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Background: In recent years, data derived from international large-scale assessments have significantly influenced the discourse surrounding educational equity. However, the use of such data has often neglected the full spectrum of dimensions that equity encompasses, while being limited to exploring the relationship between achievement variations and student background. This approach, however, constrains our understanding of the rich notion. Methods: This paper aims to contribute to the advancement of current research by advocating for an alternative approach that encompasses all relevant dimensions of equity and examines their impact on both achievement and motivational outcomes. A cluster analysis manifests itself as the designated method to employ, as the concept of equity remains theoretically challenged and the detection of data patterns can serve as a strong step in its multifaceted inquiry. Moreover, this method enables us to incorporate the multidimensional concept in a country-level context. Results: Employing data from the Trends in International Mathematics and Science Study at grade four, this paper presents five distinct clusters of educational systems that illustrate diverse equity configurations. Notably, none of the identified clusters consistently scores high or low on all equity dimensions. This suggests that all of the clusters perform inconsistently to different degrees across the dimensions of equity. Furthermore, no single cluster emerges as superior to the others across both outcome measures. Conclusions: These findings shed light on the intricate interplay between equity, achievement, and motivation within the examined educational systems. The unique configuration of the equity dimensions within each cluster underscores the importance of adopting a nuanced evaluation of equity, which can enhance our understanding of equity patterns. [ABSTRACT FROM AUTHOR]

The focus of this study is to use the mixture item response theory (MixIRT) model while implementing the no-U-turn sampler as a technique for investigating the presence of latent classes (i.e., subpopulations) among eighth-grade students who were administered TIMSS 2019 mathematics subtest in paper format from the gulf cooperation council (GCC) countries. One-, two-, and constrained three-parameter logistic MixIRT models with one to four classes were used to fit to the data, where the model data fit was assessed using Bayesian fit indices. The results indicate that multiple latent classes or subpopulations can better reflect the mathematical proficiency of eighth graders from the four GCC countries, and specifically the two-class constrained three-parameter MixIRT model provides a relatively better fit to the data. The results also indicate that when a mixture of several latent classes present, the conventional unidimensional IRT model is limited in providing information for multiple latent classes and shall be avoided. In addition to adding to the existing literature on MixIRT models for international large-scale assessments such as TIMSS on its heterogenous subpopulations from a fully Bayesian approach, this study sheds light on the limitation of conventional unidimensional IRT models and subsequently directs attention to the use of the more complex MixIRT model for such assessments. [ABSTRACT FROM AUTHOR]

Inquiry‐Based Teaching Practice (IBTP) is an essential component of science education, and promoting its implementation is at the heart of various reform efforts. Even though science teachers regard IBTP as an essential pedagogical method, they rarely use it for various reasons. This study utilizes Bronfenbrenner's ecological framework to examine potential factors at various levels of the educational ecosystem that predict the implementation of inquiry‐based teaching practices among Grade 9 science teachers in South Africa. To this end, quantitative data from 537 educators who participated in the Trends in International Mathematics and Science Study (TIMSS) 2019 national assessment were utilized. Data were analyzed using descriptive statistics, Pearson correlation, and hierarchical multiple regression analysis. Results revealed that four variables at different socioeconomic levels were perceived to strongly predict teachers' implementation of inquiry teaching practices. These factors include teachers' job satisfaction, instructional resource shortage, and teachers' perception of the significance of various assessment strategies at the mesosystem level as well as teachers' participation in professional development at the exosystem level. Significant correlations exist between some of the predictive variables. Implications for policy are discussed. [ABSTRACT FROM AUTHOR]

Improving the mathematics performance of school children is an objective for many policy-makers around the world. Student-centered interactive pedagogies like classroom discussions and other dialogic interaction practices have been considered the best practice to engage learners effectively in the learning process. However, dialogic teaching practices are least used in most Asian countries that on average achieve the highest mathematics scores in international assessments. Based on this conundrum, this paper utilized a large-scale education dataset for five Asian countries, namely the Trends in International Mathematics and Science Study (TIMSS) dataset for learner data from Chinese Taipei, Hong Kong, Korea, Malaysia, and Singapore to examine the relationship between dialogic classroom interaction teaching practices and the mathematics performance of 8th-grade learners. Using a within-learner-between-subject estimation strategy to account for endogeneity, we established that learners who are taught more frequently through dialogic interactive teaching practices in mathematics classes achieve higher mathematics scores. Our results confirm that interactive pedagogies do provide learning benefits, even in countries that use them sparingly. Thus, our findings challenge the held assumption that the efficacy of dialogic classroom interaction practices is context and learning culture specific. Nevertheless, our study also shows that the highly endogenous nature of the teaching and learning environment and learner performance limits the ability of any study that uses observational data to establish the true impact of dialogic practices on learner mathematics performance. [ABSTRACT FROM AUTHOR]

