Latest Research News
A study involving 845 secondary school students has revealed that each hour per day spent watching TV, using the internet or playing computer games at average age 14.5 years was associated with poorer GCSE grades at age 16. Additionally, each hour of daily homework and reading was linked to significantly better grades. Surprisingly, however, the amount of physical activity had no effect on academic performance.
Median screen time was four hours a day, of which around half was spent watching TV; median sedentary non-screen time (reading/homework) was 1.5 hours.
Each hour per day of time spent in front of the TV or computer in Year 10 was associated with 9.3 fewer GCSE points in Year 11 — the equivalent to two grades in one subject or one grade in each of two subjects. Two hours was therefore associated with 18 fewer points at GCSE, and the median of four hours, with a worrying 36 fewer points.
The burning question: are some screens better than others? Comparison of the different screen activities revealed that TV viewing was the most detrimental to grades.
More positively, each hour of daily homework and reading was associated with an average 23.1 more GCSE points. This was a U-shaped function, however, with pupils doing over four hours of reading or homework a day performing less well than their peers. But the number of pupils in this category was relatively low (only 52 pupils) and may include students who were struggling at school.
The benefits from spending time on homework or reading were not simply a consequence of spending less time staring at a screen; screen time and time spent reading or doing homework were independently associated with academic performance.
Do note that, although some homework was doubtless done on the computer, this was not counted as screen time for the purposes of this study.
The finding of no significant association between moderate to vigorous physical activity and academic performance is more surprising, given the evidence for the benefits of exercise and physical fitness for cognition. The median was 39 minutes of moderate to vigorous physical activity a day, with a quarter of the students getting less than 20 minutes a day, and a quarter getting more than 65 minutes.
The data used was from the ROOTS study, a large longitudinal study assessing health and wellbeing during adolescence. Objective levels of activity and time spent sitting were assessed through a combination of heart rate and movement sensing. Screen time, time spent doing homework, and reading for pleasure, relied on self-report. Medians were used rather than means, because of the degree of skew in the data.
 . Revising on the run or studying on the sofa: prospective associations between physical activity, sedentary behaviour, and exam results in British adolescents. International Journal of Behavioral Nutrition and Physical Activity [Internet]. 2015 ;12(1):1 - 8. Available from: http://link.springer.com/article/10.1186/s12966-015-0269-2
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!
 . Intergenerational Effects of Parents’ Math Anxiety on Children’s Math Achievement and Anxiety. Psychological Science [Internet]. 2015 :0956797615592630. Available from: http://pss.sagepub.com/content/early/2015/08/06/0956797615592630
A small study that compared teaching Spanish-speaking children English vocabulary using a song or a spoken poem has found definite and long-term advantages to the song form.
The study involved 38 Spanish-speaking Ecuadorian children (aged 9-13), of whom 22 were randomly assigned to learn a 29-word English text as an oral poem, and 16 learned it as a song. None of the children had had any formal instruction in English; all had some limited music training. The children were given 4 training sessions and 3 testing sessions over two weeks, with a final test for 13 children six months later.
Children in the song condition out-performed those in the spoken condition on every measure: their ability to recall the passage verbatim, pronounce the words, and translate target terms from English to Spanish.
While pronunciation of vowels was notably better, though there was no difference in consonants.
Long-term recall is of course the main question of interest: six months after this little experiment, with no English instruction since, those from the song condition could recall without prompting an average of 8.83 words out of 10 target words, compared with 0.29 words for those from the spoken condition. However, there was no significant difference in translation success, which was extremely low in both cases (2.26 vs 1.07 — this compares with 4.03 vs 2.69 at the end of training).
The song itself, its melody and rhythmic structure, was remembered very well. The children in the song condition also enjoyed the learning sessions much more.
The study is small, and comes with several caveats, but it does provide support for the use of songs as an adjunct to foreign language learning.
 . The efficacy of singing in foreign-language learning. Psychology of Music [Internet]. 2015 ;43(5):627 - 640. Available from: http://pom.sagepub.com/content/43/5/627
We say so blithely that children learn by copying, but a recent study comparing autistic children and normally-developing ones shows there’s more to this than is obvious.
The study, involving 31 children with ASD, 30 typically developing children matched for language skills, and 30 typically developing age-matched children, had the children watch an adult model how to perform a simple action. The demonstration included two vital actions and one superfluous action. The child was then asked to undertake the same task (without mentioning any need to copy all of the actions of the adult exactly as they had seen them).
Almost all children (97%) successfully managed the task, but while typical children copied 43-57% of the unnecessary actions, autistic children copied only 22%. This despite the fact that, when shown the demonstration again and asked to judge whether each action was “sensible” or “silly,” the children (and especially typical children) had no trouble recognizing the unnecessary actions as silly.
In other words, it’s not about reasoning ability, it’s about social motivation. Typical children want to please adults and ‘fit in’, so they copy even the silly actions. Autistic children care less about this.
The findings point to the social nature of copying behavior — it’s not simply about learning.
