A sedentary lifestyle is linked to poorer reading skills for boys

A new Finnish study adds to the long list of negative effects of a sedentary lifestyle. More specific the study conducted at the University of Eastern Finland in collaboration with the University of Jyväskylä and the University of Cambridge and recently published in the Journal of Science and Medicine and Sport shows that a sedentary lifestyle is linked to poorer reading skills in the first three school years in 6-8 year old boys.

From the press release:

“Low levels of moderate-to-vigorous physical activity and high levels of sedentary time in Grade 1 were related to better reading skills in Grades 1-3 among boys. We also observed that boys who had a combination of low levels of physical activity and high levels of sedentary time had the poorest reading skills through Grades 1-3,” explains Eero Haapala, PhD, from the University of Eastern Finland and the University of Jyväskylä.

The study, constituting part of the Physical Activity and Nutrition in Children Study conducted at the University of Eastern Finland and part of the First Steps Study conducted at the University of Jyväskylä, investigated the longitudinal associations of physical activity and sedentary time with reading and arithmetic skills in 153 children aged 6-8 years old in Grades 1-3 of the primary school. Physical activity and sedentary time were measured objectively using a combined heart rate and movement sensor in Grade 1, and reading and arithmetic skills were assessed by standardised tests in Grades 1-3.

The study showed that high levels of moderate-to-vigorous physical activity, low levels of sedentary time, and particularly their combination in Grade 1 were related to better reading skills in Grades 1-3 in boys. High levels of physical activity and low levels of sedentary time were also associated with better arithmetic skills in Grade 1 only in boys. In girls, there were no strong and consistent associations of physical activity and sedentary time with reading or arithmetic skills.

Promoting physically active lifestyle may kick-start boys’ school performance

The results of the study suggest that a combination of low levels of moderate-to-vigorous physical activity and high levels of sedentary time might be particularly harmful for the development of academic skills in boys, and that increasing physical activity, reducing sedentary time, and especially their combination may improve academic achievement.

Abstract of the study (open access):

Objectives
To investigate the independent and combined associations of objectively measured moderate-to-vigorous physical activity (MVPA) and sedentary time (ST) with reading and arithmetic skills.

Design
Cross-sectional/prospective.

Methods
Participants were 89 boys and 69 girls aged 6–8 years. MVPA and ST were measured using a combined heart rate and movement sensor and body fat percentage by dual-energy X-ray absorptiometry in Grade 1. Reading fluency, reading comprehension, and arithmetic skills were assessed using standardized tests in Grades 1–3. The data were analyzed using linear regression analyses and analyses of covariance with repeated measures.

Results
In boys, MVPA was directly and ST inversely associated with reading fluency in Grades 1–3 and arithmetic skills in Grade 1 (P < 0.05). Higher levels of MVPA were also related to better reading comprehension in Grade 1 (P < 0.05). Most of the associations of MVPA and ST with reading and arithmetic skills attenuated after mutual adjustment for MVPA or ST. Furthermore, boys with a combination of lower levels of MVPA and higher levels of ST had consistently poorer reading fluency (P = 0.002) and reading comprehension (P = 0.027) across Grades 1–3 than other boys. In girls, ST was directly associated with arithmetic skills in Grade 2 (P < 0.05). However, this relationship of ST with arithmetic skills was no longer significant after adjustment for body fat percentage.

Conclusions
Lower levels of MVPA and higher levels of ST and particularly their combination were related to poorer reading skills in boys. In girls, higher levels of ST were related to better arithmetic skills.

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Best evidence in brief: Breakfast clubs boost reading and mathematics results for elementary students

There is a new Best Evidence in Brief and this study made me hum ‘Don’t you forget about me’, the title song of the movie The Breakfast Club.

But this study is not about a Saturday morning detention…

Breakfast clubs that offer students in elementary schools a free and nutritious meal before school can boost their reading, writing and math results, according to the results of a randomized controlled trial published by the Education Endowment Foundation.

