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School inspections are a key component of the accountability system in many education systems, including England. The judgments and reports produced through these inspections are widely used by parents when they are choosing a school for their children. But should they be? This paper presents new evidence on this issue. We illustrate how parents selecting secondary schools using Ofsted judgments will often be basing their decision on dated information. Indeed, half the time, this will be based on a period in which the school had a different headteacher. We find there are almost no differences in future academic, behavioral, school leadership and parental satisfaction outcomes between schools rated as good, requiring improvement and inadequate in the inspection data available to parents at the point of school selection. That is, parents who choose a "good" secondary school for their child will not leave with appreciably better outcomes than a parent who selects an "inadequate" school. The one exception to this is an Outstanding judgment, which does predict future academic outcomes -- though only if the inspection was conducted within the last five years. We thus advise parents that -- besides choices involving Outstanding schools -- Ofsted judgments are of limited use to them in selecting a school.

Family structures are associated with achievement outcomes, but the percentage of children residing in different family structures has changed over time. In this paper, we revisit data from the Programme for International Student Assessment (PISA) to determine whether previous findings have also changed over time. Drawing on PISA 2012, we employ multilevel modelling to examine whether school and country compositional factors are still salient a decade later. The final analytical sample included 172,452 students in 7,391 schools from 24 countries. The results indicate, like previous research, an educational disadvantage for students that attend schools with a large concentration of children from single-parent homes. However, this disadvantage is largely due to the lower socioeconomic composition of these schools. At the country level, there is little support for the hypothesis that the achievement gap between students from two- versus one-parent households is greater in countries with higher percentages of single-parent families.

Background: Bullying is widely acknowledged as one of the most harmful events in a child's life, leading to negative life experiences and outcomes. However, 'school effects of bullying' are rarely studied from an international perspective, especially with international large-scale data. Purpose: In this study, we aim to look at bullying through an international comparative approach, focusing on the contribution of the school, the education system and culture, and pupil level factors such as socio-economic status (SES) and gender. Our key question is whether school factors can affect bullying prevalence. Methods: We used data from six countries (USA, Finland, England, Romania, Korea and Italy) from the Trends in International Mathematics and Science Study (TIMSS), a large-scale international study. We used multilevel modelling to analyse the dataset. Findings: We find little evidence of a relation between country policies and levels of bullying, though there are differences in the extent to which school and pupil factors are related to bullying. The most consistent relationship was between gender and bullying, with prevalence higher among boys, while school factors were not significant. Conclusion: The findings indicate that 'one size fits all' school policies might not be the best course of action, and individual support might be a more fruitful avenue.

An article by Kim et al. from 2014 examined individual- and school-level variables affecting the information and communication technology (ICT) literacy level of Korean elementary school students, finding differential gender effects. In this secondary data replication, we used data from the 2018 International Computer and Information Literacy Study, focusing on data from Korea as main replication. As many characteristics of the study as possible, such as variables and analytical strategy, were modelled in the analysis. Additional analyses included 13 countries and jurisdictions, varied centring techniques for variables, and missing data treatment. The replication and analyses were pre-registered via the Open Science Framework. The main analysis did not replicate the main gender finding. However, it was also clear that, despite care taken in a rigorous replication, analytical variability still plays a large role in replications of findings, and with secondary datasets. We discuss the implications of this for secondary data replications.

Many national education systems incorporate a central inspectorate tasked with visiting, evaluating and reporting on the performance of schools. The judgements produced by inspectors often play a part in the way that schools are held to account and constitute an important source of data in their own right. Inspection reports are therefore of great interest to researchers. However, the sheer quantity of inspection reports produced by national school inspectorates creates challenges for analysts. We demonstrate the use of text mining -- automated processing and analysis of unstructured textual data -- to analyse the complete corpus of school inspection reports released by the English national schools inspectorate since the turn of the century. More precisely, we report the results of a sentiment analysis, comparing the tone of inspection reports across the different grades awarded in each inspection and across different Chief Inspectors. In doing so, we hope to demonstrate the efficiency with which text mining approaches can provide representative analysis of very large volumes of inspection reports, making them a useful complement to smaller-scale, manual analyses. Resources and references are provided for researchers looking to use text mining techniques.

