A study published in the Journal of Public Economics examines how leisure time can impact pupils’ effort and educational achievement by looking at the overlap of major football tournaments (the FIFA World Cup and the UEFA European Championship) with GCSE exams in England.
Using seven years of subject data on pupils in England,
taken from the National Pupil Database, Robert Metcalfe and colleagues
estimated the overall effect of a tournament by comparing within-pupil
variation in performance during the exam period between tournament and
Overall, they found a negative average effect of the
tournament on exam performance, as measured by whether pupils achieved a grade
C or higher in at least 5 subjects at GCSE. In tournament years, the odds of
achieving the benchmark of a grade C or higher in at least 5 subjects fell by
12%. For pupils who are likely to be very interested in football (defined as
likely to be white, male, disadvantaged pupils), the impact is greater, with
the odds of achieving the benchmark reduced by 28%. This result is important as
this group is already the lowest performing, with only 21.3% achieving a grade
C or higher in at least 5 subjects at GCSE in non-tournament years.
An earlier study reported in a previous issue of Best Evidence in Brief also found that some pupils perform less well in their GCSEs in years when there is a major international football tournament taking place.
effort and educational achievement: Using the timing of the World Cup to vary the
value of leisure (January 2019), Journal
of Public Economics, Volume 172
Helping pupils to understand the logical principles underlying maths may improve their mathematical achievement, according to the findings of a randomised controlled trial published by the Education Endowment Foundation (EEF).
Mathematical Reasoning lessons focus on developing pupils’ understanding of the logic principles underlying maths, and cover principles such as place value and the inverse relation between addition and subtraction. One hundred and sixty English primary schools took part in the trial, and were randomly allocated to receive either Mathematical Reasoning or to be in the control group. The control group was given the opportunity to take part in the programme the following year. Teachers in the intervention schools delivered the programme to Year 2 pupils over 12 to 15 weeks as part of their usual maths lessons. Learning was supported by online games, which could be used by pupils at school and at home.
The independent evaluation by a team from the National Institute of Economic and Social Research (NIESR) found a small but statistically significant effect size of +0.08 on maths achievement for pupils who took part in the programme, compared to other pupils. It had the same impact for pupils eligible for free school meals. They also found some evidence that the programme had a positive impact on mathematical reasoning.
Source: Mathematical Reasoning: Evaluation report and executive summary (December 2018), Education Endowment Foundation.
An evaluation of the Education Endowment Foundation’s trial of Families and Schools Together (FAST), delivered by Save the Children, did not appear to make a difference to children’s achievement, but was found to be an effective mechanism for engaging parents in their children’s early education. FAST was also shown to have a positive impact on children’s social and behavioural outcomes across the whole year group and not just for the children who participated in the programme.
FAST is a parental engagement programme that aims to support parenting and enhance links between families, schools and the community. Parents and their children attend eight weekly two-and-a-half-hour group sessions delivered after school by accredited FAST trainers.
The school-level randomised trial measured the impact of FAST for the whole year group on Key Stage 1 (KS1) reading and arithmetic achievement, and children’s behavioural and pro-social outcomes (measured using the Strengths and Difficulties Questionnaire). One hundred and fifty eight schools took part in the trial, with a total of 7,027 pupils across the Year 1 cohort in these schools, and 632 pupils taking part in the eight-week programme.
The evaluation found no evidence that FAST had an effect on KS1 reading and arithmetic outcomes for the whole year group (effect size = +0.01). There was also no evidence that FAST had an impact on KS1 outcomes for the children whose families took part in the eight-week programme. However, FAST showed some promise on non-academic outcomes, with positive outcomes for the whole year group. Immediately after the eight-week programme, Year 1 pupils in the intervention schools had a higher average pro-social score and a lower average total difficulties score than pupils in comparison schools. However, these effects diminished by the end of Year 2.
Source: Families and Schools Together (FAST) evaluation report and executive summary (November 2018), Education Endowment Foundation
The Education Endowment Foundation has published the results of a randomised controlled trial of IPEELL
The IPEELL intervention is a writing process model in which pupils are encouraged to plan, draft, edit, and revise their writing. IPEELL stands for Introduction, Point, Explain, Ending, Links, and Language. The strategy provides a clear structure to assist writers and can be used for most genres of writing, including narrative writing. In addition to the writing process, the IPEELL intervention also involves ‘memorable experiences’ for pupils designed to act as a stimulus for their writing.
