Intergenerational and interethnic mental health: an analysis for the United Kingdom

This paper uses a nationally representative data set to examine the extent to which family migration history helps explains inter-ethnic variations in mental health in the UK. We confirm that there is significant variation in mental health across ethnic group and generation of migration. Furthermore, we show how these dimensions interact. The analysis explores the extent to which neighbourhood, personal characteristics and migration experience are related to mental health. We find evidence that all are important. Our results are consistent with a dynamic view of migration and settlement whereby individuals' circumstances and how they might contribute to mental health change over time and across generations

Flight validation of a pulsed smoke flow visualization system

A flow visualization scheme, designed to measure vortex fluid dynamics on research aircraft, was validated in flight. Strake vortex trajectories and axial core velocities were determined using pulsed smoke, high-speed video images, and semiautomated image edge detection hardware and software. Smoke was pulsed by using a fast-acting three-way valve. After being redesigned because of repeatedly jamming in flight, the valve shuttle operated flawlessly during the last two tests. A 25-percent scale, Gothic strake was used to generate vortex over the wing of a GA-7 Cougar and was operated at a local angle of attack of 22 degrees and Reynolds number of approximately 7.8 x 10(exp 5)/ft. Maximum axial velocities measured in the vortex core were between 1.75 and 1.95 times the freestream velocity. Analysis of the pulsed smoke system's affect on forebody vortices indicates that the system may reorient the forebody vortex system; however, blowing momentum coefficients normally used will have no appreciable affect on the leading-edge extension vortex system. It is recommended that a similar pulsed smoke system be installed on the F/A-18 High Angle Research Vehicle and that this approach be used to analyze vortex core dynamics during the remainder of its high-angle-of-attack research flights

Evaluation of Year 1 of the Tuition Partners Programme: Impact Evaluation for Primary Schools. Evaluation Report

