What works for bullying prevention?

Child Trends has released a new policy brief on preventing bullying and cyberbullying. The report provides information on the current state of bullying research using data from the US Department of Education, journal articles, and existing research by Child Trends, and provides recommendations for addressing and preventing bullying behaviour.

The report notes that while many bullying prevention programmes and strategies are available, evidence of their effectiveness has been mixed, and most have never been rigorously evaluated. Based on the existing research, the report provides the following recommendations:

  • Include cyberbullying as part of a broader approach to bullying prevention. Strategies targeting cyberbullying alone without addressing the broader issue of bullying are unlikely to be effective. Similarly, monitoring pupils’ social media accounts is likely to be an ineffective use of resources without additional efforts to encourage more civil behaviour online and in person.
  • Support the development of evidence-based approaches through dedicated funding for research. Such investments should also examine interventions, such as integrated pupil supports, for pupils who are targeted by bullying or witness it.
  • Discourage approaches that lack evidentiary support, criminalise young people, or remove them from school. Research shows that anti-bullying assemblies, speakers, and campaigns are not effective at preventing bullying, nor are zero-tolerance policies that remove students from school and do not address the underlying causes of bullying behaviour.

Source: Preventing bullying and cyberbullying: research-based policy recommendations for executive and legislative officials in 2017 (Jan 2017), Child Trends

Do computers have a negative effect on children’s social development?

A working paper from the National Bureau of Economic Research reports the findings from a large-scale randomised controlled trial that explores whether owning a home computer has a negative effect on children’s social development.

The study included 1,123 students in grades 6-10 (Years 7-11) in 15 different schools across California. Students were eligible to take part in the trial only if they did not already have a computer at home. Half were then randomly selected to receive free computers, while the other half served as the control group. Surveys were conducted with the students and schools at the start of the school year to collect data on child and household characteristics and school participation. Follow-up surveys were then administered at the end of the school year, and the data compared to establish any causal evidence.

As predicted, Robert W Fairlie and Ariel Kalil found that having computers at home did increase the amount of time that children spent on social networking sites and email as well as for games and other entertainment. However, rather than being socially isolating, children in the treatment group communicated with 1.57 more friends per week than children in the control group, and spent 0.72 more hours with their friends in person. They also found no evidence that the children who received a computer were less likely to participate in sports teams or after-school clubs, or spend any less time in these activities.

Source: The effects of computers on children’s social development and school participation: evidence from a randomized control experiment (December 2016), NBER Working Paper No. 22907, The National Bureau of Economic Research

How much sleep do teenagers need?

In a new study published in Child Development, Andrew J Fuligni and colleagues examined whether there is an “optimal” amount of sleep for peak levels of academic achievement and mental health in teenagers.

A total of 421 pupils (mean age = 15.03 years) with Mexican-American backgrounds from the 9th and 10th grades (Years 10 and 11) of two high schools in the Los Angeles area reported the amount of sleep they had every night for two weeks. Official school records were obtained at the end of the academic year to measure academic achievement. The Youth Self-Report form of the Child Behavior Checklist was used as a measure of mental health. A year later, 80% repeated the same process and a second wave of data was collected.

Pupils who averaged 8.75 – 9 hours of sleep per school night demonstrated peak levels of mental health, whereas those who averaged 7 – 7.5 hours of sleep per night had the highest levels of academic achievement (see also an earlier study reported in Best Evidence in Brief).

While the results showed that the “optimal” amount of sleep needed is different for the two developmental outcomes, the researchers note that reducing sleep for the sake of academic performance may result in a greater decline in mental health than in the decline in academic performance from increasing sleep for the sake of mental health.

Source: Adolescent sleep duration, variability, and peak levels of achievement and mental health (January 2017), Child Development DOI: 10.1111/cdev.12729

Examining the results of SIG funding

Former President Obama’s American Investment and Recovery Act of 2009 included $3 billion of funding for School Improvement Grants (SIG). SIG awards went to states’ lowest-performing schools who agreed to implement improvements using either the turnaround, transformation, restart, or closure models, and using four main improvement practices: adopting comprehensive school reform programmes; developing teacher and principal effectiveness; making more time for learning and creating community-orientated schools, and providing support and operational flexibility for schools.

