To understand the relationship between social background and sex in schooling, we use Bourdieu's theory of social reproduction and a feminist perspective of gender as practice. We pose two questions: ...(1) What is the relationship between economic and cultural capital and achievement for 4th-grade females versus males studying in Germany? (2) Is the relationship between school composition and student achievement different for 4th-grade females versus males? We report no differences between females and males in the relationships between social background and achievement (p > 0.05). However, the relationship between class-aggregated social background and achievement is halved in female-majority mathematics classrooms (β = -12.6, p < 0.05).
The purpose of this study is to compare and contrast student, teacher, and school factors that are associated with student mathematics achievement in South Korea and the United States. Using the data ...from the Trends in International Mathematics and Science Study (TIMSS) 2011, this study examines factors that are linked to teachers who deliver quality instruction with high self-efficacy in both countries. We also investigate the association between teachers with high-quality instruction and high self-efficacy and 8th graders' mathematics achievement. It was found that teachers' perceived academic emphasis was commonly associated with teachers who claimed to provide high-quality mathematics instruction with high self-efficacy. However, the two countries' results differed in the association between teachers' opportunities to learn in professional development programs and high-quality instruction with high self-efficacy. Implications from this study suggest that the quality and training of teachers and students' gender gap in achievement are significant issues.
Professional development for teachers has been a substantial issue in contemporary educational research and policy. Yet, opportunities for professional development activities have been very limited ...in Turkey. In this study, we examined Turkish teachers' involvement in professional development activities by comparing their participation with the level of participation in top-performing countries in the Trends in International Mathematics and Science Study 2011, including Singapore, South Korea, Hong Kong, Taiwan, and Japan. Then, we also conducted face-to-face interviews with 13 Turkish mathematics and science teachers in order to explore their views about the current professional development opportunities for teachers in Turkey. The results of this study indicate that, when compared with teachers from Turkey, a larger proportion of teachers in the top-ranking countries participated in professional development activities in most of the sub-categories of professional development in both mathematics and science. In line with this finding, results of the qualitative analysis suggest that most of the teachers in Turkey are not happy with the quantity of professional development activities available to them. In addition, teachers believe that the quality of professional development provided to teachers is low in terms of its connection to the practice of teaching. This situation might hinder teachers' performance and negatively impact student achievement in Turkey.
This paper examines changes in demographic and socioeconomic inequalities in student achievement over the school career, and the extent that these inequalities are accounted for by other influences ...such as, region and socioeconomic background (where appropriate), school differences and prior achievement. The data analysed are from a longitudinal cohort of Victorian government school students in Years 3, 5 and 7 between 2008 and 2012. The most important finding is the dominant influence of prior achievement which substantially reduces demographic and socioeconomic differences. The strong effects of prior achievement hold even after differences between schools and socioeconomic background have been taken into account. Therefore, policy positions and theories of student performance that give primacy to the socioeconomic resources of families when students are at school, or schools themselves, are not supported. The genesis of demographic and socioeconomic inequalities in student achievement occurs prior to Year 3 and point to the importance of factors operating in the preceding years. Author abstract
Class size reduction has been viewed as one school mechanism that can improve student achievement. Nonetheless, the literature has reported mixed findings about class size effects. We used 4th- and ...8th-grade data from TIMSS 2003 and 2007 to examine the association between class size and mathematics achievement in public schools in Cyprus. We employ instrumental variables methods, and take advantage of a regression discontinuity design to examine causal effects of class size on mathematics achievement. The results indicate a non-significant relationship between class size and mathematics achievement in 8th grades. However, there is evidence of positive class size effects in 4th grade. The gender gap is significant and favoured males in 4th grade and females in 8th grade. SES indexes such as parental education and items in the home are positively and significantly related to mathematics achievement. Teacher and school variables are not significantly related with mathematics achievement.