Over the course of an academic year parents of around 8,600 students from 106 elementary schools in England with higher than average numbers of disadvantaged students were encouraged to send their child to free breakfast clubs. The independent evaluation by researchers at the Institute for Fiscal Studies and the National Children’s Bureau found that for Year 2 (first grade) children the provision of a breakfast club led to a significant improvement in the main outcome measures of mathematics (Effect Size = +0.15) and reading (+0.10) when compared with schools running “business as usual”. For Year 6 (fifth grade) children, the impact on assessments were positive but slightly smaller in reading (+0.10) and mathematics (+0.08). Surprisingly, there were larger improvements for students not eligible for free school meals than for those eligible.

The evaluators also reported that students’ behavior and concentration improved. Attendance at school also improved for students in breakfast club schools, resulting in about 26 fewer half-days of absence per year for a class of 30. The findings suggest that it is not just eating breakfast that delivers improvements, but attending a breakfast club. This could be due to the content of the breakfast itself, or to other social or educational benefits of the club.

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TIMSS-results are in, Asia still reigns, Finland and Germany see lower average achievement

The new TIMSS-results are in. Check everything here.

But because everybody wants to know the rankings, I’ll share them first, the press release is next. More info about the different comparative tests? Check here.

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Ready to Peak? Becoming an Expert through Deliberate Practice: A book review

Interesting book review about Peak .

Mirjam Neelen

The first thing that Ericsson and Pool’s Peak: Secrets from the New Science of Expertise confirmed for me is that expertise is a word that’s used too often. Too many people call themselves experts while they’re actually not. Following Ericsson and Pool’s definition of expertise some fields don’t even have experts. Because it’s not just about being extraordinarily good at something or about being exceptionally amazing. It’s about having objective standards so that you can determine if someone is an expert in an objective manner. What triggered me is that, according to Peak’s authors an expert’s awesomeness lies in the heart of their capabilities and that it’s something that “every one of us is born with and can, with the right approach, take advantage of” (p xii). Wow. We all can be experts in something? Now that’s an appealing thought, isn’t it?

If you’re not an expert, it’s…

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Interesting: sleep deprivation affects children’s brains differently than adults’

It’s something we’ve known for quite a while now: children and teens need sleep (you too, btw, but a bit less than those under 18). But there is far less known about the details of how sleep deprivation affects children’s brains and what this means for early brain development.

Well, until now… now we now a bit more what actually happens in the brain.

From the press release:

“The process of sleep may be involved in brain ‘wiring’ in childhood and thus affect brain maturation,” explains Salome Kurth, first author of the study published in Frontiers in Human Neuroscience, and a researcher at the University Hospital of Zurich. “This research shows an increase in sleep need in posterior brain regions in children.”

This contrasts with what researchers know about the effects of sleep deprivation in adults, where the effect is typically concentrated in the frontal regions of the brain.

After staying up too late, both children and adults need a period of deep sleep to recover. This recovery phase is characterized by an increase in an electrical pattern called slow-wave activity, which can be measured with a non-invasive technique called an electroencephalogram. With a large number of electrode channels distributed across the scalp, this method also detects which brain regions show more slow-wave activity than others.

Supported by a large student team, Kurth and her colleagues, Monique LeBourgeois professor at the University of Colorado Boulder, and Sean Deoni , professor at Brown University, studied the effects of 50% sleep deprivation in a group of 13 children between the ages of 5 and 12 years. The team first measured the children’s deep sleep patterns during a normal night’s sleep. They then re-measured on another night after the researchers had kept the children up well past their bedtimes by reading and playing games with them.

After only getting half of a night’s worth of sleep, the children showed more slow-wave activity towards the back regions of the brain — the parieto-occipital areas. This suggests that the brain circuitry in these regions may be particularly susceptible to a lack of sleep.

The team also measured how this deep sleep activity correlated with the myelin content of the brain — a cornerstone of brain development. Myelin is a fatty microstructure of the brain’s white matter that allows electrical information between brain cells to travel faster. It can be measured with a specific magnetic resonance imaging technique.

“The results show that the sleep loss effect on the brain is specific to certain regions and that this correlates with the myelin content of the directly adjacent regions: the more myelin in a specific area, the more the effect appears similar to adults,” says Kurth. “It is possible that this effect is temporary and only occurs during a ‘sensitive period’ when the brain undergoes developmental changes.”