Given the size and expense of the SIG programme, The Institute of Education Sciences at the Department of Education commissioned a report by Lisa Dragoset and colleagues at Mathematica Policy Research, and Cheryl Graczewski and colleagues at the American Institutes for Research, to investigate to what extent the SIG-funded schools used the recommended practices, how these schools compared to non-funded schools, the effect of SIG funding on student outcomes, and which of the intervention models was most effective.

Researchers found that the use of SIG funding had no effect on pupil outcomes in maths or reading test scores, high school graduation, or likelihood to attend college. No SIG model was associated with more gains than another at the elementary (primary school) level, although in grades 6-12 (Years 7-13), SIG-funded schools using the turnaround model were associated with higher pupil maths achievement than the transformational model. More recommended improvement practices were used in SIG-funded schools than in non-funded schools, although not significantly so, and were implemented most often in schools using the school reform model. These findings indicate that SIG funding did not significantly impact pupil achievement outcomes or increase the use of recommended practices, at least for schools near the SIG funding cut-off. They noted that results might be different for schools not near the SIG-funding cut-off.

Source: School Improvement Grants: implementation and effectiveness (January 2017), Institute of Education Sciences

A century of research on ability grouping and acceleration

Researchers Saiying Steenbergen-Hu and colleagues recently analysed the results of almost 100 years of research on the effects of ability grouping (which places pupils of similar skills and abilities in the same classes) and acceleration (where pupils are given material and assignments that are usually reserved for older year groups) on pupils’ academic achievement. After screening thousands of studies, their secondary meta-analysis, recently published in Review of Educational Research, synthesised the results of thirteen earlier meta-analyses on ability grouping and six on acceleration that met inclusion criteria for the final review.

They divided ability grouping into four types: (1) between-class ability grouping, where pupils in the same year are divided into low-, medium-, or high-level classes; (2) within-class ability grouping, where pupils within a classroom are taught in groups based on their levels; (3) cross-year subject grouping, where pupils in different year groups are combined into the same class depending on their prior achievement; and (4) grouping for pupils considered gifted.

Results showed academic benefits of within-class grouping, cross-year grouping by subject, and grouping for the gifted, but no benefit of between-class grouping. Results were consistent regardless of whether pupils were high-, medium-, or low-achievers. Analyses of acceleration groups for pupils labelled as gifted showed that these pupils performed the same as older non-gifted pupils, and that being in accelerated classes had positive effects on these pupils’ grades.

Source: What one hundred years of research says about the effects of ability grouping and acceleration on K–12 students’ academic achievement: Findings of two second-order meta-analyses (December 2016), Review of Educational Research, Vol. 86, No. 4

Improving reading comprehension for English learners

A randomised controlled trial, published in the Journal of Educational Psychology, has examined the impact of a version of the PACT reading comprehension and content acquisition intervention, which was modified to meet the needs of pupils with English as an Additional Language (EALs), in eighth-grade (Year 9) social studies classes.

Sharon Vaughn and colleagues carried out the trial with schools with moderate to high concentrations of EALs. In the selected schools, all eighth-grade (Year 9) social studies teachers participated, and classes were randomly assigned to the treatment or comparison condition. Each teacher taught both PACT treatment classes and comparison classes, and the same social studies content was delivered to pupils in both conditions, but with the interrelated components of PACT included in the treatment classes.

Pupils in the treatment group did better than pupils in the comparison group on measures of content knowledge acquisition and content reading comprehension, but not general reading comprehension. Both EALs and non-EALs who received the intervention performed better on measures of content knowledge acquisition (effect size = 0.40) and content-related reading (effect size = 0.20).

Source: Improving content knowledge and comprehension for English language learners: Findings from a randomized control trial (January 2017), Journal of Educational Psychology, Vol 109(1)