This study capitalizes on response and process data from the computer‐based TIMSS 2019 Problem Solving and Inquiry tasks to investigate gender differences in test‐taking behaviors and their association with mathematics achievement at the eighth grade. Specifically, a recently proposed hierarchical speed‐accuracy‐revisits (SAR) model was adapted to multiple country‐by‐gender groups to examine the extent to which mathematics ability, response speed, revisit propensity, and the relationship among them differ between boys and girls. Results across 10 countries showed that boys responded to items faster on average than girls, and there was greater variation in boys' response speed across students. A mixture distribution of revisit propensity was found for all country‐by‐gender groups. Both genders had moderate to strong negative correlations between mathematics ability and response speed, supporting the speed‐accuracy tradeoff pattern reported in the literature. Results are discussed in the context of low‐stakes assessments and in relation to the utility of the multiple‐group SAR model. [ABSTRACT FROM AUTHOR]

Analyzing education does not only involve years of schooling, quality matters! This paper aims at providing better data on schooling with a focus on learning outcomes. It provides the largest dataset on learning outcomes, years of schooling and learning-adjusted year of schooling (LAYS) with comparable data between 1970 and 2020. The quantity dimension is measured by years of schooling and uses the latest data from Barro and Lee (J Dev Econ 104:184–198, 2013), while the quality dimension is taken from linking standardized, psychometrically robust international achievement tests and hybrid tests. The data are available for more than 120 countries between 1970 and 2020. Several findings can be highlighted. A global convergence on both learning outcomes and enrollment has occurred since 1970, but a breakdown can be found after 1990. A very low number of countries perform better after 2000 regarding the quality of schooling, while most countries have a stable level of learning outcomes. [ABSTRACT FROM AUTHOR]

Abstract Background In recent years, data derived from international large-scale assessments have significantly influenced the discourse surrounding educational equity. However, the use of such data has often neglected the full spectrum of dimensions that equity encompasses, while being limited to exploring the relationship between achievement variations and student background. This approach, however, constrains our understanding of the rich notion. Methods This paper aims to contribute to the advancement of current research by advocating for an alternative approach that encompasses all relevant dimensions of equity and examines their impact on both achievement and motivational outcomes. A cluster analysis manifests itself as the designated method to employ, as the concept of equity remains theoretically challenged and the detection of data patterns can serve as a strong step in its multifaceted inquiry. Moreover, this method enables us to incorporate the multidimensional concept in a country-level context. Results Employing data from the Trends in International Mathematics and Science Study at grade four, this paper presents five distinct clusters of educational systems that illustrate diverse equity configurations. Notably, none of the identified clusters consistently scores high or low on all equity dimensions. This suggests that all of the clusters perform inconsistently to different degrees across the dimensions of equity. Furthermore, no single cluster emerges as superior to the others across both outcome measures. Conclusions These findings shed light on the intricate interplay between equity, achievement, and motivation within the examined educational systems. The unique configuration of the equity dimensions within each cluster underscores the importance of adopting a nuanced evaluation of equity, which can enhance our understanding of equity patterns.

Abstract The focus of this study is to use the mixture item response theory (MixIRT) model while implementing the no-U-turn sampler as a technique for investigating the presence of latent classes (i.e., subpopulations) among eighth-grade students who were administered TIMSS 2019 mathematics subtest in paper format from the gulf cooperation council (GCC) countries. One-, two-, and constrained three-parameter logistic MixIRT models with one to four classes were used to fit to the data, where the model data fit was assessed using Bayesian fit indices. The results indicate that multiple latent classes or subpopulations can better reflect the mathematical proficiency of eighth graders from the four GCC countries, and specifically the two-class constrained three-parameter MixIRT model provides a relatively better fit to the data. The results also indicate that when a mixture of several latent classes present, the conventional unidimensional IRT model is limited in providing information for multiple latent classes and shall be avoided. In addition to adding to the existing literature on MixIRT models for international large-scale assessments such as TIMSS on its heterogenous subpopulations from a fully Bayesian approach, this study sheds light on the limitation of conventional unidimensional IRT models and subsequently directs attention to the use of the more complex MixIRT model for such assessments.

Improving the mathematics performance of school children is an objective for many policy-makers around the world. Student-centered interactive pedagogies like classroom discussions and other dialogic interaction practices have been considered the best practice to engage learners effectively in the learning process. However, dialogic teaching practices are least used in most Asian countries that on average achieve the highest mathematics scores in international assessments. Based on this conundrum, this paper utilized a large-scale education dataset for five Asian countries, namely the Trends in International Mathematics and Science Study (TIMSS) dataset for learner data from Chinese Taipei, Hong Kong, Korea, Malaysia, and Singapore to examine the relationship between dialogic classroom interaction teaching practices and the mathematics performance of 8th-grade learners. Using a within-learner-between-subject estimation strategy to account for endogeneity, we established that learners who are taught more frequently through dialogic interactive teaching practices in mathematics classes achieve higher mathematics scores. Our results confirm that interactive pedagogies do provide learning benefits, even in countries that use them sparingly. Thus, our findings challenge the held assumption that the efficacy of dialogic classroom interaction practices is context and learning culture specific. Nevertheless, our study also shows that the highly endogenous nature of the teaching and learning environment and learner performance limits the ability of any study that uses observational data to establish the true impact of dialogic practices on learner mathematics performance.

