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In this journal, Sciffer et al. (Large-scale Assessments in Education 10:1–22, 2022), hereafter SP&M, conclude that school socioeconomic compositional (SEC) or school socioeconomic status (school-SES) effects in Australia are substantial and substantively important for research and policy. This paper demonstrates that these claims are unwarranted. Their SEC estimates are much larger than estimates from comparable studies and a metastudy. Despite plausible theoretical reasons and empirical evidence, SP&M do not consider that school academic composition is a significant predictor of student achievement independent of SEC. SEC effects are confounded by academic composition and are typically trivial when considering academic composition. The second part of this paper compares SP&M's estimates with analysis of the same data, from the Australian National Assessments in Performance—Literacy and Numeracy (NAPLAN). In a model corresponding to SP&M analyses comprising demographics, SES, school-SES, and student-level prior achievement, the effects of school-SES are small, with standardized effects mostly less than 0.10. With the addition of academic composition measured by school-level prior achievement, school-SES effects are effectively zero. In contrast, academic composition has significant, albeit small, impacts on student achievement. Therefore, contrary to SP&M's (2022) conclusion, school-SES effects on student achievement in NAPLAN are negligible, whereas school-level prior achievement has small effects. That is not to say that school-SES is always irrelevant, but any assessment of its importance must consider both student- and school-level prior achievement. [ABSTRACT FROM AUTHOR]

The study of variables related to the use of ICT in the classroom is a topic of interest that has been frequently researched. In this paper, after examining the importance of teacher training in explaining the use of ICT in the classroom, we focused on analysing the weight of variables related to teaching practices and the organisational context of schools, which are variables that are less frequently addressed in the literature. To do so, a secondary analysis was carried out using data provided by the Teaching and Learning International Study (TALIS 2018). Specifically, we worked with a sample of 3,918 principals and 64,899 teachers from a total of 3921 schools in 21 countries. A multilevel binary regression model with random intercept, fixed coefficients and a two-level structure with teachers at level 1 and schools at level 2 was used. The results indicate that the presence of ICT in the classroom is associated with self-efficacy in teaching and the cognitive activation of students and with the organisational aspects of the school, which are scarcely addressed by the existing literature on this topic of interest, such as school climate, educational innovation and cooperation among teachers. Based on these results, we reflect on possible ways to promote the use of ICT in the classroom.

This study examines the effect of school socioeconomic composition on student achievement growth in Australian schooling, and its relationship with academic composition utilising the National Assessment Program—Literacy and Numeracy (NAPLAN) dataset. Previous research has found that school composition predicts a range of schooling outcomes. A critique of school compositional research has been that measurement error may have biased findings of compositional effects. Prior studies have found that socioeconomic compositional effect sizes are small when models include academic composition. The relationship between socioeconomic and academic compositions has yet to be fully determined. Multi-level regressions and structural equation models were compared to estimate the degree of bias in socioeconomic compositional effects due to measurement error. Multi-level path models were used to test if academic composition mediated the relationship between socioeconomic composition and achievement growth. The results showed that measurement error did not bias compositional effects in the dataset, and academic composition mediates the relationship between socioeconomic composition and achievement growth. We argue that school value-add research should include academic composition to account for contextual effects. The socioeconomic compositional effect is of practical significance to policy makers and educational researchers due to its relative size compared to average student achievement growth. Potential reforms include ensuring public subsidies to private schools in Australia do not increase school segregation and the amelioration of the effects of residential segregation through school funding reforms. [ABSTRACT FROM AUTHOR]

Background: While the relationship between school socioeconomic composition and student academic outcomes is well established, knowledge about differential effects is not extensive. In particular, little is known whether the relationship differs for students with varying levels of academic performance. We examined whether the school socioeconomic composition effect on academic achievement is stronger or weaker for high-performing students than for average- and low-performing students. Australia is a theoretically interesting case study as it has high levels of school socioeconomic segregation compared to other economically developed countries. Methods: We conducted quantile regression analysis using data from the Australia PISA 2018 sample (N = 14,273 15-year-old students). We examined the effect of school socioeconomic status (school SES) on student performance in reading, mathematical and scientific literacy. Results: We found that the school socioeconomic composition effect is substantial and is similar for all students, regardless of their level of academic performance. The findings also show that school SES is a stronger predictor than student SES for all student performance quintiles, and the size of the school SES effect relative to the size of student SES effect is larger in lower performance quintiles. Conclusions: These results indicate no differential effect of school SES on reading, mathematical or scientific literacy for students of varying levels of academic performance. The relationship is similarly strong and positive for high-performing students as it is for their lower performing peers. As school SES is a strong predictor for all students regardless of their level of academic performance, we argue that equity of educational outcomes can be best achieved by policies and structures that promote socioeconomically mixed rather than segregated schools. We also call for more research that seeks to identify and understand possible differential effects of school socioeconomic composition on a range of academic and non-cognitive student outcomes. [ABSTRACT FROM AUTHOR]