 . Children with autism do not overimitate. Current Biology [Internet]. 2013 ;23(7):R266 - R268. Available from: http://www.cell.com/current-biology/abstract/S0960-9822(13)00207-8
Benefits of high quality child care persist 30 years later
Back in the 1970s, some 111 infants from low-income families, of whom 98% were African-American, took part in an early childhood education program called the Abecedarian Project. From infancy until they entered kindergarten, the children attended a full-time child care facility that operated year-round. The program provided educational activities designed to support their language, cognitive, social and emotional development.
The latest data from that project, following up the participants at age 30, has found that these people had significantly more years of education than peers who were part of a control group (13.5 years vs 12.3), and were four times more likely to have earned college degrees (23% vs 6%).
They were also significantly more likely to have been consistently employed (75% had worked full time for at least 16 of the previous 24 months, compared to 53% of the control group) and less likely to have used public assistance (only 4% received benefits for at least 10% of the previous seven years, compared to 20% of the control group). However, income-to-needs ratios (income taken into account household size) didn’t vary significantly between the groups (mainly because of the wide variability; on the face of it, the means are very different, but the standard deviation is huge), and neither did criminal involvement (27% vs 28%).
See their website for more about this project.
Evidence that more time at school raises IQ
It would be interesting to see what the IQs of those groups are, particularly given that maternal IQ was around 85 for both treatment and control groups. A recent report analyzed the results of a natural experiment that occurred in Norway when compulsory schooling was increased from seven to nine years in the 1960s, meaning that students couldn’t leave until 16 rather than 14. Because all men eligible for the draft were given an IQ test at age 19, statisticians were able to look back and see what effect the increased schooling had on IQ.
They found that it had a substantial effect, with each additional year raising the average IQ by 3.7 points.
While we can’t be sure how far these results extend to other circumstances, they are clear evidence that it is possible to improve IQ through education.
Why children of higher-income parents start school with an advantage
Of course the driving idea behind improved child-care in the early years is all about the importance of getting off to a good start, and you’d expect that providing such care to children would have a greater long-term effect on IQ than simply extending time at school. Most such interventions have looked at the most deprived strata of society. An overlooked area is that of low to middle income families, who are far from having the risk factors of less fortunate families.
A British study involving 15,000 five-year-olds has found that, at the start of school, children from low to middle income families are five months behind children from higher income families in terms of vocabulary skills and have more behavior problems (they were also 8 months ahead of their lowest income peers in vocabulary).
Low-middle income (LMI) households are defined by the Resolution Foundation (who funded this research) as members of the working-age population in income deciles 2-5 who receive less than one-fifth of their gross household income from means-tested benefits (see their website for more detail on this).
Now the difference in home environment between LMI and higher income households is often not that great — particularly when you consider that it is often a difference rooted in timing. LMI households are more common in this group of families with children under five, because the parents are usually at an early stage of life. So what brings about this measurable difference in language and behavior development?
This is a tricky thing to derive from the data, and the findings must be taken with a grain of salt. And as always, interpretation is even trickier. But with this caveat, let’s see what we have. Let’s look at demographics first.
The first thing is the importance of parental education. Income plus education accounted for some 70-80% of the differences in development, with education more important for language development and income more important for behavior development. Maternal age then accounted for a further 10%. Parents in the higher-income group tended to be older and have better education (e.g., 18% of LMI mothers were under 25 at the child’s birth, compared to 6% of higher-income mothers; 30% of LMI parents had a degree compared to 67% of higher-income parents).
Interestingly, family size was equally important for language development (10%), but much less important for behavior development (in fact this was a little better in larger families). Differences in ethnicity, language, or immigration status accounted for only a small fraction of the vocabulary gap, and none of the behavior gap.
Now for the more interesting but much trickier analysis of environmental variables. The most important factor was home learning environment, accounting for around 20% of the difference. Here the researchers point to higher-income parents providing more stimulation. For example, higher-income parents were more likely to read to their 3-year-olds every day (75% vs 62%; 48% for the lowest-income group), to take them to the library at least once a month (42% vs 35% vs 26%), to take their 5-year-old to a play or concert (86% vs 75% vs 60%), to a museum/gallery (67% vs 48% vs 36%), to a sporting activity at least once a week (76% vs 57% vs 35%). Higher-income parents were also much less likely to allow their 3-year-olds to watch more than 3 hours of TV a day (7% vs 17% vs 25%). (I know the thrust of this research is the comparison between LMI and higher income, but I’ve thrown in the lowest-income figures to help provide context.)
Interestingly, the most important factor for vocabulary learning was being taken to a museum/gallery at age 5 (but remember, these correlations could go either way: it might well be that parents are more likely to take an articulate 5-year-old to such a place), with the second most important factor being reading to 3-year-old every day. These two factors accounted for most of the effects of home environment. For behavior, the most important factor was regular sport, followed by being to a play/concert, and being taken to a museum/gallery. Watching more than 3 hours of TV at age 3 did have a significant effect on both vocabulary and behavior development (a negative effect on vocabulary and a positive effect on behavior), while the same amount of TV at age 5 did not.