A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization in terms of latent states of "know/don't know" at the examinee level. This in turn suggests a way to join or "fuse" the models—through the probability of knowing. A general model that fuses the SDT choice model, for MC items, with a generalized sequential logit model, for OE items, is introduced. Fitting SDT and IRT models simultaneously allows one to examine possible differences in psychological processes across the different types of items, to examine the effects of covariates in both models simultaneously, to allow for relations among the model parameters, and likely offers potential estimation benefits. The utility of the approach is illustrated with MC and OE items from large-scale international exams. [ABSTRACT FROM AUTHOR]

Abstract This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal conditions to compute teacher-centered weights are detailed, including mathematical equations. We provide a proposal on how to define the targeted populations as well as how to collect data that is needed to derive teacher-centered weights, yet currently unavailable. We also tackle the issue of teacher nonresponse by proposing a respective adjustment factor, as well as mentioning the challenge of multiple selection probabilities when teachers teach in multiple schools. The core part of the paper focuses on studying the level of accuracy that can be expected when estimating teacher population characteristics. We use TIMSS 2019 data and simulate likely scenarios regarding the variance in weights. The results show that (i) the different weighting scenarios lead to relatively similar estimates; however, the differences between the scenarios are sufficient to justify the recommendation to use correctly derived teacher weights; (ii) differences between estimated standard errors based on complex sampling and corresponding estimates based on simple random sampling are sufficiently consistent to support use of a procedure to estimate standard errors that accounts for both sample weights and the complex sampling design; (iii) sample sizes and variance in weights significantly limit estimate precision, so that total population estimates with sufficient precision are available in the majority of countries but subpopulation features are generally not sufficiently precise. To provide a critical evaluation of our results, we recommend implementation of the proposed method in one or more countries. This recommended study will permit examination of logistical considerations in implementation of required changes in data acquisition and will provide data to replicate the analysis with teacher-centered weights.

Matematika merupakan mata pelajaran yang memiliki peran penting dalam kehidupan sehari hari sehingga perlu untuk diajarkan sedari kecil. Penilaian kemampuan matematika dapat dilakukan dengan berbagai cara, salah satunya adalah dengan menggunakan Trend in Intenational Mathematic Science Study (TIMSS). Penelitian ini bertujuan untuk mengetahui kemampuan kognitif matematika Siswa kelas homogen di SMP Negeri 3 Tanjung Redeb saat mengerjakan soal TIMSS materi bilangan. Penelitian ini menggunakan metode penelitian kuantitatif deskriptif. Populasi dalam penelitian ini adalah Siswa kelas VIII homogen di SMP Negeri 3 Tanjung Redeb, sedangkan sampel penelitian menggunakan teknik cluster random sampling. Teknik pengumpulan data yang digunakan adalah tes tertulis berupa 20 soal TIMSS uraian. Teknik analisis data yang digunakan adalah statistic deskriptif kuantitatif. Hasil penelitian ini menunjukkan bahwa kemampuan Siswa menjawab benar yaitu untuk kognitif pengetahuan dengan persentase 58%, kognitif penerapan dengan persentase 43% dan kognitif penalaran dengan persentase 20%. Berdasarkan hasil data tes tertulis dapat disimpulkan bahwa untuk kemampuan Siswa dominan tinggi pada kognitif pengetahuan sedangkan kemampuan Siswa dominan rendah pada kognitif penalaran.

This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal conditions to compute teacher-centered weights are detailed, including mathematical equations. We provide a proposal on how to define the targeted populations as well as how to collect data that is needed to derive teacher-centered weights, yet currently unavailable. We also tackle the issue of teacher nonresponse by proposing a respective adjustment factor, as well as mentioning the challenge of multiple selection probabilities when teachers teach in multiple schools. The core part of the paper focuses on studying the level of accuracy that can be expected when estimating teacher population characteristics. We use TIMSS 2019 data and simulate likely scenarios regarding the variance in weights. The results show that (i) the different weighting scenarios lead to relatively similar estimates; however, the differences between the scenarios are sufficient to justify the recommendation to use correctly derived teacher weights; (ii) differences between estimated standard errors based on complex sampling and corresponding estimates based on simple random sampling are sufficiently consistent to support use of a procedure to estimate standard errors that accounts for both sample weights and the complex sampling design; (iii) sample sizes and variance in weights significantly limit estimate precision, so that total population estimates with sufficient precision are available in the majority of countries but subpopulation features are generally not sufficiently precise. To provide a critical evaluation of our results, we recommend implementation of the proposed method in one or more countries. This recommended study will permit examination of logistical considerations in implementation of required changes in data acquisition and will provide data to replicate the analysis with teacher-centered weights. [ABSTRACT FROM AUTHOR]