Background: Data from the Programme for the International Assessment of Adult Competencies (PIAAC) revealed that countries systematically differ in their respondents' literacy, numeracy, and problem solving in technology-rich environments skills; skill levels also vary by gender, age, level of education or migration background. Similarly, systematic differences have been documented with respect to adults' participation in education, which can be considered as a means to develop and maintain skills. From a psychological perspective, motivation to learn is considered a key factor associated with both skill development and participation in (further) education. In order to account for motivation when analyzing PIAAC data, four items from the PIAAC background questionnaire were recently compiled into a motivation-to-learn scale. This scale has been found to be invariant (i.e., showing full weak and partial strong measurement invariance) across 21 countries. Methods: This paper presents further analyses using multiple-group graded response models to scrutinize the validity of the motivation-to-learn scale for group comparisons. Results: Results indicate at least partial strong measurement invariance across gender, age groups, level of education, and migration background in most countries under study (all CFI > 0.95, all RMSEA < 0.08). Thus, the scale is suitable for comparing both means and associations across these groups. Conclusions:Results are discussed in light of country characteristics, challenges of measurement invariance testing, and potential future research using PIAAC data.

Ample evidence indicates that a person's human capital is important for success on the labor market in terms of both wages and employment prospects. However, unlike the efforts to identify the impact of school attainment on labor-market outcomes, the literature on returns to cognitive skills has not yet provided convincing evidence that the estimated returns can be causally interpreted. Using the PIAAC Survey of Adult Skills, this paper explores several approaches that aim to address potential threats to causal identification of returns to skills, in terms of both higher wages and better employment chances. We address measurement error by exploiting the fact that PIAAC measures skills in several domains. Furthermore, we estimate instrumental-variable models that use skill variation stemming from school attainment and parental education to circumvent reverse causation. Results show a strikingly similar pattern across the diverse set of countries in our sample. In fact, the instrumental-variable estimates are consistently larger than those found in standard least-squares estimations. The same is true in two "natural experiments," one of which exploits variation in skills from changes in compulsory-schooling laws across U.S. states. The other one identifies technologically induced variation in broadband Internet availability that gives rise to variation in ICT skills across German municipalities. Together, the results suggest that least-squares estimates may provide a lower bound of the true returns to skills in the labor market.

Background: Educational qualifications and literacy skills are highly related. This is not surprising as it is one aim of educational systems to equip individuals with competencies necessary to take part in society. Because of this relationship educational qualifications are often used as a proxy for "human capital". However, from a theoretical perspective, there are many reasons why this relationship is not perfect, and to some degree this is due to third variables. Thus, we want to explore the net relationship between educational attainment (harmonized according to the International Standard Classification of Education, ISCED) and literacy skills, and how much skills vary within education levels across countries. Methods: We use data from 21 countries from the Programme for the International Assessment of Adult Competencies 2012. This paper compares the literacy skills of adults who achieved different levels of educational attainment across countries. Given the high degree of educational differentiation in most countries, we do this using a more differentiated educational attainment variable than what is commonly used. In our analyses we firstly adjust for factors that are likely to affect access to education and the acquisition of educational qualifications and literacy skills, such as parental education and language and migration background. In a second step, we also take into account factors affecting skill development after initial formal education, such as occupation and skill use at home. Results: We firstly find a high degree of heterogeneity of skills across countries for equivalent education categories. Secondly, we find skill similarities for equivalent education categories classified at different broad education levels, sometimes even breaking the hierarchical order of 'higher education entails higher competencies'. Conclusion: We conclude that ISCED levels cannot be taken as a cross-nationally comparable proxy for human capital in terms of literacy skills, and that education has to be harmonized in a substantively more meaningful way in future adult literacy surveys.