Differences in parenting style explained 10% of the vocabulary gap and 14% of the behavior gap, although such differences were generally small. The biggest contributors to the vocabulary gap were mother-child interaction score at age 3 and regular bedtimes at age 3. The biggest contributors to the behavior gap were regular bedtimes at age 5, regular mealtimes at age 3, child smacked at least once a month at age 5 (this factor also had a small but significant negative effect on vocabulary), and child put in timeout at least once a month at age 5.
Maternal well-being accounted for over a quarter of the behavior gap, but only a small proportion of the vocabulary gap (2% — almost all of this relates to social support score at 9 months). Half of the maternal well-being component of the behavior gap was down to psychological distress at age 5 (very much larger than the effect of psychological distress at age 3). Similarly, child and maternal health were important for behavior (18% in total), but not for vocabulary.
Material possessions, on the other hand, accounted for some 9% of the vocabulary gap, but none of the behavior gap. The most important factors here were no internet at home at age 5 (22% of LMIs vs 8% of higher-incomes), and no access to a car at age 3 (5% of LMIs had no car vs 1% of higher incomes).
As I’ve intimated, it’s hard to believe we can disentangle individual variables in the environment in an observational study, but the researchers believe the number of variables in the mix (158) and the different time points (many variables are assessed at two or more points) provided a good base for analysis.
 . Adult outcomes as a function of an early childhood educational program: An Abecedarian Project follow-up. Developmental Psychology;Developmental Psychology. 2012 :No Pagination Specified - No Pagination Specified.
Washbrook, E., & Waldfogel, J. (2011). On your marks : Measuring the school readiness of children in low-to-middle income families. Resolution Foundation, December 2011.
Following a monkey study that found training in spatial memory could raise females to the level of males, and human studies suggesting the video games might help reduce gender differences in spatial processing (see below for these), a new study shows that training in spatial skills can eliminate the gender difference in young children. Spatial ability, along with verbal skills, is one of the two most-cited cognitive differences between the sexes, for the reason that these two appear to be the most robust.
This latest study involved 116 first graders, half of whom were put in a training program that focused on expanding working memory, perceiving spatial information as a whole rather than concentrating on details, and thinking about spatial geometric pictures from different points of view. The other children took part in a substitute training program, as a control group. Initial gender differences in spatial ability disappeared for those who had been in the spatial training group after only eight weekly sessions.
A study of 90 adult rhesus monkeys found young-adult males had better spatial memory than females, but peaked early. By old age, male and female monkeys had about the same performance. This finding is consistent with reports suggesting that men show greater age-related cognitive decline relative to women. A second study of 22 rhesus monkeys showed that in young adulthood, simple spatial-memory training did not help males but dramatically helped females, raising their performance to the level of young-adult males and wiping out the gender gap.
Another study showing that expert video gamers have improved mental rotation skills, visual and spatial memory, and multitasking skills has led researchers to conclude that training with video games may serve to reduce gender differences in visual and spatial processing, and some of the cognitive declines that come with aging.
 . Gender Differences in Spatial Ability of Young Children: The Effects of Training and Processing Strategies. Child Development [Internet]. 2010 ;81(5):1417 - 1430. Available from: http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8624.2010.01482.x/abstract
 . Sex, Age, and Training Modulate Spatial Memory in the Rhesus Monkey (Macaca mulatta). Behavioral Neuroscience [Internet]. 2005 ;119(1):118 - 126. Available from: http://psycnet.apa.org/journals/bne/119/1/118/
 . Increasing Speed of Processing With Action Video Games. Current Directions in Psychological Science [Internet]. 2009 ;18(6):321 - 326. Available from: http://dx.doi.org/10.1111/j.1467-8721.2009.01660.x
Current study: www.physorg.com/news203744243.html Monkey study: http://www.eurekalert.org/pub_releases/2005-02/apa-ima022205.php http://www.eurekalert.org/pub_releases/2005-02/euhs-npm020905.php http://www.sciam.com/article.cfm?articleID=000560D5-7252-12B9-9A2C83414B... Video game study: http://www.eurekalert.org/pub_releases/2009-12/afps-rsa121709.php
A study involving 120 toddlers, tested at 14, 24, and 36 months, has assessed language skills (spoken vocabulary and talkativeness) and the development of self-regulation. Self-regulation is an important skill that predicts later academic and social success. Previous research has found that language skills (and vocabulary in particular) help children regulate their emotions and behavior. Boys have also been shown to lag behind girls in both language and self-regulation.
The present study hoped to explain inconsistencies in previous research findings by accounting for general cognitive development and possible gender differences. It found that vocabulary was more important than talkativeness, and 24-month vocabulary predicted the development of self-regulation even when general cognitive development was accounted for. However, girls seemed ‘naturally’ better able to control themselves and focus, but the ability in boys was much more associated with language skills. Boys with a strong vocabulary showed a dramatic increase in self-regulation, becoming comparable to girls with a strong vocabulary.
These gender differences suggest that language skills may be more important for boys, and that more emphasis should be placed on encouraging young boys to use words to solve problems, rather than accepting that ‘boys will be boys’.