Further exploration is needed before drawing any conclusions about how insufficient sleep affects early brain developmental processes in the longer term. But for now, these results suggest that going to bed too late may have a different impact on kids’ brains than on adults’.

Abstract of the study:

Brain networks respond to sleep deprivation or restriction with increased sleep depth, which is quantified as slow-wave activity (SWA) in the sleep electroencephalogram (EEG). When adults are sleep deprived, this homeostatic response is most pronounced over prefrontal brain regions. However, it is unknown how children’s developing brain networks respond to acute sleep restriction, and whether this response is linked to myelination, an ongoing process in childhood that is critical for brain development and cortical integration. We implemented a bedtime delay protocol in 5- to 12-year-old children to obtain partial sleep restriction (1-night; 50% of their habitual sleep). High-density sleep EEG was assessed during habitual and restricted sleep and brain myelin content was obtained using mcDESPOT magnetic resonance imaging. The effect of sleep restriction was analyzed using statistical non-parametric mapping with supra-threshold cluster analysis. We observed a localized homeostatic SWA response following sleep restriction in a specific parieto-occipital region. The restricted/habitual SWA ratio was negatively associated with myelin water fraction in the optic radiation, a developing fiber bundle. This relationship occurred bilaterally over parieto-temporal areas and was adjacent to, but did not overlap with the parieto-occipital region showing the most pronounced homeostatic SWA response. These results provide evidence for increased sleep need in posterior neural networks in children. Sleep need in parieto-temporal areas is related to myelin content, yet it remains speculative whether age-related myelin growth drives the fading of the posterior homeostatic SWA response during the transition to adulthood. Whether chronic insufficient sleep in the sensitive period of early life alters the anatomical generators of deep sleep slow-waves is an important unanswered question.

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What are the differences between TIMSS and PISA?

This Tuesday the new TIMSS -results will be published, one week later the OECD will publish it’s new PISA-results. But what are the differences between those two comparisons? I found this handy overview in this Cambridge report (and they added PIRLS too):

pisa-timss-comparison-1
pisa-timss-comparison-2

If you want to compare countries, these links I collected are also a great place to start.

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Funny on Sunday: 10 funniest movie moments

It’s always very dangerous to make a top 10 list, but one thing I know: you’ll smile at least a couple of times:

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“Conclusions based on PISA results deserve further attention”

2 weeks from now all educationalists will know where to go to next for inspiration. But maybe we’ll need to take a closer look to the PISA results – to be published on December 6 – before booking our plane tickets.

Just some extra input to the discussions to come:

The tests results of the Programme for International Student Assessment (PISA), which often informs the development of academic policies in various countries, often receive rather simplified interpretations. As such, analysis of PISA data does not reflect the entire ‘package’ of school students’ knowledge in one key area – mathematics. This is the opinion of researchers from National Research University Higher School of Economics (Russia), Stanford University (USA), and Michigan State University (USA).

The Organization for Economic Co-operation and Development (OECD) is the leading authority currently monitoring PISA educational assessments (since 2000). This process can uncover changes and developments in various education systems throughout the world, while also evaluating the effectiveness of strategic decision-making with respect to education. However, this type of analysis does not include data on teachers and the ‘educational histories’ of children and youth. Thus, the results of the OECD’s monitoring may be inaccurately interpreted, thus hindering countries’ ability to properly develop and establish educational policies.

The PISA measures the knowledge of 15-year old students in mathematics and the natural sciences, as well as their ability to work with various types of text. However, according to researchers in Russia and the USA, this monitoring can only provide a ‘snapshot’ of the knowledge of such students and, thus, does not consider earlier assessments of their abilities and grades, as well as the conditions affecting one’s education (e.g., the cultural standards and progress of an entire class, the education level of a student’s parents, a teacher’s professional abilities and qualifications, etc.). At the same time, all of these factors may influence the movement (up or down) of the grades on the PISA. Furthermore, the researchers cited the results of math tests, which showed that such additional factors can significantly alter the conclusions drawn from the OECD’s monitoring data.