In poor-performing, resource-constrained education systems, such as South Africa, solutions to improve academic achievement have tended to focus on resources and cognitive factors. An area that requires more attention is the importance of non-cognitive, psychosocial factors and their relationship with academic performance. These factors are strongly associated with behaviour, playing a role in either facilitating or impeding the learning process. Understanding attitudes is therefore critical in interpreting achievement results with a view to improving them. This article used data from the 2019 Trends in International Mathematics and Science Study administered to 20,829 South African students in Grade 9 to investigate the confidence these students have in their mathematics ability (their self-efficacy) and the relationship with achievement. Linear regression analysis was employed to determine: (1) the relationship between Grade 9 students' self-efficacy and mathematics achievement in South Africa; and (2) the contextual factors that were associated with the mathematics self-efficacy of the students. The results indicate a positive correlation between students' self-efficacy and their performance in mathematics. In addition, good teaching practices and parental involvement in school activities were associated with higher levels of students' mathematics self-efficacy. Being female was associated with lower levels of self-efficacy. These findings have important implications for shaping educational policy and practice in the resource constrained context of South Africa, to enhance students' self-efficacy and performance in mathematics. [ABSTRACT FROM AUTHOR]

Standardised International Large-Scale Assessments (ILSAs) have gained prominence in global and national educational discussions. ILSAs claim to offer valuable insights for improving education systems, but their impact on educational policy varies and has become a contested arena. This article analyses how these assessments fed educational policymaking in six Latin American countries based on a review of policy documents; the article advances three theses on how ILSAs are used by policymakers: First, there is a tokenistic usage of ILSAs; second, ILSAs must be considered more as political devices bolstering national reputation rather than studies in the academic sense; third, ILSAs can serve as leverage tools that can be mobilised for broader political ends. The study shows that the promises, designs and reporting of ILSAs are not necessarily aligned, that participation in ILSAs has become a symbolic gesture, and that ILSAs' data are often cherry-picked to support pre-existing diagnoses and policy agendas. [ABSTRACT FROM AUTHOR]

ICT integration in the classroom is viewed as a panacea towards resolving education challenges. A quantitative approach using South African Trends in International Mathematics and Science Studies (TIMSS) 2019 Grades 5&9 data with a positivist philosophical stance was used to explore ICT use. For a long time, most school research took the form of small-scale qualitative studies, such as case studies or critical policy studies; however, research in education has witnessed an increasing demand for high-quality, large-scale quantitative studies such as the current study. TIMSS utilised a two-stage stratified cluster sampling design, sampling schools by size and selecting intact classes. This study focusses on South Africa where 297 schools, 294 mathematics teachers, and 11,903 students were sampled at Grade 5 level, and, at Grade 9 level, the sample consisted of 519 schools, 543 mathematics teachers and 20,829 students. More than 50% of students attend schools lacking computers/tablets, a figure that rises to nearly 90% concerning their availability in classrooms. Less than half of students attend schools utilising online learning systems or providing digital resources. Principals in approximately half the schools indicated shortages/inadequacies in technologically competent staff, and audio-visual and computer technology/software resources. Approximately 80% of teachers expressed interest in future technology integration training for both grades when surveyed. Over half of the students lacked home internet access; however, the majority had access to cell phones and computers/tablets at home. In tailoring this study to the South African context, a novel model for ICT integration emerged which draws upon the Dynamic Model of Educational Effectiveness and the TIMSS curriculum model. Recommendations for improving policy and practice in ICT implementation in schools are structured around the new model. [ABSTRACT FROM AUTHOR]

Cross-national comparisons of educational achievement rely upon each participating country collecting nationally representative data. While obtaining high response rates is a key part of reaching this goal, other potentially important factors may also be at play. This paper focuses on one such issue—exclusion rates—which has received relatively little attention in the academic literature. Using data from 20 years of international large-scale assessment data, we find there to be modest variation in exclusion rates across countries and that there has been a relatively small increase in exclusion rates in some over time. We also demonstrate how exclusion rates tend to be higher in studies of primary students than in studies of secondary students. Finally, while there seems to be little relationship between exclusion rates and response rates, there is a weak negative association between the level of exclusions and test performance. We conclude by discussing how information about exclusions—and other similar issues—might be more clearly communicated to non-specialist audiences. [ABSTRACT FROM AUTHOR]

This study aims to determine the factors that influence the mathematics achievement of grade 4 students in Indonesia at the student and school level using Trends in International Mathematics and Science Study (TIMSS) 2015 data. Sample in this study were all grade 4 students in Indonesia who participated in TIMSS 2015. There are 4,025 students from 230 schools. The TIMSS 2015 data used in this study was analyzed using a multilevel model (MLM) using the R package ‘lme4’ software. The results of this study indicate that i) the school visited by each student accounts for the majority of the variance in the mathematics achievement of Indonesian grade 4 students (51%); ii) factors related to students’ self-construction of mathematics such as attitude-toward mathematics (ATM) and self-concept and factors related to schools such as socioeconomic status (SES) school, self-concept school, school readiness, general school resources, and teacher education level was found to influence students’ mathematics achievement positively and significantly, where self-concept school was the strongest predictor compared to other predictors; and iii) variables at the student and school level explain 35% of the total variance in Indonesian grade 4 students’ mathematics achievement. [ABSTRACT FROM AUTHOR]