 . Use your words: The role of language in the development of toddlers' self-regulation. Early Childhood Research Quarterly [Internet]. Submitted ;In Press, Uncorrected Proof. Available from: http://www.sciencedirect.com/science/article/B6W4B-512D8N2-1/2/a3c049839dabca86ac79a60b208b52d8
Brain imaging of 49 children aged 9-10 has found that those who were physically fit had a hippocampus significantly bigger (around 12%) than those who were not fit. Animal studies and those with older adults have shown that aerobic exercise increases the growth of new brain cells in the hippocampus. Physical fitness was measured by how efficiently the children used oxygen while running on a treadmill. Fitter children also did better on tests of relational (but not item) memory, and this association was directly mediated by hippocampal volume.
 A neuroimaging investigation of the association between aerobic fitness, hippocampal volume, and memory performance in preadolescent children. Brain Research [Internet]. 2010 ;1358:172 - 183. Available from: http://www.sciencedirect.com/science/article/B6SYR-50V5NMC-4/2/54b1e162e3c23c598ef08a5f00645cc3
A study involving 117 six year old children and 104 eight year old children has found that the ability to preserve information in working memory begins at a much younger age than had previously been thought. Moreover the study revealed that, while any distraction between learning the words and having to recall them hindered recall, having to perform a verbal task was particularly damaging. This suggests that their remembering was based on “phonological rehearsal”, that is, verbally repeating the names of the items to themselves. Consistent with the research suggesting children begin to phonologically rehearse at around 7 years of age, the verbal task hindered the 8 year olds more than the 6 year olds.
 . The development of memory maintenance: Children's use of phonological rehearsal and attentional refreshment in working memory tasks. Journal of Experimental Child Psychology [Internet]. 2010 ;107(3):306 - 324. Available from: http://www.sciencedirect.com/science/article/B6WJ9-50CDHD8-2/2/6ba1eea33d63196f7da3ca0445fe8e6e
‘Working memory’ is thought to consist of three components: one concerned with auditory-verbal processing, one with visual-spatial processing, and a central executive that controls both. It has been hypothesized that the relationships between the components changes as children develop. Very young children are more reliant on visuospatial processing, but later the auditory-verbal module becomes more dominant. It has also been found that the two sensory modules are not strongly associated in younger (5-8) American children, but are strongly associated in older children (9-12). The same study found that this pattern was also found in Laotian children, but not in children from the Congo, none of whom showed a strong association between visual and auditory working memory. Now a new study has found that Ugandan children showed greater dominance of the auditory-verbal module, particularly among the older children (8 ½ +); however, the visuospatial module was dominant among Senegalese children, both younger and older. It is hypothesized that the cultural differences are a product of literacy training — school enrolment was much less consistent among the Senegalese. But there may also be a link to nutritional status.
 . The Relationship between Visual-Spatial and Auditory-Verbal Working Memory Span in Senegalese and Ugandan Children. PLoS ONE [Internet]. 2010 ;5(1):e8914 - e8914. Available from: http://dx.doi.org/10.1371/journal.pone.0008914
You may think that telling students to strive for excellence is always a good strategy, but it turns out that it is not quite as simple as that. A series of four experiments looking at how students' attitudes toward achievement influenced their performance on various tasks has found that while those with high achievement motivation did better on a task when they also were exposed to subconscious "priming" that related to winning, mastery or excellence, those with low achievement motivation did worse. Similarly, when given a choice, those with high achievement motivation were more likely to resume an interrupted task which they were told tested their verbal reasoning ability. However, those with high achievement motivation did worse on a word-search puzzle when they were told the exercise was fun. The findings point to the fact that people have different goals (e.g., achievement vs enjoyment), and that effective motivation requires this to be taken account of.
 . The effects of chronic achievement motivation and achievement primes on the activation of achievement and fun goals. Journal of Personality and Social Psychology [Internet]. 2009 ;97(6):1129 - 1141. Available from: http://psycnet.apa.org/journals/psp/97/6/1129/
Data from North Carolina's mandated End-of-Grade tests (2000-2005), which includes student reports on how frequently they use a home computer for schoolwork, watch TV or read for pleasure, reveals that students in grades five through eight (c.10-13), particularly those from disadvantaged families, tended to have lower reading and math scores after they got a home computer. The researchers suggest that the greater negative effect in disadvantaged households may reflect less parental monitoring.
 . Scaling the Digital Divide: Home Computer Technology and Student Achievement. National Bureau of Economic Research Working Paper Series [Internet]. 2010 ;No. 16078. Available from: http://www.nber.org/papers/w16078
A study involving 163 overweight children and adolescents aged 10 to 17 has revealed that moderate to severe obstructive sleep apnea was linked to both lower academic grades and behavioral concerns. None of the students with moderate to severe OSA had an "A" average, and 30% had a "C" average or lower. In contrast, roughly 15% of those without sleep-disordered breathing had an "A" average, and only about 15% had a "C" average or lower. The results remained significant after adjustment for sex, race, socioeconomic status and sleep duration on school nights. OSA was particularly associated with inattention and poor study skills in real-world situations Forty-two students had moderate to severe OSA; 58 had mild OSA; 26 students were snorers; 37 had no sleep-disordered breathing.
Beebe, D.W. et al. 2010. The association between sleep-disordered breathing, academic grades, and neurobehavioral functioning among overweight subjects during middle to late childhood. Presented at SLEEP 2010, the 24th annual meeting of the Associated Professional Sleep Societies LLC, in San Antonio, Texas.