The trial tested the impact of one year of IPEELL for children in Year 6 and the impact of two years of IPEELL for children who started it in Year 5 and continued in Year 6. In total, 84 schools and 2,682 children in the north of England participated in the one-year trial and 83 schools and 2,762 children participated in the two-year trial. Writing outcomes were measured using Key Stage 2 (KS2) writing outcomes for the one-year trial and a bespoke writing test based on historic KS2 writing tests for the two-year trial.
The results showed that pupils who used IPEELL for two years made more progress in writing (effect size = +0.11) than pupils who did not. However, they made less progress in reading, spelling and mathematics than pupils in the control group (ES = -0.17—0.30). Pupils who used IPEELL for one year made less progress in writing, reading, spelling and maths than comparison pupils.
A previous trial of the approach had shown large positive results, but there were important differences between the two trials. In this latest trial, the model used teacher trainers who had never seen IPEELL delivered in the classroom. It also measured the average impact across all pupils, while the first looked only at pupils with low prior attainment. In this latest trial, pupils with low prior attainment who used IPEELL for two years made more progress in writing (effect size = +0.26) than pupils who did not – a larger effect size than the figure for all pupils.
Source: Calderdale Excellence Partnership: IPEELL evaluation report and executive summary (November 2018), Education Endowment Foundation
A study published in the journal Archives of Disease in Childhood looks at whether children who are born prematurely (at 23–36 weeks) are more likely to struggle in school compared to their full-term peers.
David Odd and colleagues used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (a longitudinal population-based cohort study that enrolled pregnant women in 1991 and 1992) to examine how the educational progress of children who are born prematurely varies from their peers throughout school, and to what extent they catch up over time.
The study found that, on average, premature children had lower test scores at Key Stage 1 (5–7 years), and continued to perform below their peers throughout school However, there was some evidence of catching up between Key Stage 1 and Key Stage 2 (age 7 to 11 years), particularly among children with the lowest scores. Between Key Stage 2 and Key Stage 4 (14-16 years) premature children progressed at a similar rate as their peers.
There was little evidence that closing the gap between KS1 and KS2 was explained by special education support. The authors point out that educating premature children in their correct school year for their expected birth date may be a cost-effective way of supporting them, and also highlight the importance of early schooling and environment for these children.Source: Prediction of school outcome after preterm birth: a cohort study (October 2018), Archives of Disease in Childhood doi: 10.1136/archdischild-2018-315441
Researchers from the Medical Research Council (MRC) Cognition and Brain Sciences Unit at the University of Cambridge have used machine learning – a type of computer algorithm – to identify clusters of learning difficulties which did not match the previous diagnosis children had been given.
The study, published in Developmental Science, used a sample of 530 children (ages 5–18) who were referred to the Centre for Attention Learning and Memory (CALM) by health and education professionals because they were struggling in school. All the children in the sample completed a number of cognitive and learning assessments, they underwent a structural MRI scan, and their parents completed behaviour questionnaires.
Based on the data collected from these tests, the computer algorithm identified four groups that the children could be matched to: (1) broad cognitive difficulties and severe reading, spelling and maths problems; (2) age-typical cognitive abilities and learning profiles; (3) difficulties with working memory skills; and (4) difficulties with processing sounds in words.
While these groups aligned closely with other data on the children, such as the parents’ reports of their communication difficulties and educational data on reading and maths, there was no correspondence with their previous diagnoses. To check if these groupings corresponded to biological differences, the groups were checked against MRI brain scans from 184 of the children. The groupings mirrored patterns in connectivity within parts of the children’s brains, suggesting that the machine learning was identifying differences that partly reflect underlying biology.
The researchers conclude that these findings reinforce the need for children to receive detailed assessments of their cognitive skills to identify the best type of support.
Source: Remapping the cognitive and neural profiles of children who struggle at school (September 2018), Developmental Science