Physiological measures associated with emotional expressions have been used extensively in lab- and, more recently, digital-learning settings. However, the portable and ubiquitous nature of hardware that measures these physiological features makes them particularly useful in situations where you do not want the hardware to be too obtrusive, like in contexts of informal learning. In this proof-of-concept study, we apply skin conductance methods that measure Electrodermal Activity (EDA) to a family everyday activities context, in which a parent and their children, complete several science learning activities, while being recorded by both video and EDA hardware. We analyse the resulting data in three different ways: (i) a peak analysis in software recommended by the hardware provider, (ii) a conventional, qualitative microanalysis, and (iii) a method mainly used by econometricians to discover 'structural breaks' in time series data. We conclude that all three provide a piece of the overall puzzle, revealing up- and down-sides of each method. [ABSTRACT FROM AUTHOR]

A recent discussion involves the elaboration on possible design principles for sequences of tasks. This paper builds on three principles, as described by Bokhove and Drijvers (2012a). A model with ingredients of crises, feedback and fading of sequences with near-similar tasks can be used to address both procedural fluency and conceptual understanding in an online environment. Apart from theoretical underpinnings, this is demonstrated by analyzing a case example from a study conducted in nine schools in the Netherlands. Together with quantitative results of the underlying study, it is showed that the model described could be a fruitful addition to the task design repertoire.

Policy changes in the higher education landscape have given way to increased interest in the way students perceive engagement in UK higher education. This paper examines whether we can reliably distinguish between institutions and disciplines, and what key student and institutional variables are a predictor of engagement of undergraduate students. Using data from two waves of the United Kingdom Engagement Survey (UKES), a national survey of undergraduate student engagement, we constructed multilevel models for different aspects of student engagement. The results show that the vast majority of the variance of the models is at the student level, indicating that demographic characteristics seem to contribute most to differential aspects of engagement. Some variance at student level could be explained: females, distance learners, part-time students, and disabled student indicators were negative predictors of engagement, while indicators for Black and minority ethnic (BME) students and for students from Africa and Asia were positive predictors of engagement.

In England teachers of secondary school mathematics and science are in short supply and it is important to understand how pre-service teachers develop and maintain networks of support during their training year and the impact these networks can have on their training outcomes. The purpose of this study is to examine how changes to the size and composition of these support networks during the training year are associated with programme outcomes. The paper draws on social network theory to examine the nature of the support networks that develop around each pre-service teacher, and examines how supportive ties were initiated, maintained, and broken over the course of the training year. A survey design was utilised to collect data at four time points across the 2014-2015 academic year from a total cohort of more than 75 pre-service teachers. At all four time points, participants were asked to nominate those peers and others to whom they had turned during the previous month for different aspects of support. Results showed that the size and composition of support networks changed over time with significant differences in the development of the networks between pre-service teachers on school-led and university-led programmes.

This article reports on an exploratory project in which technology and dynamic social network analysis (SNA) are used for modelling classroom interaction. SNA focuses on the links between social actors, draws on graphic imagery to reveal and display the patterning of those links, and develops mathematical and computational models to describe and explain those patterns. "Dynamic" SNA extends SNA and builds on previous research on network change. Utilizing data from six videos from the TIMSS video study and a convenience sample of five observations of one teacher in a secondary school in the south of England, a methodology for dynamic SNA was applied to classroom interaction data. The results are in two ways relevant for this journal. Firstly, they show that recent developments in SNA might be usefully applied to furthering knowledge about the dynamics of classroom interaction. Secondly, the results provide an example of the use of tablet technology for fieldwork data collection.