A national study involving some 8,000 children, has revealed receptive and expressive language, phonological awareness, literacy and early math abilities were all better in 4-year-old children whose parents reported having rules about what time their child goes to bed. Having an earlier bedtime also was predictive of higher scores for most developmental measures. Recommendations are that preschool children get a minimum of 11 hours of sleep each night. These findings (which confirm earlier studies) indicate not only that lower scores on phonological awareness, literacy and early math skills are associated with getting less than this recommended amount of sleep, but that many children are not getting the recommended amount of sleep.
Gaylor, E., Wei, X. & Burnham, M.M. 2010. Associations between nighttime sleep duration and developmental outcomes in a nationally representative sample of preschool-age children. Presented at SLEEP 2010, the 24th annual meeting of the Associated Professional Sleep Societies LLC, in San Antonio, Texas.
A study involving 629 12th-grade students from three Los Angeles-area high schools has revealed that, across both genders and all ethnicities, adolescents with more in-school friends, compared with out-of-school friends, had higher grade point averages. It’s assumed that this is due to the fact that in-school friends are more likely to support school-related activities, including studying.
 . In-School Versus Out-of-School Friendships and Academic Achievement Among an Ethnically Diverse Sample of Adolescents. Journal of Research on Adolescence [Internet]. 2010 ;9999(9999). Available from: http://dx.doi.org/10.1111/j.1532-7795.2010.00653.x
A national Swedish study involving the 1.16 million children in a national birth cohort identified nearly 8000 on the country's Prescribed Drug Register as using a prescription for ADHD medication (and thus assumed to suffer from severe ADHD). These children were significantly more likely to come from a family on welfare benefits (135% more likely), to have a mother with only the most basic education (130% more likely than those with mothers with university degrees), and to come from a single parent family (54% more likely). Boys were three times more likely to be on ADHD medication than girls, with medication use highest in boys aged between 10 and 15. The finding that family adversity is such a strong risk factor points to the need for more research into the role of environment
 . Social adversity predicts ADHD-medication in school children – a national cohort study. Acta Pædiatrica [Internet]. 2010 ;99(6):920 - 924. Available from: http://dx.doi.org/10.1111/j.1651-2227.2009.01638.x
Data from the same long-running study (the NICHD Study of Early Child Care and Youth Development), this time involving 1,364 youth (followed since birth), found that teens who had spent the most hours in non-relative child care in their first 4½ years reported a slightly greater tendency toward impulsiveness and risk-taking at 15 than did peers who spent less time in child care (21% were in care for more than 30 hours a week; 24% had had more than one year of care by 4 ½). But it was the quality of child care that made the difference as far as cognitive and academic performance was concerned. Those who had higher quality child care had better results on cognitive and academic assessments at both age 4½ and age 15. High-quality care was characterized by the caregivers' warmth, support, and cognitive stimulation of the children under their care. More than 40% of the children experienced high-quality (17%) or moderately high-quality (24%) care. The findings were consistent across gender and socioeconomic status. Previous research has tended to focus on the effects of child care on disadvantaged children; this one is notable for involving children across society. The study is important not only for pointing to the effects of childcare quality, but for the finding that the effect continues into adolescence.
 . Do Effects of Early Child Care Extend to Age 15 Years? Results From the NICHD Study of Early Child Care and Youth Development. Child Development [Internet]. 2010 ;81(3):737 - 756. Available from: http://dx.doi.org/10.1111/j.1467-8624.2010.01431.x
Older news items (pre-2010) brought over from the old website
Aschermann, E., Dannenberg, U. & Schulz, A. 1998. Photographs as retrieval cues for children. Applied Cognitive Psychology, 12, 55-66.
Finding: Photographs, frequently used as cues to remembering in adults, also appear to be effective with children as young as three.
This study looked at the value of photographs as retrieval cues for young children. Fifty-seven children (3,6-7, and 8 years old) participated in a fishing game. Ten days later the children were questioned about the game. Those children who were shown relevant photos recalled more details than those who were simply verbally reminded of the game. Appropriate props also improved accuracy of recall.
Bjorklund, D.F., Miller, P.H., Coyle, T.R. & Slawinski, J.L. 1997. Instructing Children to Use Memory Strategies: Evidence of Utilization Deficiencies in Memory Training Studies. Developmental Review, 17, 411-441.
Finding: When teaching young children learning strategies, care should be taken to keep it simple. Simply providing instructions is preferable than providing both instructions and a rationale.
The term "utilization deficiencies" refers to the use of an effective strategy without any improvement in performance. Thus, if a child dutifully rehearsed items without being able to remember them any better than items she had not rehearsed, this would be a deficiency in utilization.
Utilization deficiencies appear to be common among children. They are more common, unsurprisingly, with younger children, and more common when strategy training has included multiple procedures rather than a single procedure.
Manion, V. & Alexander, J.M. 1997. The Benefits of Peer Collaboration on Strategy Use, Metacognitive Causal Attribution, and Recall. Journal of Experimental Child Psychology, 67, 268-289.