The National Tutoring Programme (NTP) Tuition Partners (TP) programme was designed to provide additional support to schools and teachers to supplement classroom teaching through subsidised high-quality tutoring for pupils from an approved list of tutoring organisations, the Tuition Partners. This evaluation covers the TP programme as delivered in its first year by the Education Endowment Foundation (EEF), from November 2020 to August 2021. Tuition Partners was one arm of the NTP. The NTP aimed to support teachers and schools in providing a sustained response to the Covid-19 pandemic and to provide a longer term contribution to closing the attainment gap between disadvantaged pupils and their peers. The NTP was part of a wider government response to the pandemic, funded by the Department for Education and originally developed by the EEF, Nesta, Impetus, The Sutton Trust, and Teach First, and with the support of the KPMG Foundation. The EEF appointed 33 approved ‘Tuition Partners’ that schools could select from to deliver tuition. Schools could access 15 hours of tutoring per selected pupil (with a minimum of 12 hours being considered a completed block of tuition). Tuition was provided online and/or face-to-face; and was 1:1, or in small groups (1:2 or 1:3); and available in English, maths, science, humanities and modern foreign languages. Tuition was expected to be delivered in schools (before, during and after school), in addition to usual teaching; and, in certain circumstances, at home. The programme was targeted at disadvantaged pupils attending state-maintained schools in England, including those eligible for Pupil Premium funding (PP-eligible), Free School Meals (FSM), or those identified by schools as having an equivalent need for support. Participating schools had discretion to identify which of their pupils they felt would most benefit from additional tuition support. Pupils in Years 1–11 were eligible (5–16 years old). The programme aimed to reach 215,000 to 265,000 pupils, across 6000 state-maintained schools in England, and it was expected that approximately 20,000 tutors would be recruited by Tuition Partners. The TP programme was set up and delivered during the Covid-19 pandemic, requiring continued responsiveness to the challenges faced by schools including restricted attendance, remote teaching, and ongoing widespread staff and pupil absences. During the school closures to most pupils from January – March 2021, the EEF approved TPs to deliver online tuition at home, however many schools chose to wait to commence tutoring until schools reopened fully, and therefore started tutoring later than planned. This evaluation report covers the analysis on the impact of the TP programme on the maths and English attainment outcomes for primary school pupils (Years 1–6) using standardised classroom assessments. Separate reports relate to analysis on Year 11 pupils and an implementation and process evaluation (IPE). The evaluation findings for the TP programme are brought together in a summary and interpretation report that is available here. This evaluation uses a quasi-experimental design (QED), involving a group of intervention schools that participated in the TP programme, and a group of comparison schools that did not receive the programme. The evaluation relies on a propensity score matching and re-weighting approach to ensure that the intervention and comparison schools are similar to each other in important, observable regards. As pupils who would have received TP in comparison schools were difficult to identify, the evaluation focused on pupils eligible for Pupil Premium and on all pupils, as these groups can be identified in both TP and comparison schools. For English, the analysis is based on 165 primary schools with 7073 pupils eligible for Pupil Premium and for maths, 126 primary schools with 5102 pupils eligible for Pupil Premium3. An additional instrumental variable (IV) analysis, based on the sample of TP schools only, looked at the impact of TP in schools that signed up to the TP programme earlier (and that delivered more tutoring) compared to schools that signed up later. On average, pupils eligible for Pupil Premium in schools that received TP made similar progress in English and maths compared to pupils eligible for Pupil Premium in comparison schools (no evidence of an effect in English or in maths). This result has a low security rating. A particular challenge is that, on average, only approximately 20% of pupils eligible for Pupil Premium were selected for tutoring, meaning a large proportion of pupils eligible for Pupil Premium were included in the analysis who did not receive tutoring. Therefore, this estimated impact of TP is diluted and it is hard to detect any effect that may (or may not) be present. Similar analysis on all pupils found that pupils in schools that received TP made, on average, similar progress in English compared to all pupils in comparison schools (no evidence of an effect), and an additional one month’s progress in maths compared to pupils in comparison schools. However, there is uncertainty around these estimates, with the positive maths result being consistent with a null (0 months) or slightly larger positive effect (2 months) and the English result being consistent with small positive (1 month) or small negative effect (−1 months). Furthermore, this analysis was subject to even further dilution: on average, only 12% (for maths) and 14% (for English) of pupils in the analysed schools were selected for tutoring. Given this context, it is unlikely that any of these differences were due to TP. In the sample of TP schools, completing a 12-hour block of tutoring (compared to zero hours) was related to higher English scores amongst pupils eligible for Pupil Premium that received more tutoring due to the early sign-up of the school. An equivalent analysis for maths was not able to proceed. A different analysis within TP schools showed that pupils who received more hours of tutoring were associated with higher English scores on average than pupils who received fewer hours of tutoring. However, this was not the case for maths, where receiving more hours of tutoring was not associated with higher maths scores. These results are associations and are not necessarily causal estimates of impact; there may be other explanations for the results

Evaluation of Year 1 of the Tuition Partners Programme: Impact Evaluation Report for Year 11. Evaluation Report: An exploration of impact in Year 11

