classroom learning

Classroom Learning

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Mathematics

Reading

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.

http://www.physorg.com/news123859991.html

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.

http://www.physorg.com/news123404466.html 
http://www.eurekalert.org/pub_releases/2008-02/du-cuc022608.php

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

http://www.nature.com/news/2006/060220/full/060220-19.html
http://www.eurekalert.org/pub_releases/2006-02/uoc--uri022806.php
http://www.eurekalert.org/pub_releases/2006-02/ucl-ywr022206.php

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Meditating leads to better grades

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).

05/2013
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More evidence of the value of gesture in teaching math

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.

04/2013
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Immediate reward improves low-performing students’ test scores

July, 2012

A large study involving Chicago public school students has found conditions in which rewards offered just before a test significantly improve test performance.

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.

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Support for link between physical activity & academic success

March, 2012

A review supports the benefits of physical activity for children’s and adolescent’s scholastic performance, but points to the need for better studies. A recent study looks at the effects on attention of different types of physical activity.

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!

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The problem in correcting false knowledge

February, 2012

Whether corrections to students’ misconceptions ‘stick’ depends on the strength of the memory of the correction.

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!

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Myths about gender and math performance

January, 2012

Two new reviews debunk several theories for the reasons for gender gaps in math performance.

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.

Stereotype threat

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.

Reference: 

Kane, J. M., & Mertz, J. E. (2012). Debunking Myths about Gender and Mathematics Performance. Notices of the AMS, 59(1), 10-21.

Stoet G, Geary DC. Can stereotype threat explain the gender gap in mathematics performance and achievement?. Review of General Psychology;Review of General Psychology. 2012 :No Pagination Specified - No Pagination Specified.

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Inattention, not hyperactivity, is associated with educational failure

October, 2011

A large, long-running study reveals that academic achievement for those with ADHD is hindered by attention problems not hyperactivity.

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.

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Using 'hard to read' fonts may help you remember more

June, 2011

Two experiments manipulating fonts to create texts that are slightly more difficult to read has found that such texts are better remembered.

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!

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Effect of motivation on IQ score

May, 2011

A new review pointing to the impact of motivation on IQ score reminds us that this factor is significant, particularly for predicting accomplishments other than academic achievement.

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.

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