Finding: Working in groups with children who understand and use memory strategies can help children with poorer metacognitive skills increase their understanding and strategy use.
Metacognition - knowledge and understanding of your own cognitive processes - is increasingly being recognized as important in determining whether or not you can use cognitive strategies effectively. This study looked at the benefits of children with different levels of metacognitive understanding working together.
Children were tested as to their knowledge about the effectiveness of a sorting strategy, and then placed in small groups. These groups were given instructions to explicitly discuss their strategies. It was found that children with a lower metacognitive understanding improved their understanding and strategy use as a result of being placed with children with a higher level of understanding.
Harnishfeger, K.K. & Pope, R.S. 1996. Intending to Forget: The Development of Cognitive Inhibition in Directed Forgetting. Journal of Experimental Child Psychology, 62, 292-315.
Finding: Intentional forgetting is a learned skill, which children acquire gradually, and which is not fully acquired by age 10.
Although we tend to decry forgetting, and regard it as a failure of memory, forgetting is an important ability. Not everything is worth remembering. Certainly we don't want to remember everything all at once!
Part of efficient remembering involves ignoring information that is irrelevant. It is thought that "directed ignoring" plays an important role in controlling what goes into working memory. Interestingly, it has been suggested that one of the reasons for memory problems in old age is a diminished ability to ignore irrelevant information.
This research looks at directed ignoring in children. First, third, and fifth graders and adults were given a "forget" or "remember" cue midway through the presentation of a list of words. At recall, the subjects were asked either to remember all the words (even the ones they had been instructed to forget) or to remember only to-be-remembered words.
It was found that the children were less able than the adults to forget the to-be-forgotten words. The results suggested that the ability to intentionally inhibit recall of irrelevant information improves gradually over the elementary school years, but is not fully mature by fifth grade. A further experiment checked that the different results were due to differences in memory rather than a failure to understand the instructions.
Oyen, A. & Bebko, J.M. 1996.The Effects of Computer Games and Lesson Contexts on Children's Mnemonic Strategies. Journal of Experimental Child Psychology, 62, 173-189.
Finding: Learning in the context of a computer game may be more difficult for young children than in the context of a more structured lesson. Interest is higher, but the complexity of the game (number of distracting details) may hinder learning.
This study looked at the effect of embedding a memory task in the context of a computer game. Four to seven year olds participated in one of two computer games and a more formal "lesson" condition. While the game context appeared to stimulate much more rehearsal, this was because the rehearsal was more overt. The amount of rehearsal when both overt and covert rehearsal were included, was similar for both the lesson and the game condition.
There was, as expected, an increase in rehearsal with age - at each age level the number of rehearsers nearly doubled. Rehearsers did, of course, recall more items than those children who did not rehearse.
Regardless of rehearsal, recall of items experienced in the game context was less than that for items experienced in a more formal "lesson". The games were more interesting for the children, but the multiplicity of goals and distractions in the games may have made the task more difficult.
Event memory in young children
Reese, E. & Brown N. 2000. Reminiscing and recounting in the preschool years. Applied Cognitive Psychology, 14, 1-17.
Finding: Parents can help their child remember events that have happened to them by reminiscing with them (recalling with them events that they have shared) and encouraging them to recall details about unshared events.
Talk about past events can be classified as either reminiscing (discussingshared experiences) or recounting (discussing unshared experiences).
This study looked at reminiscing and recounting between preschoolers and their mothers. Forty children between three and five participated in the experiment. It was found that children reported more unique memory information when they were discussing unshared experiences (recounting) rather than shared. Mothers who provided morememory information during reminiscing and asked for more information during recounting had children who reported more unique information about events.
Buckner, J.P. & Fivush, R. 1998. Gender and self in children's autobiographical narratives. Applied Cognitive Psychology, 12, 407-29.
Finding: Gender differences in conversational style seem to appear at an early age. At age 8, girls' recounting of personal experiences are already more detailed and socially contexted than boys' narratives are.
This study looked at the differences between girls and boys in recounting personal experiences. The children were aged eight, and from a middle-class background. As has tended to be found with adults, it was found that the girls' narratives were longer, more coherent and more detailed than were the boys' narratives. The girls' narratives also tended to mention more people and more emotions, and to be placed in a social context.
Maintenance rehearsal in children
Maintenance rehearsal refers to the simple repetition of items to hold them in working memory, where we are conscious of them. Thus, when we want to remember a phone number for long enough to ring it, or write it down, we repeat it to ourselves until we have completed our action.
Maintenance rehearsal no doubt seems a self-evident strategy to any adult, simple as it is and long accustomed as we are to using it. However, it is, like any strategy, something we have to learn to do. It is rare in five year olds, common in ten year olds (although still not universal).
Rehearsal is an effective strategy for short-term recall, and young children (at least as old as six) can be taught to use the strategy. However, continued use of the strategy (without explicit instruction) is more unlikely than not. It may be however, that training was insufficient to impress upon the children the usefulness of the strategy, and with better feedback they might be encouraged to use the strategy spontaneously.
Flavell JH, Beach DR & Chinsky JM 1966. Spontaneous verbal rehearsal in a memory task as a function of age. Child Development, 37, 283-99.