During math tests, students usually must solve three types of problem. The most important for PISA evaluations are assignments in applied mathematics (e.g., with real-life applications such as measuring a frame for a photograph). A large amount of attention is paid to ‘real life’ problems since PISA tests aim to determine the depth of students’ ability to apply their knowledge in order to solve essential problems. The second type of assignment is text-based problems with a large amount of additional information. In order to solve such problems, students must read through the text, determine what is most important, and then quickly adapt to the unfamiliar format of the given question. The third type are ‘formal’ mathematical problems (algebra and geometry), which require the application of complex formulas. PISA tests pay less attention to such problems, even though ‘formal’ mathematics are much more difficult than applied mathematics, often elevating mathematical thinking to an entirely new level. Furthermore, those students more often engaged in solving such problems usually have better PISA results that those whose teachers tend to focus on practical ‘real life’ examples.

In addition, the cultural sophistication of a student’s family is a key factor (e.g., standard of living, linguistic abilities, what is done in their leisure time, etc.). Students from better educated families with access to many books at home usually show the best test results. Also, such students have the conditions in place enabling them to excel academically. At the same time, classes with many students from educated families are more likely to acquire the skills necessary to solve formal algebraic and geometrical tasks, and thus are able to succeed in PISA testing.

Better qualified teachers can be found in classes where there is a higher average level of culture, and, as such, they tend to give their students more assignments dealing with formal mathematics. During their analysis, researchers also discovered that teachers with a mathematical non-pedagogical background tend to give better instruction, thus helping to boost the average grades of high school seniors.

Thus, best suited for PISA test are those learners who have successfully mastered formal mathematics. The researchers stress that cramming for questions on PISA tests are simply not enough. Thus, in order to ensure a more objective assessment of students’ knowledge and abilities in international monitoring, the factors influencing their success should be considered more fully. At the same time, in its recommendations, the OECD overestimates the role of schools in enhancing academic achievements, but underestimates other ‘areas of influence’ affecting evaluations of students’ knowledge.

The results of this analysis were published in the article ‘Revisiting the Relationship Between International Assessment Outcomes and Educational Production: Evidence From a Longitudinal PISA-TIMSS Sample’ http://aer.sagepub.com/content/53/4/1054.full.pdf+html in the American Educational Research Journal. The article’s authors include: Andrey Zakharov (Deputy Head of the HSE Institute of Education/International Laboratory for Education Policy Analysis), Martin Cornoy (Academic Supervisor, Leading Research Fellow at the HSE Institute of Education/International Laboratory for Education Policy Analysis, distinguished Professor of Stanford University), Tatiana Khavenson (Research Fellow at the HSE Institute of Education/International Laboratory for Education Policy Analysis), Prashant Loyalka (Professor at Stanford University) and William H. Schmidt (distinguished professor at Michigan State University).

Abstract of the article:

International assessments, such as the Program for International Student Assessment (PISA), are being used to recommend educational policies to improve student achievement. This study shows that the cross-sectional estimates behind such recommendations may be biased. We use a unique data set from one country that applied the PISA mathematics test in 2012 in ninth grade to all students who had taken the Trends in International Mathematics and Science Survey (TIMSS) test in 2011 and collected information on students’ teachers in ninth grade. These data allowed us to more precisely estimate the effects of classroom variables on students’ PISA performance. Our results suggest that the positive roles of teacher “quality” and “opportunity to learn” in improving student performance are much more modest than claimed in PISA documents.

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Revisiting Progressivism: Then and Now (Part 1)

This seems to be the start of a very interesting serie of posts. Looking forward to read them!

Larry Cuban on School Reform and Classroom Practice

Since January, I have visited classrooms, schools, and districts in Silicon Valley to see exemplars of technology integration. Posts appeared regularly over the past months describing individual elementary and secondary school teachers teaching lessons that put technology in the background, that is, laptops and tablets were as mundane as paper and pencil, in order to reach the content and skill goals they have set.

I intend to complete all of my observations and interviews by early December. Then I will re-read everything I wrote, reflect on what I have seen, read about “best cases” elsewhere in the U.S., and talk to people across the country whose work intersects with mine, place all of this in a historical context, and finally begin tapping away on my keyboard.

Oh, do I wish that the process in the above paragraph were so linear. But it ain’t. I have thoughts and intuitions now that…

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Sometimes you can sum up a conclusion of a study with a simple: we don’t know for sure

There is a new working paper by the OECD on teaching strategies. By combining the data of TALIS and PISA the researchers hope to be able to give practical advice to both teachers and policy makers.

