: Evidence based on exact birth dates.
Journal of Health Economics. 29(5), 641 - 656.
(2010). Measuring inappropriate medical diagnosis and treatment in survey data: The case of ADHD among school-age children.
Journal of Health Economics. 29(5), 657 - 673.
Analysis of 30 years of SAT and ACT tests administered to the top 5% of U.S. 7th graders has found that the ratio of 7th graders scoring 700 or above on the SAT-math has dropped from about 13 boys to 1 girl to about 4 boys to 1 girl. The ratio dropped dramatically between 1981 and 1995, and has remained relatively stable since then. The top scores on scientific reasoning, a relatively new section of the ACT that was not included in the original study, show a similar ratio of boys to girls.
(Submitted). Sex differences in the right tail of cognitive abilities: A 30 year examination.
Intelligence. 38(4), 412 - 423.
A study following nearly 1300 young children from birth through the first grade provides more evidence for the importance of self-regulation for academic achievement. The study found that children showing strong self-regulation in preschool and kindergarten did significantly better on math, reading and vocabulary at the end of first grade, independent of poverty, ethnic status, and maternal education (all of which had significant negative effects on reading, math, and vocabulary achievement in first grade). At-risk children with stronger self-regulation in kindergarten scored 15 points higher on a standardized math test in first grade, 11 points higher on an early reading test, and nearly seven points higher on a vocabulary test than at-risk children with weaker self-regulation. The findings emphasize the need to help children learn how to listen, pay attention, follow instructions, and persist on a task.
(Submitted). Relations between early family risk, children's behavioral regulation, and academic achievement.
Early Childhood Research Quarterly. In Press, Uncorrected Proof,
Older news items (pre-2010) brought over from the old website
Effect of schooling on achievement gaps within racial groups
Analysis of data from a national sample (U.S.) of 8,060 students, collected at four points in time, starting in kindergarten and ending in the spring of fifth grade, has found evidence that education has an impact in closing the achievement gap for substantial numbers of children. High-performing groups in reading were found among all races. About 30% of European Americans, 26% of African Americans and 45% of Asian Americans were in high-achieving groups by the spring of fifth grade — these groups included approximately 23% of African American children and 36% of Asian children who caught up with the initial group of high achievers over time. Only around 4% of European American students were in catch-up groups, because a higher percentage of European Americans started kindergarten as high achievers in reading. The situation was different for Hispanic students, however. By the end of fifth grade, just over 5% of Hispanic children were high achievers in reading, while the remainder tested in the middle range. There were no low achievers and no catch-up groups. A different pattern was found in math. Only 17% of European American students were high-achievers in math by the end of fifth grade, including 13% who started kindergarten at a lower achievement level and caught up over time. About 18% of Asian Americans were high-achievers at the end of fifth grade (11% catch-up). Only 0.3% of African Americans were high achievers at the end of fifth grade, and 26% were medium-high achievers. But about 16% of Hispanics were high achievers in math. There were no catch-up groups for either the African Americans or the Hispanics. This suggests that current schooling doesn't have as strong an impact on math achievement as it does in reading.
The study was presented in Washington, D.C. at the annual meeting of the Society for Research on Educational Effectiveness.
Children's under-achievement could be down to poor working memory
A survey of over three thousand children has found that 10% of school children across all age ranges suffer from poor working memory seriously affecting their learning. However, poor working memory is rarely identified by teachers, who often describe children with this problem as inattentive or as having lower levels of intelligence. The researchers have developed a new tool, a combination of a checklist and computer programme called the Working Memory Rating Scale, that enables teachers to identify and assess children's memory capacity in the classroom from as early as four years old. The tool has already been piloted successfully in 35 schools across the UK, and is now widely available. It has been translated into ten foreign languages.
Priming the brain for learning
A new study has revealed that how successfully you form memories depends on your frame of mind beforehand. If your brain is primed to receive information, you will have less trouble recalling it later. Moreover, researchers could predict how likely the participant was to remember a word by observing brain activity immediately prior to presentation of the word.
Otten, L.J., Quayle, A.H., Akram, S., Ditewig, T.A. & Rugg, M.D. 2006. Brain activity before an event predicts later recollection. Nature, published online ahead of print 26February2006