Finding: Spontaneous rehearsal found among 10% of 5 year olds; 60% of 7 year olds, 85% of 10 year olds.
Keeney TJ, Cannizo SR & Flavell JH 1967. Spontaneous and induced verbal rehearsal in a recall task. Child Development, 38, 953-66.
Finding: 6 & 7 year olds who rehearsed spontaneously (without instruction) were significantly better at recalling a list of items than that of non-rehearsers. Training of non-rehearsers resulted in improvement almost to the level of the spontaneous rehearsers; however on later trials (given the option to rehearse) 10 of 17 newly taught rehearsers abandoned the strategy.
Categorizing is another very basic strategy that many of us use to help us remember items. Thus, if you are given a list:
BANANA VAN PANSY TRUCK CARNATION PLUM PEACH MOTORCYCLE ROSE MARIGOLD MANGO CAR
the items will be much easier to remember if you note that the items belong to only three categories — fruit, vehicles, flowers. Noting that there are four examples of each will also help. The category labels help considerably when it comes to retrieving the information (and knowing how many items in each category tells us when we can stop searching that category and move on to another).
Most educated adults do this sort of thing automatically. But, again, like any strategy no matter how simple, it is not something we are born knowing.
Very young children are not likely to group items at all, but if they do, it will be most likely according to some sort of association (cornflakes — milk, baby — bottle, paper — pencil). If young children are taught to group items into taxonomic categories, they will still not use category labels effectively when retrieving the information, without explicit instruction.
From around 6 or 7, children seem to benefit more from instruction in categorization strategies. If the children are very young, such instruction may only confuse them. Using category labels as retrieval cues appears to be a more complex strategy than the first step of learning to group according to category, and doesn’t appear until later. Even children as old as 11 may benefit from explicit reminders to use category labels as retrieval cues and search the categories exhaustively before moving on.
At around 7, about 50% of children appreciate the value of categorization as a memory strategy. This doesn’t increase all that much over the next few years (about 60% of ten year olds), although nearly all 17 year olds understand the strategy.
Moely BE, Olson FA, Halwes T & Flavell J 1969. Production deficiency in young children’s clustered recall. Developmental Psychology, 1, 26-34.
Finding: Children were shown pictures of animals, furniture, vehicles and clothes, and told they could arrange the pictures in any way that would help them remember. 5th graders sorted them into these taxonomic categories. 3rd graders were able to arrange them that way once the experimenter labeled each category and pointed out members. Kindergarten and 1st graders needed a lot of help — to sort the items, label the categories, and count the number of pictures in each category.
Moely BE & Jeffrey WE 1974. The effects of organization training on children’s free recall of category items. Child Development, 45, 135-143.
Finding: most 6 and 7 year olds could sort successfully when given the suggestion that the items could be divided into “groups of things that are alike in some way or kind of go together”. Some children needed help to label the categories. When given the instruction, during recall, to think of a category label and name all the members in the category, then to repeat this with each category, recall was improved.
Zinobar JW Cermak LS Cermak SA & Dickerson DJ 1975. A developmental study of categorical organization in short-term memory. Developmental Psychology, 11, 398-9.
Finding: found 3rd and 4th graders spontaneously used taxonomic categories, but 2nd graders didn’t.
Bjorklund DF, Ornstein PA & Haig JR 1977. Developmental differences in organization and recall: Training in the use of organizational techniques. Developmental Psychology, 13, 175-83.
Finding: 3rd and 5th graders were much better at categorizing when given explicit instructions about what to look for.
Denney NW & Ziobrowski M 1972. Developmental changes in clustering criteria. Journal of Experimental Child Psychology, 13, 275-83.
Finding: if 1st graders grouped items at all (spontaneously), they do it according to associations, e.g. pipe-tobacco, baby-crib.
Black MM & Rollins HA 1982. The effects of instructional variables on young children’s organization and free recall. Journal of Experimental Child Psychology, 33, 1-19.
Finding: 1st graders taught to categorize pictures of common objects ( such as furniture, clothes, animals, food) using two different methods of instruction:
- questioning (using direct questioning to lead the child to consider ways to remember and to develop a verbal explanation of the strategy).
These methods were further differentiated according to how general or specific the instructions were. Thus:
- In the general explanation group, the experimenter explained why organization was helpful in recall while demonstrating with the picture cards (“If I put cards together that are similar, such as all the animals, it will be easier to remember”).
- In specific explanation, the instructions were directed towards specific items (“I will put the dog next to the cat”).
- In general question, the experimenter asked questions and encouraged the child to manipulate the cards. The question emphasized the purpose for an organizational strategy (“Why do we put the animals together?”). Correct answers were provided if the child couldn’t answer correctly.
- In specific question, the questions were directed to specific items.
In all cases, the training lasted 10 — 12.5 minutes. All types of training appeared to be effective in improving recall, and there was little difference between them. Explanation was slightly better than questioning, and general strategies were slightly better than the corresponding specific ones.
Kobasigawa A 1974. Utilization of retrieval cues by children in recall. Child Development, 45, 1067-72.