The National Tutoring Programme (NTP) Tuition Partners (TP) programme was designed to provide additional support to schools and teachers to supplement classroom teaching through subsidised, high quality tutoring for pupils from an approved list of tutoring organisations, the Tuition Partners. This evaluation covers the TP programme as delivered in its first year by the Education Endowment Foundation (EEF), from November 2020 to August 2021. Tuition Partners was one arm of the NTP. The NTP aimed to support teachers and schools in providing a sustained response to the Covid-19 pandemic and to provide a longer term contribution to closing the attainment gap between disadvantaged pupils and their peers. The NTP was part of a wider government response to the pandemic, funded by the Department for Education and originally developed by the EEF, Nesta, Impetus, The Sutton Trust, and Teach First, and with the support of the KPMG Foundation. The EEF appointed 33 approved ‘Tuition Partners’ that schools could select from to deliver tuition. Schools could access 15 hours of tutoring per selected pupil (with a minimum of 12 hours being considered a completed block of tuition). Tuition was provided online and/or face-to-face; and was 1:1, or in small groups (1:2 or 1:3); and available in English, maths, science, humanities and modern foreign languages. Tuition was expected to be delivered in schools (before, during and after school), in addition to usual teaching; and in certain circumstances, at home. The programme was targeted at disadvantaged pupils attending state-maintained schools in England, including those eligible for Pupil Premium funding (PP-eligible), Free School Meals (FSM), or those identified by schools as having an equivalent need for support. Participating schools had discretion to identify which of their pupils they felt would most benefit from additional tuition support. Pupils in Years 1–11 were eligible (5–16 years old). The programme aimed to reach 215,000 to 265,000 pupils, across 6,000 state-maintained schools in England, and it was expected that approximately 20,000 tutors would be recruited by Tuition Partners. The TP programme was set up and delivered during the Covid-19 pandemic, requiring continued responsiveness to the challenges faced by schools including restricted attendance, remote teaching, and ongoing widespread staff and pupil absences. During school closures to most pupils from January – March 2021, the EEF approved TPs to deliver online tuition at home, however many schools chose to wait to commence tutoring until schools reopened fully, and therefore started tutoring later than planned. The usual summer exams process for Year 11 pupils could not go ahead as planned in summer 2021, and GCSEs were determined by TAGs instead. This evaluation report covers the analysis on the impact of the TP programme on the maths and English attainment outcomes for Year 11 pupils only. Separate reports relate to analysis on a sample of primary schools and an implementation and process evaluation (IPE). The evaluation findings for the TP programme are brought together in a summary and interpretation report that is available here. This evaluation uses a quasi-experimental design (QED), involving a group of intervention schools that participated in the TP programme, and a group of comparison schools that did not receive the programme. The evaluation relies on a propensity score matching approach to ensure that the intervention and comparison schools are similar to each other in important, observable regards. As pupils who would have received TP in comparison schools were difficult to identify, the evaluation focused on pupils eligible for Pupil Premium and on all pupils, as these groups can be identified in both TP and non-TP schools. The analysis is based on 1,464 secondary schools with a total of 62,024 pupils eligible for Pupil Premium. The evaluation assessed impact in English and maths using Teacher Assessed Grades (TAGs) from 2021. Year 11 pupils eligible for Pupil Premium in schools that received TP made similar progress in English and maths compared to pupils eligible for Pupil Premium in comparison schools (there was no evidence of an effect in English or maths). A particular challenge is that, on average, only 12% of pupils eligible for Pupil Premium were selected for tutoring in maths and 9% were selected for tutoring in English, meaning the vast majority of the pupils included in the analysis did not receive tutoring. Therefore, this estimated impact of TP is diluted and it is hard to detect any effect that may (or may not) be present. When looking at all pupils in Year 11, pupils in schools that received TP made, on average, similar progress in English compared to all Year 11 pupils in comparison schools (there was no evidence of an effect). In maths, Year 11 pupils in schools that received TP made slightly less progress than all Year 11 pupils in comparison schools (though this effect was very small and equivalent to zero months ’ additional progress). However, this analysis was subject to even further dilution than the PPeligible analysis: only 7% of Year 11 pupils were selected for tutoring in maths and 6% in English. Given this context, it is unlikely that any of these differences were due to TP. Additional analysis restricted the sample of schools to those that targeted higher proportions of pupils eligible for Pupil Premium to receive tutoring, to reduce the issue of dilution and bring the group of analysed pupils closer to those that were selected for the intervention. In schools that selected over 50% of pupils eligible for Pupil Premium for tutoring, pupils eligible for Pupil Premium made similar progress in TP and comparison schools in English and maths. However, when the sample was restricted to schools that selected over 70% of pupils eligible for Pupil Premium for tutoring (and reducing dilution further), the impact of TP on pupils eligible for Pupil Premium is positive. In these schools, pupils eligible for Pupil Premium made, on average, the equivalent of two months additional progress in English and two months additional progress in maths, compared to pupils eligible for Pupil Premium in comparison schools. This analysis was based on a smaller sample of schools that were rematched to a comparison sample. However, different characteristics to the rest of the TP population of schools remained (more ‘Outstanding’ schools, lower percentage of FSM students), so this finding may not necessarily be generalisable to all TP schools. Within schools that participated in TP, pupils who received more hours of tutoring in maths obtained higher maths TAGs, and pupils who received more hours of tutoring in English obtained higher English TAGs, than pupils who received fewer hours of tutoring in the respective subjects. These results are associations and are not necessarily causal estimates of impact; there may be other explanations for the higher grades among these pupils