Math achievement is not a unidimensional construct but includes different skills that require different cognitive abilities. The focus of this study was to examine associations between a number of ...cognitive abilities and three domains of math skills (knowing, applying and problem solving) simultaneously in a multivariate framework. Participants were 723 third-grade children (mean age = 9.07) from 28 elementary schools. Confirmatory factor analyses with binary indicators showed that a four-factor model of math skills (Knowing-Recalling, Knowing-Computing, Applying and Problem Solving) and a nine-factor model of cognitive abilities (Nonverbal and Verbal Reasoning, Verbal Concepts, Planning, Visuo-Spatial Working Memory (WM), two types of Verbal WM, Phonological Awareness and Phonological WM) fit the data well. Results from structural equation modelling showed that verbal reasoning and verbal concepts were most consistently associated with math knowing and problem solving domains. Verbal concepts contributed also to the math applying domain. In addition, simultaneous processing of verbal WM predicted problem solving skills in math. The results can be used in supporting the learning process of students with difficulties in math.
The purpose of this study is to examine the relationship among students' experiences of teaching activities in science lessons, students' attitudes towards science and their achievement in science. ...The sample consisted of 105,078 students worldwide who participated in the Trends in International Mathematics and Science Study (TIMSS) 2003. The students completed a questionnaire and took a science test. We conducted structural equation modeling to estimate and test the hypothesized relationship between students' experiences of ways of teaching, their attitude and their achievement. In addition, after sorting appropriate groups from participating countries/regions, we compared the structural equation model for each group based on the results of the analyses. Under the condition that we do not focus the relevant factors which influence their achievement, except school factors, the results indicate that first, science lessons, including the teaching activity of having students working out problems by themselves, enhanced students' self-concepts for science and improved their science achievement; second, introducing only the teaching activity of having students work out problems by themselves to science lessons was not effective enough for improving students' achievements. This means that bringing in characteristic factors of teaching activities, which were unique for each group of countries/regions, is important.
In large-scale assessment programs such as NAEP, TIMSS and PISA, students' achievement data sets provided for secondary analysts contain so-called
plausible values. Plausible values are multiple ...imputations of the unobservable latent achievement for each student. In this article it has been shown how plausible values are used to: (1) address concerns with bias in the estimation of certain population parameters when point estimates of latent achievement are used to estimate those population parameters; (2) allow secondary data analysts to employ
standard techniques and tools (e.g., SPSS, SAS procedures) to analyse achievement data that contains substantial measurement error components; and (3) facilitate the computation of standard errors of estimates when the sample design is complex. The advantages of plausible values have been illustrated by comparing the use of maximum likelihood estimates and plausible values (PV) for estimating a range of population statistics.
In 2015, PISA and TIMSS are coming up to us together. In this study, the data from PISA and TIMSS are used to investigate that which one is a better indicator of national science and technology (S&T) ...competitiveness? Number of S & T journal articles (per million people) is used as a measure to represent the national S&T competitiveness. Average IQ of the population, research and development (R&D) expenditure (% of GDP) and number of R&D researchers and technicians which affect the national competitiveness in S&T were also investigated. The study shows that PISA science scores would more significantly indicate national S&T competitiveness than TIMSS. Moreover, the study also shows a strong link between competence in S&T and IQ, research and development expenditure (% of GDP) or number of research and development researchers and technicians. Some possible micro-foundations of these relationships are discussed, and policy implication is clear.
Large-scale studies, such as the Trends in International Mathematics and Science Study (TIMSS), provide data to understand cross-national differences and similarities. In this study, we aimed to ...identify factors predicting mathematics achievement of Turkish students by comparing to Australian students. First, construct equivalence and item bias were evaluated to check the comparability. Second, factors predicting mathematics achievement of Turkish and Australian students were identified. Then, propensity score matching on background variables was conducted to identify the remaining achievement differences. Results indicated that mathematics skills were free of construct bias in these groups. After removal of some biased items, we obtained an item bias free booklet. Additionally, students' self-confidence and educational resources at home were significant predictors of achievement. Propensity score analysis indicated that educational resources and to a somewhat lesser extent self-confidence were effective in explaining achievement differences between these two countries.
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