The relations of a school’s capacity for institutional diversity to student achievement in socio-economically,ethnically, and linguistically diverse schools

This study examines how a school’s capacity for institutional diversity relates to student achievement in socio-economically, ethnically, and linguistically diverse schools. It also investigates whether various student groups benefit differently from a school’s level of student diversity and its institutional capacity for diversity. Using data from the High School Longitudinal Study of 2009 (HSLS:09), the study uses two-level hierarchical linear models to explore the relationships between multiple types of school diversity and student achievement and to examine the role played by an institution’s capacity for diversity. Our findings confirm that different types of school diversity have different associations with the academic achievement of students from varied family and language backgrounds. We also find that a school’s capacity for diversity is a significant predictor of the academic success of students, particularly for students from lower income families and those who use a home language other than English.     

A Multilevel Modelling Approach to Investigating Factors Impacting Science Achievement for Secondary School Students: PISA Hong Kong Sample

This study utilized data from the 2006 Programme for International Student Assessment Hong Kong sample to investigate the factors that impact the science achievement of 15-year-old students. A multilevel model was used to examine the factors from both student and school perspectives. At the student level, the results indicated that male students, students from high socioeconomic status (SES) families, students with higher motivation and higher self-efficacy, and students whose parents highly value science are more likely to demonstrate achievement in science. At the school level, the results showed school science achievement differences can be explained by school enrolment size, school SES composition, and instruction time per week. Contrary to the negative influence of school size that was reported in previous studies, our findings suggested a positive relationship between school enrolment size and science achievement. This finding leads to an international discussion of school size.     

A multilevel latent growth curve approach to predicting student proficiency

Value-added models and growth-based accountability aim to evaluate school??s performance based on student growth in learning. The current focus is on linking the results from value-added models to the ones from growth-based accountability systems including Adequate Yearly Progress decisions mandated by No Child Left Behind. We present a new statistical approach that extends the current value-added modeling possibilities and focuses on using latent longitudinal growth curves to estimate the probabilities of students reaching proficiency. The aim is to utilize time-series measures of student achievement scores to estimate latent growth curves and use them as predictors of a dichotomous outcome, such as proficiency or passing a high-stakes exam, within a single multilevel longitudinal model. We illustrated this method through analyzing a three-year data set of longitudinal achievement scores and California High School Exit Exam scores from a large urban school district. This latent variable growth logistic model is useful for (1) early identification of students at risk of failing or of those who are most in need; (2) a validation or/and adequacy of student growth over years with relation to distal outcome criteria; (3) evaluation of a longitudinal intervention study.     

The investigation of school effects on student achievement in science: A multilevel analysis of educational data

The Second International Science Study provides a large Australian data base for the purpose of secondary analyses. This data base consists of a large number of student and school level variables which were examined with reference to the students nested within the schools. Multilevel analysis involves the use of the hierarchical linear model to adequately compensate for variability between-schools, as well as within-schools. The role of the school organization and effects such as the average student ability and average social factors were found to substantially influence student achievement in science. These school effects were also found to influence boys and girls differently with respect to their science achievement as measured by the tests in this study. Specializations: large scale data analysis, gender differences, socioeconomic factors, epidemiology.     

Measurement and evaluation issues in education: The value of multivariate techniques in evaluating an innovative high school reform program