Improving Working Memory: Evaluation report and executive summary

This project tested the Improving Working Memory intervention (WM) and an adapted version, entitled the Working Memory Plus intervention (WM+). Working memory is the ability to remember and manipulate information over short time-frames. Previous research has suggested that working memory is a reliable predictor of numeracy outcomes. The Improving Working Memory intervention aimed to improve the numeracy skills of Year 3 pupils (aged 7-8) who were behind the class average in numeracy by improving their working memory capacity. The intervention, developed and previously tested by a team at Oxford University, combined the explicit teaching of working memory strategies by Teaching Assistants (TAs) and the independent practice of these strategies using web-based games. The intervention was delivered in ten one-hour sessions and lasted for one term. The Working Memory Plus intervention also had ten sessions, but only five were focused on working memory, whilst the other five were focused on arithmetic content. The project was a randomised controlled trial (RCT). 127 schools participated, being randomised at the school-level to one of three arms – the Improving Working Memory intervention, the Working Memory Plus intervention, or a business as usual control group. The primary outcome was maths attainment and the project also looked at working memory, and attention and behaviour in class as secondary outcomes. The process evaluation included fieldwork with eight intervention schools (four from each intervention), and an online survey of treatment and control schools. The trial took place between September 2016 and July 2017

Evaluation of Year 1 of the Academic Mentoring Programme: Impact Evaluation for Year 11. Evaluation Report: An exploration of impact in Year 11