Check the abstract:

This report explores the relationships between mathematics teachers’ teaching strategies and student learning outcomes in eight countries, using information from the TALIS-PISA link database. First, the study seeks to understand the shaping of teaching strategies by examining the way teachers use different classroom practices and the prevalence of these strategies among teachers across schools and countries. As a result of this exploration, three teaching strategies are put forward: active learning, cognitive activation and teacher-directed instruction. Second, the report aims at identifying the teaching strategies that are positively associated with student skill acquisition. Third and finally, it analyses the contributions of the school and the classroom settings, the teacher background and beliefs, to the implementation of the teaching strategies found to be positively related to student learning outcomes. Results show that cognitive activation strategies and, to a lesser extent, active learning strategies, have a strong association with students’ achievement in mathematics. However, this association seems to be weaker in schools with socio-economically disadvantaged students. Also, teachers from the same school tend to share the same approach to teaching, which indicates that these teaching strategies are part of a “teaching culture” within the school. Teacher self-efficacy and teacher collaboration are shown to be the factors more often associated with the implementation of cognitive activation strategies and active learning. Following on from these findings, the paper concludes with a series of policy recommendations.

Ok, fine, but when I checked the conclusions in the working paper I did made me think: wait a minute:

It’s a long excerpt, so bear with me (bold by me):

Which teaching strategies are associated with improved mathematics performances? The findings show that, overall, a frequent use of the cognitive activation strategy, which stimulates student critical thinking, problem-solving and decision making, is associated with higher mathematics performances (see Section 3). This association is particularly strong in Australia, Latvia, Portugal, and Romania. These types of practices encourage students to solve problems in more than one way, explain their thinking on complex problems and be innovative in their work.

On the other hand, in most countries in this study, no positive association was found between teacher- directed instruction and student achievement in mathematics. A possible explanation for this lack of association is that teacher-directed strategies are more often used with low-performing students (Echazarra et al., 2016). However, it is important to note that the implementation of teacher-directed strategies should not necessarily be interpreted as something negative. Presenting clear instructions, or providing a summary of previous lessons, are an important component of a successful learning climate. Indeed, a previous study conducted by the OECD has shown that teacher-directed practices are positively associated with the likelihood of answering easy items on the PISA 2012 mathematics test (Echazarra et al., 2016). Since this study shows that, when teacher-directed instruction becomes the most frequently used type of instruction it may have unfavourable consequences on student learning, the issue may be for the teacher to find the right balance: when, in what way and with whom is it appropriate to use this type of practice?

Finally, the association between the implementation of active learning practices and student mathematics achievement does not show a clear pattern across countries. In Australia and Portugal there is a strong negative association between active learning and student achievement, while Mexico, Romania and Spain show a clear positive association. The reason for these differences might be that, even if teachers report implementing an active learning strategy, the way they implement it may vary considerably across countries. More research is need at the classroom level to observe and explore the difference in the implementation of teaching strategies that a self-reporting survey such as TALIS is not able to provide.

Finland and Singapore did not show a significant association between any teaching strategy and student mathematics outcomes. At the same time, Romania and Mexico are the countries that more frequently engage in these teaching strategies and exhibit a positive association with student outcomes when applying active learning strategies (both Mexico and Romania) and cognitive activation strategies (Romania only).

This poses the question: why are Mexico and Romania not among of the top performing systems? One possibility is that, although teaching strategies are a crucial element for improving student outcomes, they are not the only variable that matters in this association. Student outcomes are a complex product of student, teacher and school factors. This analysis has isolated a single variable – teaching strategies – but there may be other factors not taken into account by the model use here that may overshadow the overall contribution of teaching strategies in the aforementioned countries.

Isn’t this a long way of telling us: we don’t really know?

The biggest insight seems to be:

Since this study shows that, when teacher-directed instruction becomes the most frequently used type of instruction it may have unfavourable consequences on student learning, the issue may be for the teacher to find the right balance: when, in what way and with whom is it appropriate to use this type of practice?

Correct, and this is something that both cognitive psychology and educational sciences have been showing over and over again.

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