Cultivating students' enjoyment of science is one of the significant aims of science education. However, it seems challenging to achieve this goal in most countries or economies. Using the Trends in International Mathematics and Science Study (TIMSS) 2019 Hong Kong data, this study aims to identify multiple configurations of school conditions to develop students' science enjoyment with a School Analytics model. A fuzzy-set Qualitative Comparative Analysis (fsQCA) was employed to capture the potential asymmetric relationships and measure multiple combinations of different conditions. Results indicated that no single school condition was necessary or sufficient for high enjoyment of science (ES). While lacking instructional clarity was a sufficient condition for low enjoyment of science (∼ES). Three different configurations resulted in ES and ∼ES respectively. The combination of supportive school discipline and high instructional clarity jointly constituted a crucial science learning environment for developing science enjoyment in Hong Kong secondary schools. Under this environment, the effectiveness of science investigation was further discussed to enhance science enjoyment. Our study enlightens educational practitioners to improve students' science enjoyment with multiple combinations of school conditions. [ABSTRACT FROM AUTHOR]

Research indicates that education quality – measured by test scores in international student surveys – predicts economic growth. In this paper, we extend previous findings up to 2016 and analyse test scores of upper-secondary school students only. We find that the positive relationship between growth and test scores holds in both cases. The share of top-performing students exhibits a stronger correlation with economic growth than does the share of students who meet basic requirements. [ABSTRACT FROM AUTHOR]

National policy initiatives in Ireland, such as Project Maths and the Science, Technology, Engineering, and Mathematics (STEM) Education Policy Statement have sought to increase the engagement and performance of students in mathematics and science. The current study investigated the performance of students in Ireland in these areas and in reading in international large-scale assessments (Programme for International Student Assessment [PISA], Trends in International Mathematics and Science Study [TIMSS], and Progress in International Reading Literacy Study [PIRLS]), with a view to better understand the performance of high-achieving students, relative to their counterparts in other countries in general, and in countries with similar average performance. Lower than expected proportions of high achievers were noted and a pattern of relative underachievement was observed among high achievers – those performing at the highest levels of proficiency, and those performing at key benchmarks, including the 75th and 90th percentiles – in mathematics and science to a greater extent than in reading. These issues were found to be consistent over time, and more prevalent at post-primary level, compared with primary level. The findings of this study are discussed with reference to individual and societal costs, and specific issues that need to be investigated further are identified. [ABSTRACT FROM AUTHOR]

The reports of the Education Evaluation Commission in the Kingdom of Saudi Arabia monitored the average performance of second-year intermediate students in the TIMSS international tests in the three consecutive years 2011, 2015, and 2019. The reports indicate a decline in the level of students' performance and obtaining lagging positions, as the Kingdom ranked (37) Out of (39) participating countries in 2019, and as an investment in the efforts of the Ministry of Education in developing education, the current study sought to train female second-year intermediate students to develop thinking skills to solve problems simulating international test questions (TIMSS) (algebra field) using the Madrasati platform according to the Needham constructivist model. The study applied the mixed approach on a purposive sample of (20) students. They were tested with a pre-test, followed by a proposed educational program using Needham's constructivist strategy through suggested cards in a sequence consistent with Needham's model with its five stages, the training phase was followed by a post-test for the female sample students. The results of quantitative and descriptive data analysis showed positive impact of the training according to the proposed educational program, and effectiveness of the Madrasati platform according to the Needham constructivist model in increasing the achievement of second-year intermediate female students in the international tests TIMSS (algebra field). [ABSTRACT FROM AUTHOR]

According to the World Economic Forum, the occupational gender gap with men dominating well-remunerated STEM careers is a key factor in the gender pay gap. However, the problem of underrepresentation of women in STEM fields is mitigated or reversed in some Eastern European and Islamic countries. This disparity suggests that cultural factors are at play. Gender-segregated schooling, which is commonly practiced in Islamic countries, is often seen as a contributing factor. However, the issue of gender-segregated education sparks much controversy. Critics argue evidence is lacking, and segregation may foster sexism and hinder social skills. In New Zealand, there is a significant opportunity to conduct research on gender segregation, as approximately 14.43% of girls and 14.35% of boys attend single-gender schools for their secondary (high school) education. In contrast to the USA and Australia, where single-gender schooling is predominantly offered by private and/or Catholic schools, the majority of New Zealand gender-segregated schools are state schools. Utilising the TIMSS 2019 dataset, our analysis revealed that girls from low socio-economic backgrounds and boys from higher socio-economic backgrounds who attend single-gender schools exhibit significantly higher mathematics and science achievement scores compared to their counterparts in co-educational settings. This success is particularly striking for girls in low socio-economic settings. Given mixed international evidence, this suggests that there must be protective factors at single-gender New Zealand schools, positively influencing these students. We examine potential factors setting apart girls-only schools to provide an explanation of our results: (1) a mitigated influence of gender socialisation practices and stereotype threat and (2) explicit messaging aimed at challenging stereotypes and empowering girls to actively engage in STEM fields. [ABSTRACT FROM AUTHOR]