The National Tutoring Programme (NTP) Academic Mentoring (AM) programme (2020/21) was designed to help disadvantaged pupils ‘catch up’ on missed learning by providing trained academic mentors to deliver one to one and small group tutoring in schools. This evaluation covers year 1 of the AM programme as delivered by Teach First from November 2020 to July 2021 (delivery was in three waves starting 26th October 2020, 15th January 2021 and 22nd February 2021). AM was one arm of the NTP. The NTP aimed to support teachers and schools in providing a sustained response to the Covid-19 pandemic and to provide a longer -term contribution to closing the attainment gap between disadvantaged pupils and their peers. The NTP was part of a wider government response to the pandemic, funded by the Department for Education (DfE) and was originally developed by the Education Endowment Foundation (EEF), Nesta, Impetus, The Sutton Trust, Teach First, and with the support of the KPMG Foundation. The DfE appointed Teach First to manage the provision of mentors (referred to as ‘academic mentors’) to schools; recruiting, training and placing them in schools. The mentor worked in the school setting as an employee of the school. It was expected that each academic mentor would work with at least 50 pupils between the date they started in school and the end of the academic year. Mentoring was provided online and/or face-to-face; and was one to one, or in groups of 2-4 pupils; and available in English/literacy, maths, science, humanities, and modern foreign languages. Mentoring was expected to be delivered in schools during normal teaching time, as well as before or after school. In certain circumstances, mentoring could be delivered online with pupil(s) at home. The AM programme was targeted at state-maintained primary and secondary schools serving disadvantaged populations. 89% of the schools met Teach First’s priority criteria, which is based on the proportion of children living in income deprived families (IDACI) and whether the school is in an area of chronic and persistent underperformance (AEA). The remaining 11% of schools had an above average proportion of pupils eligible for Pupil Premium (Teach First, 2021). Participating schools could decide which pupils received support from academic mentors. However, the programme encouraged them to select pupils from disadvantaged households or those whose education had been disproportionately impacted by Covid-19. Pupils in Years 1–11 were eligible (5–16 years old). The programme aimed to reach a minimum of 900 schools and 50,000 children, with 1,000 academic mentors. By the end of February 2021, it had surpassed targets having trained and placed 1,124 academic mentors in 946 schools and delivered mentoring sessions to 103,862 pupils, 49% of whom were identified by mentors as being eligible for Pupil Premium of Free School Meals (FSM), and 23% of whom were identified as having a special educational need or disability. The AM programme was initiated and delivered at a time of great pressure for schools when the education system had been disrupted by a series of school closures to most pupils and was contending with ongoing widespread pupil and staff absences. Covid-19 related issues disrupted the anticipated operation of academic mentoring during the year. The AM programme involved initial training and ongoing support from Teach First as intended but there was greater variation in schools’ deployment of mentors during the latter stages of the Autumn Term 2020/21, and during the January to March 2021 period of school closures to most pupils. This evaluation report presents the analysis of the impact of the AM programme on maths and English attainment outcomes for Year 11 pupils only—who represent a very small proportion of individuals targeted by the AM programme. Originally, it was planned to evaluate impact across all year groups (Years 1 – 11) at primary and secondary level using schools’ standardised assessment data from Renaissance Learning (RL) assessments and, in addition, to evaluate the impact for Year 6 pupils using Key Stage (KS) 2 data. However, these analyses could not go ahead as KS2 assessments were cancelled in summer 2021 (related to the ongoing Covid-19 pandemic) and because the number of schools providing agreement to use their RL data was insufficient to warrant impact analyses. Data was only available for pupils in Year 11. Since GCSEs could not go ahead as planned in 2021, the data was in the form of Teacher Assessed Grades (TAGs), which had not previously been used as an outcome measurement tool. Checks were therefore undertaken to explore if TAGs would be suitable as an outcome measure. The only analysis that could proceed was therefore exploratory. The evaluation uses a quasi-experimental design (QED), in which a group of secondary schools and Year 11 pupils who did not receive the AM programme were selected for comparison with schools and pupils who received the AM programme. Comparison schools were selected by matching schools that were similar in important, observable regards to the schools that participated in AM. The evaluation included analysis on the availability of AM for pupils who were eligible for Pupil Premium (a key focus of the overall NTP), and all pupils, as these groups could be identified for both the AM and non-AM schools. In addition, the evaluation aimed to analyse the impact on pupils who received AM by predicting their participation and identifying a comparison group of pupils with similar characteristics. Analysis was based on data about Year 11 pupils’ attainment and characteristics from the National Pupil Database (NPD) merged with data provided by Teach First about pupils’ participation in AM. In total, 159 AM schools (8,977 Year 11 pupils eligible for Pupil Premium) and an equal number of comparison schools (8,419 Year 11 pupils eligible for Pupil Premium) were included in the final analysis. The evaluation assessed impact in English and maths using Teacher Assessed Grades (TAGs) from 2021. Where appropriate, this impact evaluation refers to important implementation features from the implementation and process evaluation (IPE) conducted by Teach First themselves. However, there is no independent IPE data to draw on in the interpretation of the impact results. Of the Year 11 pupils selected for Academic Mentoring in this evaluation, 46% of them were eligible for Pupil Premium, however, despite this it is important to note that the number of Year 11 Pupil Premium-eligible pupils selected for AM in AM schools was small as a proportion of all Year 11 Pupil Premium-eligible pupils, and the number of these Year 11 Pupil Premium-eligible pupils receiving AM in maths and/or English (as opposed to other subjects), was smaller still. The same is the case when considering the whole year group of Year 11 pupils – the number receiving AM was small as a proportion of all Year 11 pupils. This means that in the analysis, the number of Year 11 pupils who actually received AM in maths and/or English was heavily ‘diluted’ by the number of pupils who did not. The primary impact findings must be therefore treated with a high degree of caution. The analysis was subject to very high dilution; a large proportion of the pupils eligible for Pupil Premium included in the analysis in AM schools were not selected for AM. This was due to limited programme reach and a tendency for teachers to allocate both non-Pupil Premium and Pupil Premium eligible pupils to the programme. This dilution means that, in order to detect an effect, either the effect would need to be very strong amongst the very small proportion of Year 11 pupils eligible for Pupil Premium who were selected for mentoring (and there was no indication that this was the case elsewhere in our analysis), and/or there would need to be strong spillover effects amongst the rest of the Year 11 pupils eligible for Pupil Premium. Although the programme Theory of Change includes such a mechanism, it is unlikely to be relevant at the dilution levels seen. With such high dilution, it is hard to detect whether AM had an effect on those who received mentoring in the analyses focusing on pupils eligible for Pupil Premium and on all pupils. It is not possible to conclude whether a lack of observed impact is due to the small proportion of disadvantaged pupils who received mentoring, or because AM did not work for those who received it. An additional challenge was that it was not possible to construct a comparison group of similar Year 11 pupils in nonAM to schools to those who received mentoring in AM schools, based on observable, pupil-level characteristics, and this impact analysis did not go ahead. Schools used information such as classroom assessments to select pupils into the programme that was not observable in the available datasets, suggesting that pupil-level selection was driven by unobserved dimensions. These constraints, both of very high dilution and not being able to identify a comparison group with similar pupil characteristics, mean that the evaluation is unable to conclude, with any certainty, whether or not AM had an impact on the English or mathematics attainment outcomes of those pupils who received it. The report must be considered in the light of these caveats. Year 11 pupils eligible for Pupil Premium in schools that received AM made, on average, similar progress in English compared to Year 11 pupils eligible for Pupil Premium in comparison schools (there was no evidence of an effect). In maths, Year 11 pupils eligible for Pupil Premium in schools that received AM made, on average, slightly more progress (equivalent to 1 months’ additional progress) compared to Year 11 pupils eligible for Pupil Premium in comparison schools. However, there is uncertainty around this result; it is also consistent with a null (0 months) effect or an effect of slightly larger than 1 month’s additional progress. A particular challenge in interpretation is that, on average, only 13% of Year 11 pupils eligible for Pupil Premium were selected for mentoring by schools, and only 4.2% of Year 11 pupils eligible for Pupil Premium were selected for mentoring in maths and 2.9% in English, meaning that the vast majority of pupils eligible for Pupil Premium included in the analysis did not receive mentoring. Therefore, this estimated impact of AM is severely diluted and it is unlikely any of these differences were due to AM. When looking at all Year 11 pupils, pupils in schools that received AM made, on average, similar progress in English and maths compared to all Year 11 pupils in comparison schools (there was no evidence of an effect). However, this finding was similarly subject to severe dilution: on average only 10% of Year 11 pupils in the analysed schools were selected for mentoring, with 3.4% in maths and 2.1% in English, and therefore it is hard to detect any effect that may (or may not) have been present. Within schools that offered AM to Year 11 pupils, there was no association between the number of completed mentoring sessions in maths and Year 11 outcomes in maths, or between the number of completed mentoring sessions in English and Year 11 outcomes in English. These results are associations and not necessarily causal