Finding: young children not only fail to categorize, even when they have been explicitly instructed to categorize they don’t use categories effectively during retrieval. Thus, when asked to remember the items, if they remember a category label, they tend to be satisfied as soon as they have retrieved one item from the category instead of searching the category exhaustively.
Scribner S & Cole M 1972. Effects of constrained recall training on children’s performance in a verbal memory task. Child Development, 43, 845-57.
Finding: when children were reminded at presentation and recall that there were four categories, and told to recall all items from a category before moving on, recall was better for all ages (7, 9 and 11 years).
Yussen SR, Kunen S & Buss R 1975. The distinction between perceiving and memorizing in the presence of category cues. Child Development, 46, 763-8.
Finding: interestingly, preschool children seemed to do better when they were not given such instructions, but simply asked to remember as much as they could.
Davies GM & Brown L 1978. Recall and organization in five year old children. British Journal of Psychology, 69, 343-9.
Davies G & Rushton A 1979. Presentation mode and organizational strategies in young children’s free recall. In MP Friedman, JP Das, & N O’Connor (eds) Intelligence and learning. NY: Plenum Pr.
Finding: some evidence that spontaneous categorization is less likely with pictures (the usual experimental stimulus); that young children are far more likely to categorize when faced with real objects.
Wimmer H & Tornquist K 1980. The role of metamemory and metamemory activation in the development of mnemonic performance. International Journal of Behavioral Development, 3, 71-81.
Finding: children questioned to find out to what extent they understood the value of categorizing in aiding remembering. They found 50% of 7 year olds, 60% of 10 year olds, and nearly all 17 year olds did.
Category labels don’t appear to particularly help recall in children before the age of ten.
Picture recognition is assisted by labeling in children as young as four.
Researchers have had mixed results in labeling pictures as an aid to learning paired associations in young children.
Labeling pictures does not appear to help very young children remember the order of items, but can be helpful to children from six years old until they are of an age to spontaneously label, when such explicit labeling may interfere with their own learning strategy. Such spontaneous labeling probably occurs around ten.
Labeling however is often part of a wider strategy, and may well be helpful to young children for other reasons than improving recall. For example, it may be useful in helping children acquire language.
Kobasigawa A & Middleton D. 1972. Free recall of categorized items by children at three grade levels. Child Development, 43, 1067-1072.
Moely BE 1977. Organizational factors in the development of memory. In R Kail & J Hagen (eds) Perspectives on the development of memory and cognition. Hillsdale: NJ: LEA.
Finding: categorization (labeling categories of items during presentation) improves recall in children in the 5th grade (10 year olds), but not younger.
Horowitz AB 1969. Effect of stimulus presentation modes on children’s recall and clustering. Psychonomic Science, 14, 297-8.
Finding: increased recall but no increased organization by 5 and 8 year olds who had to label auditory or visual items during presentation (vs children who simply looked at or listened to the items).
Williams KG & Goulet LR 1975. The effects of cuing and constraint instructions on children’s free recall performance. Journal of Experimental Child Psychology, 19, 464-475.
Finding: telling children category names before presenting the items (prelabeling) didn’t help recall in 4 year olds.
Nelson K 1969. The organization of free recall by young children. Journal of Experimental Child Psychology, 8, 284-295.
Finding: prelabeling didn’t help recall in 5 and 8 year olds.
Ward WC & Legant P 1971. Naming and memory in nursery school children in the absence of rehearsal. Developmental Psychology, 5, 174-5.
Finding: labeling pictures appeared to help picture recognition in 4 year olds
Nelson KE & Kosslyn SM 1976. Recognition of previously labeled or unlabeled pictures by 5-year-olds and adults. Journal of Experimental Child Psychology, 21, 40-45.
Finding: labeling pictures appeared to help picture recognition in 5 year olds and adults. Such labeling probably modifies attention to particular elements.
Rohwer WD, Lynch S, Levin JR & Suzuki N. 1967. Pictorial and verbal factors in the efficient learning of paired associates. Journal of Educational Psychology, 58, 278-84.
Finding: labeling pictures aided paired-associate learning in kindergarten children, 1st, 3rd & 6th graders.
Rohwer WD, Kee D & Guy K. 1975. Developmental changes in the effects of presentation media on noun-pair learning. Journal of Experimental Child Psychology, 19, 137-152.
Finding: labeling pictures didn’t help paired-associate learning in 2nd graders.
Means & Rohwer 1974 (unpublished study)
Finding: labeling pictures didn’t aid paired-associate learning in nursery school children,1st or 4th graders.
Hagen JW & Kingsley PR. 1968. Labelling effects in short-term memory. Child Development, 39, 113-121.
Finding: Overt labeling of animal pictures resulted in no improvement in recall of serial position in nursery children (around 5 years old); did improve serial recall in 6-8 year olds who didn’t spontaneously label; didn’t improve serial recall in 10 year olds who spontaneously labeled.
Ghatala ES & Levin JR. 1976. Children’s recognition memory processes. In JR Levin & VL Allen (eds) Cognitive learning in children: Theories and strategies. NY: Academic Pr
Finding: Overt labeling produced substantially better recall than covert labeling in elementary school children.