In this study, measurement invariance and differential item functioning (DIF) studies of the TIMSS 2019 4th and 8thgrade mathematics and science achievement tests were conducted for the country groups participating in both TIMSS and eTIMSS. The study sample consisted of 9560 responders of the first booklet of the 2019 cycle. Multiple Group Confirmatory Factor Analysis (MGCFA) was utilized to test measurement invariance, and Mantel-Haenszel (MH), Logistic Regression (LR), and SIBTEST were used for the DIF analyses. The measurement invariance results indicated strict invariance between groups for all tests which included 111 items in total. In the DIF analyses, for the 4th and 8th-grade mathematics tests, only three items showed moderate DIF with MH, and four items showed DIF with SIBTEST. For the 4th-grade science test, one item showed moderate DIF with both MH and SIBTEST. However, in the 8th-grade science test, no items showed DIF with MH and LR methods, while four items showed moderate DIF with SIBTEST. Overall, MH and SIBTEST techniques were in agreement, whereas LR method produced inconsistent results and showed disagreement with these two methods. The results of the measurement invariance analysis and the LR method were consistent and indicated equivalency of TIMSS and e-TIMSS scores. [ABSTRACT FROM AUTHOR]

Abstract Background Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification. Determining the validity of the source of DIF has implications for how it is handled in practice. Method We demonstrate a form of sensitivity analysis that can point to model misspecification induced by item complexity as a possible cause of DIF, and show how such a cause of DIF might be accommodated through attempts to generalize the IRT model for the studied item(s) in psychometrically and psychologically plausible ways. Results In both simulated illustrations and empirical data from TIMSS 2011 and TIMSS 2019 4th and 8th Grade Math and Science, we have found that using a form of proposed IRT model generalization can substantially reduce DIF when IRT model misspecification is at least a partial cause of the observed DIF. Conclusions By demonstrating item complexity as a possible valid source of DIF and showing the effectiveness of the proposed approach, we recommend additional attention toward model generalizations as a means of addressing and/or understanding DIF.

Standardised tests of academic basic skills are an established feature of contemporary Australian schooling. Assessment results are widely reported and directly influence educational policymaking. Furthermore, Australian national educational priorities are linked to educational system accountability via the results of standardised tests. Given the influence and importance of assessment data, this paper aimed to collate publicly available data from four assessment programmes undertaken by Australian students, and document long‐term trends in average achievement across all available assessments. Results are reported from three international assessments, the Progress in International Reading Literacy Study, the Trends in International Mathematics and Science Study and the Programme for International Student Assessment (PISA), along with the only Australian assessment, the National Assessment Program: Literacy and Numeracy. Of these four, only PISA demonstrated systematic declines in average scores over time. For the remaining three programmes, results in the primary school years showed initial improvements that were subsequently maintained over remaining iterations of the tests. In secondary school, students' average results neither declined nor increased appreciably over time. The consensus of the four largest assessment programmes undertaken by Australian students since 1995 thus fails to support the prevailing narrative of a broadscale decline in academic skills attainment. [ABSTRACT FROM AUTHOR]

International Large-Scale Assessments (ILSAs) have had significant impact on education policy across the globe. But has interest in ILSAs now started to wane? This paper presents new evidence on this issue, exploring how the amount of attention three major ILSAs receive compares across countries, between studies and over time. Using information on Google searches made for ILSAs over time, we illustrate how results from TIMSS and PIRLS results receive significantly less attention than those from PISA. Globally, interest in ILSAs seems to have peaked in 2012 and has been on the decline since. There is however substantial cross-country variation, with increasing interest in some countries over the last decade (e.g. Sweden, Turkey) offsetting some of the fall in others (e.g. Japan, German). Moreover, while changes in scores seem to be related to the attention that ILSAs receive, other factors - including their current position in political and policy narratives - are also likely at play. [ABSTRACT FROM AUTHOR]