The Effect of Embedding Formative Assessment on Pupil Attainment

Evidence suggests that adapting teaching responsively to pupil assessment can be effective in improving students’ learning. However, existing studies tend to be small-scale, leaving unanswered the question of how such formative assessment can operate when embedded as standard practice. In this study, we present the results of a randomized trial conducted in 140 English secondary schools. The intervention uses light-touch training and support, with most of the work done by teacher-led teaching and learning communities within schools. It is, therefore, well-suited to widespread adoption. In our pre-registered primary analysis, we estimate an effect size of 0.09 on general academic attainment in national, externally assessed examinations. Sensitivity analysis, excluding schools participating in a similar program at baseline, and complier analysis both suggest a larger effect size of 0.11. These results are encouraging for this approach to improving the implementation of formative assessment and, hence, academic attainment. Our findings also suggest that the intervention may help to narrow the gap between high and low prior attainment pupils, although not the gap between those from disadvantaged backgrounds and the rest of the cohort

Theoretical analysis of the role of chromatin interactions in long-range action of enhancers and insulators

Long-distance regulatory interactions between enhancers and their target genes are commonplace in higher eukaryotes. Interposed boundaries or insulators are able to block these long distance regulatory interactions. The mechanistic basis for insulator activity and how it relates to enhancer action-at-a-distance remains unclear. Here we explore the idea that topological loops could simultaneously account for regulatory interactions of distal enhancers and the insulating activity of boundary elements. We show that while loop formation is not in itself sufficient to explain action at a distance, incorporating transient non-specific and moderate attractive interactions between the chromatin fibers strongly enhances long-distance regulatory interactions and is sufficient to generate a euchromatin-like state. Under these same conditions, the subdivision of the loop into two topologically independent loops by insulators inhibits inter-domain interactions. The underlying cause of this effect is a suppression of crossings in the contact map at intermediate distances. Thus our model simultaneously accounts for regulatory interactions at a distance and the insulator activity of boundary elements. This unified model of the regulatory roles of chromatin loops makes several testable predictions that could be confronted with \emph{in vitro} experiments, as well as genomic chromatin conformation capture and fluorescent microscopic approaches.Comment: 10 pages, originally submitted to an (undisclosed) journal in May 201