The purpose of this chapter is twofold. The first is to explore uses of new methods for the analysis of multilevel data in school effectiveness research with limited observed data, where the word “limited” is used because more often than not interesting information about changes in teaching styles and the influence of teachers on students is limited, and sometimes incomplete. The statistical and mathematical models we use to analyze our data should allow us to deal with these facts. Secondly a contribution is made to school effectiveness research by establishing that multilevel causes determine student achievement. The combination of student ability, a new curriculum and teacher satisfaction predict student achievement in a multilevel multivariate analysis. The rich data set contains 342 students, 20 teachers and more than 50 variables for each level, the student level and the teacher level. Half of the teachers were in an experimental condition, teaching a new type of class, called Humanitas, the other half taught history in a traditional way, and served as the control group in twelve schools in Los Angeles county.The statistical models used in this chapter can be described as (1) a data reduction model, where several observed variables are combined into a single scale, (2) a regression model for multilevel data, with a single dependent variable, and (3) a model for multilevel multivariate analysis. One of the conclusions of this chapter is that researchers should have a certain amount of knowledge of how the data are generated regarding the important relationships between the variables, before choosing a complicated model. It is advisable to explore the data, guided by a theoretical model, before fitting complicated hierarchical bilevel path models with latent variables.Above statements are in support of Rubin's statement (1991, p. 306): “that complicated analyses are often necessary in complicated problems, but unless their conclusions can be represented in clear summaries that can be supported by the real data and the observations in the field, they should not be trusted. Too often, the results of complicated analyses are summarized without making clear how the conclusions are consistent with the raw data”. The multilevel analyses in this chapter are such complicated analysis tools. The data are experimental data, collected under close observation by the researchers. The knowledge gained from the complicated data analysis is supported by observations, interviews and simple exploratory data analysis. The positive effect, on students and teachers, of an experimental curriculum in ten secondary high schools is revealed by multilevel path analysis with latent variables.     

A multilevel analysis of Japanese middle school student and school socioeconomic status influence on mathematics achievement

The author examined the simultaneous influence of Japanese middle school student and school socioeconomic status (SES) on student math achievement with two-level multilevel analysis models by utilizing the Trends in International Mathematics and Science Study (TIMSS) Japan data sets. The theoretical framework used in this study was Bronfenbrenner’s bioecological theory (Bronfenbrenner and Morris 1998). The data sets contained 4,856 students from 146 public and private middle schools. The results indicated that at the student level, different aspects of student SES (i.e., number of books, the possession of computers, paternal, and maternal educational achievements) were positively related to Japanese student math achievement. At the school level, two aspects of school SES (i.e., less populated schools and economically disadvantaged schools) were negatively related to Japanese student math achievement. None of the cross-level interactions were significant, but the random effect for the computer slope was significant. Although this study found both student and school SES effects on student achievement, the proportional reduction of prediction error explained by both student and school SES were was small, meaning the residual variances at student and school levels did not capture the majority of variance explained by math achievement. The implications of theoretical framework and educational policy are discussed.     

Sample Exclusion and Student Attrition Effects in the Longitudinal Study of Middle School Mathematics Performance

Achievement data from a longitudinally matched student cohort from a large school district in the southwestern United States were analyzed to investigate sample exclusion and student attrition effects on estimates of student, school, and district mathematics performance. Use of 2- and 3-level longitudinal growth models to estimate the growth trajectories of middle school students revealed that mathematics performance differed across 2 sample conditions. Relative to the achievement outcomes associated with a sample that included all students from the longitudinal cohort, district and school achievement were generally higher and student group performance more similar in the smaller, more advantaged student sample used for district accountability reporting. Further investigation of the school performance estimates showed that cross-sample changes in student achievement outcomes were closely related to the proportion of students from special student populations who were excluded from the district accountability sample. The achievement differences and the differential patterns of association demonstrated in this study suggest that conclusions drawn about district and school performance and relationships between student characteristics and student achievement outcomes may depend to some degree on which students are included in an analytic sample. Investigators seeking to take advantage of longitudinal designs in school effectiveness research are cautioned to closely examine their data for nonrandom student attrition and document the impact of sample exclusion and student attrition effects in the research and accountability reports that are produced from longitudinal data sets.     

Are effective or meritorious schools meretricious?