Student satisfaction has received growing attention in Higher Education systems in recent years, and are increasingly used for internal and external accountability in the sector. This does leave us with questions on the extent to which variance in student satisfaction can be explained by Higher Education Institution (HEI) and course attended rather than by individual student characteristics; and on what factors may predict student satisfaction. In this study we used the Postgraduate Taught Experience Survey (PTES) to look at these questions in a sample of approximate 70000 UK postgraduate students from 100 HEI's. Firstly, confirmatory factor analyses were used to test the validity of the proposed multidimensional structure of student satisfaction in PTES. Then multilevel models were used to look at variance at three levels (HEI, course and student), and the relationships between institutional and student factors collected in PTES and student satisfaction. Two years of data (2014 and 2015) were used. Findings suggest that over 90% of variance is explained at the student level for all dimensions of student satisfaction in both years, with variance at the HEI level being particularly low. Individual student characteristics explain more variance than institutional characteristics, but only some (such as BME status) are significant, and explained variance is low. These findings suggest using student satisfaction as an accountability measure in HE may be highly problematic.

This paper suggests a set of key features that might be appropriate when talking about digital textbooks or e-textbooks for mathematics education. The set of features are presented in a coherent framework and the paper will discuss each of the six features: widgets, interactivity, feedback, storing results, instructional design, authorability, interoperability and standards. I will argue, though, that these individual features are 'more than the sum of the parts'; in other words that it's the fact they are integrated into one e-textbook design that makes them useful. I try to support this by reframing the question to 'what will we miss if the feature wouldn't be there?'

The design and arrangement of appropriate automatic feedback in digital learning environment is a widely recognized issue. In this article, we investigate the effect of feedback on the design and the results of a digital intervention for algebra. Three feedback principles guided the intervention: timing and fading, crises, and feedback variation. The intervention aims at improving algebraic expertise and is deployed in fifteen grade 12 mathematics classes in nine secondary schools. Results show that the use of feedback timing and fading, the creation of crises and feedback variation facilitates the acquisition of algebraic expertise, and that relevant feedback fosters algebra learning by decreasing the number of attempts needed for a task while improving the scores. We conclude there is potential in applying these design principles in an online algebra education design.

In this article we report on the effects of a digital intervention on the development of algebraic expertise of 17-18 year old students in the Netherlands. The question to be answered was whether the intervention would be effective and what factors influenced the outcome. With notions of formative assessment and symbol sense as guiding theoretical concepts, the intervention's design principles included the concepts of crises, formative scenarios and feedback. The intervention aimed to improve algebraic expertise and was deployed in fifteen grade 12 mathematics classes in nine schools. Data included results from pre- and posttests, scores, questionnaires and log files of the students' digital work, and responses to a student survey. Results from the effect study, analyzed with multilevel models, showed that the intervention was effective in improving algebraic expertise. Factors that significantly contributed to the post-test score were pre-test results, the amount of time invested in digital self-tests and attitude towards mathematics. The intervention's success was not significantly influenced by other variables. We conclude that these types of intervention have a potential for the acquisition of versatile algebraic expertise. (Contains 3 figures and 5 tables.)

In the Netherlands, as in many other countries, the algebraic expertise of students graduating from secondary education is an issue. The use of digital tools for algebra education is expected to change epistemologies, activity structures and student achievement. Therefore, a study was set up to investigate in what way the use of ICT in upper secondary education might enhance the algebraic expertise of students. One of the first decisions to be made concerned the choice of appropriate digital tools. This paper describes the process of designing and using an instrument for evaluating digital tools. The conceptual framework guiding this process includes notions on symbol sense, instrumental genesis and formative assessment. The evaluation instrument is designed through a Delphi method and provides a blueprint of tool features that are relevant for the purpose of this study. The results show that such an evaluation instrument is valuable both for choosing appropriate digital tools and for making concrete the aims and expectations that researchers have on the issue of integrating technology in algebra education. The final instrument is presented and illustrated through examples implemented in different digital algebra tools. (Contains 5 tables, 8 figures, and 3 footnotes.)