Background: Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification. Determining the validity of the source of DIF has implications for how it is handled in practice. Method: We demonstrate a form of sensitivity analysis that can point to model misspecification induced by item complexity as a possible cause of DIF, and show how such a cause of DIF might be accommodated through attempts to generalize the IRT model for the studied item(s) in psychometrically and psychologically plausible ways. Results: In both simulated illustrations and empirical data from TIMSS 2011 and TIMSS 2019 4th and 8th Grade Math and Science, we have found that using a form of proposed IRT model generalization can substantially reduce DIF when IRT model misspecification is at least a partial cause of the observed DIF. Conclusions: By demonstrating item complexity as a possible valid source of DIF and showing the effectiveness of the proposed approach, we recommend additional attention toward model generalizations as a means of addressing and/or understanding DIF. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) is rapidly changing communication and technology-driven content creation and is also being used more frequently in education. Despite these advancements, AI-powered automated scoring in international large-scale assessments (ILSAs) remains largely unexplored due to the scoring challenges associated with processing large amounts of multilingual responses. However, due to their low-stakes nature, ILSAs are an ideal ground for innovations and exploring new methodologies. Methods: This study proposes combining state-of-the-art machine translations (i.e., Google Translate & ChatGPT) and artificial neural networks (ANNs) to mitigate two key concerns of human scoring: inconsistency and high expense. We applied AI-based automated scoring to multilingual student responses from eight countries and six different languages, using six constructed response items from TIMSS 2019. Results: Automated scoring displayed comparable performance to human scoring, especially when the ANNs were trained and tested on ChatGPT-translated responses. Furthermore, psychometric characteristics derived from machine scores generally exhibited similarity to those obtained from human scores. These results can be considered as supportive evidence for the validity of automated scoring for survey assessments. Conclusions: This study highlights that automated scoring integrated with the recent machine translation holds great promise for consistent and resource-efficient scoring in ILSAs. [ABSTRACT FROM AUTHOR]

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While between-school tracking has been a well-explored topic especially with countries tracking their educational systems as early as at the age of 10, within-school ability grouping has received comparatively less analytical attention. This paper explores effects of within-school informal tracking practices at socioeconomically and ethnically mixed elementary schools. In Slovakia, where these practices were previously described as linked to segregation of Roma students, they result in academically, socioeconomically, and ethnically distinct separate classes in a school. We try to identify the early tracking practices of schools by exploring if two or more classes included in the TIMSS 2019 assessment in a particular school display extreme differences with regard to ethnic (Slovak vs. Roma) or socioeconomic (defined by parental education levels or occupation) composition. We employ a series of hierarchical linear models to assess the impact of early within-school informal tracking on mathematics and science test results of students from low-track classes. We check the robustness of our findings in a parallel propensity scores approach. Our results confirm that class-level segregation seems to have a very significant connection to academic performance of students from low-track classes. When compared to identical students from non-tracked classes, students from low-track classes have more than 15% lower test scores in mathematics and science. This points to the need to further explore early informal within-school tracking practices which have so far escaped analytical attention. While not a topic of cross-national assessment programs per se, this can be done using data from major international assessments. [ABSTRACT FROM AUTHOR]

This paper explores the measurement capabilities of the Trends in International Mathematics and Science Study (TIMSS) and the Program for International Student Assessment (PISA) in assessing school factors that influence student performance. We specifically focus on the 2015 assessments of the science performance of eighth graders in Sweden and Norway. This was the latest year when the two assessments were conducted in the same year and science was the major subject area in the PISA assessment, which was essential for maximizing the assessments' comparability. Using multilevel models, the study identifies common and unique factors across the assessments and investigates the factors that influence student performance at different proficiency levels. The findings highlight the importance of school-level factors, which are significant in both assessments. Moreover, both assessments provide information on overlapping sets of factors that have varying influence on the performance of students with different proficiency levels. Overall, there are limited common factors between TIMSS and PISA. School factors vary between low-performing and high-performing schools, with differing significance in Norway and Sweden. The results indicate that TIMSS and PISA assessments offer complementary information, particularly for low-performing schools. Our findings suggest that different school types may benefit or suffer from distinct school factors. The findings are relevant for both educational professionals and policy-makers. [ABSTRACT FROM AUTHOR]

International large-scale assessments (ILSAs) have used graphical response-based items to measure student ability for decades, but they have yet to implement automated scoring of these responses and instead rely on human scoring alone. To investigate how scores provided by machine algorithms compare to those provided by human raters, we applied convolutional neural networks (CNNs) to classify image-based responses from eight Timss 2019 items. Our results show that the most accurate CNN models classified over 99% of the image responses into the appropriate scoring category for dichotomous items and almost 98% for one trichotomous item. Additionally, during the modeling process, the CNNs correctly classified numerous image responses that human raters had scored incorrectly. For most items, the number of incorrectly human-scored responses exceeded the average number of responses misclassified by the most accurate models. These results suggest that automated scoring using CNNs is comparable to, and in many cases more accurate, than human raters, even across a wide variety of graphing tasks. This paper argues that the machine learning procedure explored could be implemented in ILSAs as a verification method to improve the accuracy and consistency of graphical response item scores. In lieu of additional human raters, ILSAs could implement CNN-based automated scoring to provide a second set of scores, thus reducing the workload and costs associated with human scoring.

