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Meta-analysis is the synthesis of findings from research projects, which enables an estimate of the average or pooled effect across various studies. This study presents findings from the intention to treat analysis for a series of educational evaluations in England using a two-stage meta-analysis with standardised outcome data and individual participant data meta-analyses. The research estimates the overall impact of educational trials on pupils eligible for Free School Meals (FSM) and the attainment gap in literacy and mathematics performance between FSM and non-FSM pupils based on analysis of 88 trials and data from over half a million pupils. For the meta-analyses, frequentist and Bayesian multilevel models were used to estimate the individual and pooled effect size across categories of explanatory variables such as age groups (key stages in England) and aspects of the type of interventions (one-to-one, small group, whole class). Results indicated that the overall impact of interventions on the literacy outcomes of FSM pupils was positive, with a pooled effect size of 0.06 (0.03, 0.08). However, for mathematics, no overall effect on FSM pupils was observed. Analysis of the attainment gap indicated that literacy outcomes for FSM pupils were improved by interventions marginally more than for non-FSM pupils (pooled attainment gap 0.01 (-0.01, 0.04)). The risk of bias assessment showed that estimates were consistent across different methodological approaches. Overall, evidence from this study can be used to identify, test and scale educational interventions in schools to improve educational outcomes for disadvantaged pupils.

Educational researchers advocate the use of an effect size and its confidence interval to assess the effectiveness of interventions instead of relying on a p-value, which has been blamed for lack of reproducibility of research findings and the misuse of statistics. The aim of this study is to provide a framework, which can provide direct evidence of whether an intervention works for the study participants in an educational trial as the first step before generalizing evidence to the wider population. A hierarchical Bayesian model was applied to ten cluster and multisite educational trials funded by the Education Endowment Foundation in England, to estimate the effect size and associated credible intervals. The use of posterior probability is proposed as an alternative to p-values as a simple and easily interpretable metric of whether an intervention worked or not. The probability of at least one month's progression or any other appropriate threshold is proposed to use in education outcomes instead of using a threshold of zero to determine a positive impact. The results show that the probability of at least one month's progress ranges from 0.09 for one trial, GraphoGame Rime, to 0.94 for another, the Improving Numeracy and Literacy trial.

Genetic diversity and environmental factors are long believed to be the dominant contributors to phenotypic diversity in crop plants. However, it has been recently established that, besides genetic variation, epigenetic variation, especially variation in DNA methylation, plays a significant role in determining phenotypic diversity in crop plants. Therefore, assessing DNA methylation diversity in crop plants becomes vital, especially in the case of crops like chickpea, which has a narrow genetic base. Thus, in the present study, we employed whole-genome bisulfite sequencing to assess DNA methylation diversity in wild and cultivated (desi and kabuli) chickpea. This revealed extensive DNA methylation diversity in both wild and cultivated chickpea. Interestingly, the methylation diversity was found to be significantly higher than genetic diversity, suggesting its potential role in providing vital phenotypic diversity for the evolution and domestication of the Cicer gene pool. The phylogeny based on DNA methylation variation also indicates a potential complementary role of DNA methylation variation in addition to DNA sequence variation in shaping chickpea evolution. Besides, the study also identified diverse epi-alleles of many previously known genes of agronomic importance. The Cicer MethVarMap database developed in this study enables researchers to readily visualize methylation variation within the genes and genomic regions of their interest (http://223.31.159.7/cicer/public/). Therefore, epigenetic variation like DNA methylation variation can potentially explain the paradox of high phenotypic diversity despite the narrow genetic base in chickpea and can potentially be employed for crop improvement. [ABSTRACT FROM AUTHOR]