Bu çalışmada öğrencilerin sosyoekonomik durumu, matematik öğrenmeyi sevmeleri, okullarının akademik başarıya verdikleri önem ile öğrenci matematik başarısı arasındaki ilişki çok düzeyli yapısal eşitlik modeliyle (ÇDYEM) incelenmiştir. Araştırmada örneklem TIMSS 2011 çalışmasına katılan Türkiye’deki 5960 sekizinci sınıf öğrencisidir. Araştırma bulguları öğrencilerin matematik başarı varyansının %33’ünün okullar arası farklılıklardan, %67’sinin öğrenciler arası farklılıklardan kaynaklandığını göstermiştir. ÇDYEM’de, öğrenci düzeyinde öğrencilerin sosyoekonomik durum ve öğrencilerin matematik öğrenmeyi sevmeleri, okul düzeyinde yine sosyoekonomik durum ve okullarının matematik başarısına verdiği önem yer alarak her iki düzeyde de bu değişkenlerin matematik başarısıyla ilişkisi modellenmiştir. Bulgulara göre sosyoekonomik durumu yüksek olan öğrencilerin bireysel başarıları; dolayısıyla bu öğrencilerin bulunduğu okulların ortalama başarıları diğer okullara göre nispeten daha yüksektir. Okul düzeyindeki sosyoekonomik durumun okulun akademik başarıya önem vermesini pozitif yönde etkileyerek okulların daha yüksek başarıya sahip olmalarına katkı sağladığı görülmüştür. Ayrıca, matematik öğrenmeyi seven öğrencilerin daha yüksek matematik başarısına sahip olduğu bulgusuna ulaşılmıştır. Son olarak, araştırma bulgularına dayanarak eğitim politikaları kapsamında önerilerde bulunulmuştur.

We investigated two research questions: which students are more likely to respond inconsistently to mixed-worded questionnaire scales, and which country samples have larger shares of inconsistent respondents? We defined an inconsistent response as strongly agreeing or disagreeing with both positively and negatively worded items of the same scale. Since we assumed that inconsistent responding occurs due to a lack of carefulness, reading, or cognitive skills, we expected to find that inconsistent responding was associated with lower achievement, younger age, being a nonnative speaker, and being a boy. We used data from all 38 countries that participated in the fourth- and eighth-grade assessments of TIMSS (Trends in International Mathematics and Science Study) 2019. Using the mean absolute difference method, we identified shares of 1‒21% inconsistent respondents across samples. The results generally supported our hypotheses, especially the hypothesis that inconsistent responding is more common among students and countries with lower mathematics achievement levels. [ABSTRACT FROM AUTHOR]

On average, boys score higher on math achievement tests and girls score higher in reading; these gaps increase between primary and secondary school. Using PISA, PIRLS, and TIMSS data, we investigate the role of early educational tracking (sorting students into different types of secondary schools at an early age) on gender gaps in test achievement in a cross-country difference-in-differences framework. We find strong evidence that early tracking increases gender differences in reading. For math test scores, we do not find consistent evidence that early tracking contributes to the gender gap. [ABSTRACT FROM AUTHOR]

AbstractIn this study, we investigated the relationships between three pivotal factors that influence student performance, including opportunity-to-learn (OTL) factors, which included proximal indicators that represent science-specific learning opportunities, student motivation (propensity factor), and crucial student and teacher antecedent factors by using Trends in International Mathematics and Science Study dataset. Results showed that student propensity factors, particularly self-concept in science, and family socioeconomic status were the two strongest and positive, significant predictors of student science performance. However, the link between OTL and science performance was mixed. Additionally, OTL had less predictive power than propensity factors on science performance, but the relationship between OTL and propensity factors were strong. Implications for the examination on the opportunity-propensity model and science education are discussed. [ABSTRACT FROM AUTHOR]

Questionnaires in educational research assessing students' attitudes and beliefs are low-stakes for the students. As a consequence, students might not always consistently respond to a questionnaire scale but instead provide more random response patterns with no clear link to items' contents. We study inter-individual differences in students' intra-individual random responding profile across 19 questionnaire scales in the TIMSS 2015 eighth-grade student questionnaire in seven countries. A mixture IRT approach was used to assess students' random responder status on a questionnaire scale. A follow-up latent class analysis across the questionnaire revealed four random responding profiles that generalized across countries: A majority of consistent nonrandom responders, intermittent moderate random responders, frequent random responders, and students that were exclusively triggered to respond randomly on the confidence scales in the questionnaire. We discuss the implications of our findings in light of general data-quality concerns and the potential ineffectiveness of early-warning monitoring systems in computer-based surveys. [ABSTRACT FROM AUTHOR]

How does quantifying and ranking national performance influence state behavior? Cross-national assessments in education, such as the Programme for International Student Assessment (PISA) promoted by the Organisation for Economic Co-operation and Development (OECD), have become increasingly prominent in recent years. However, cross-national assessments are politically contentious, and their impact remains underexplored. We argue that assessment participation has a meaningful, positive impact on education outcomes and evaluate three hypotheses related to elite, domestic, and transnational mechanisms. Our mixed-method approach draws on a panel dataset covering all cross-national assessments and all countries as well as an original survey of education officials directly responsible for planning and implementation in 46 countries. We find that assessment participation increases net secondary enrollment rates even after accounting for potential self-selection. The magnitude of this increase is large: on a global basis, it is equivalent to improved access to higher education for 27–32 million students annually. The empirical evidence suggests elite-level mechanisms are primarily responsible for these findings. [ABSTRACT FROM AUTHOR]

Copyright of Hebron University Research Journal (Humanities) is the property of Hebron University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)