Data on student achievement gain in a large urban school district during the 1984–85 school year were analyzed to identify schools with achievement consistently higher or lower than schools with similar student and school characteristics. Before calculating gain scores, students were grouped with others of the same sex, ethnicity, initial grade level, and initial achievement level. After residuals for students who were above or below similar students were summed and averaged for reading and math at each grade, school-level regression analysis was used to further control for student and school characteristics. Results indicated that schools with reading gains one standard deviation above the mean had average raw scores less than two items higher than the district average on the sixty-item reading test, while schools with math gains this large had raw scores little more than one item higher than the average on the 44-item math test. In addition, examination of data on schools with residual (combined) reading and math gain scores 1.5 or more standard deviations above the average showed that after taking account of student background information and salient school characteristics, only one elementary school among 173 and no secondary school among 71 had unusually high achievement scores. Implications are discussed regarding efforts to identify and reward meritorious schools which allegedly have improved achievement more than other similar schools.     

A longitudinal study of math achievement gains for initially low achieving students

Standardized testing has been implemented in most school districts as part of an effort to improve student achievement in mathematics, reading, science, and English. There have been heated debates as to the effects of these improvement efforts on student achievement. In studying these issues, it is important to examine longitudinal growth patterns for individuals. In most of the studies, however, there is a lack of empirical data at the individual student level or the studies are cross-sectional in nature. The current study attempts to examine growth patterns of student math achievement between 1997 and 2000 and individual differences in growth patterns. MDS exploratory growth modeling was used in the investigation based on data from 716 students in a single school district. Individual differences in growth rates were found. Disadvantaged (limited English proficiency and special education) students had lower initial achievement levels and did not seem to be catching up to other students because their average growth rates were similar to those of other students. These results are discussed in light of recent school reform efforts and the goal of closing achievement gaps.     

The size,stability, and consistency of school effects: evidence from Victoria

The bulk of public debate on education focuses on schools and school differences. Ideally, the characteristics of schools that add value to student performance can be identified and implemented for other schools. However, such scenarios assume that school effects are sizable, stable across cohorts, and consistent across subject areas. This study tests these assumptions by analysing school effects in both primary and secondary schools in 5 achievement domains with administrative data from almost all government school students in Victoria, Australia. Gross school effects are reasonably large but show only moderate stability. However, in net progress models which control for prior achievement, school effects are substantially smaller, display only low levels of stability across cohorts, and are not consistent across achievement domains. Therefore, it is difficult to identify schools that consistently increase (or decrease) student performance across subject areas beyond that expected by students’ intake characteristics, most notably prior student performance. Other policy goals are recommended.     

Using computer-assisted instruction to enhance achievement of English language learners

Computer-assisted instruction (CAI) in English-Language environments offer practice time, motivates students, enhance student learning, increase authentic materials that students can study, and has the potential to encourage teamwork between students. The findings from this particular study suggested that students who used computer assisted program had a greater chance of closing achievement gap and meeting NCLB requirements than those students who did not use computer-assisted instruction. Additionally, the students that used computer-assisted classroom instruction gained scores in reading and math. Based on these findings, teachers, school administrators, and other educational stakeholder should explore strategies for technology integration to close the achievement gap.     

Schools, school quality and achievement growth: Evidence from the Philippines

A broad literature seeks to assess the importance of schools, proxies for school quality, and family background on children's achievement growth using the education production function. Using rich data from the Philippines, we introduce and estimate a model that imposes little structure on the relationship between intake achievement and follow-up achievement and evaluate school performance based on this estimated relationship. Our methods nest typical value-added specifications that use test score gains as the outcome variable and models assuming linearity in the relationship between intake and follow-up scores. We find evidence against the use of value-added models for our data and show that such models give very different assessments of school performance in the Philippines. Using a variety of tests we find that schools matter in the production of student achievement, though variation in performance across schools only explains about 4.4–5.3% of the total (conditional) variation in follow-up achievement. Schools providing basic facilities—in particular schools providing electricity—are found to perform much better in the production of achievement growth.     

Understanding achievement differences between schools in Ireland – can existing data-sets help?

Recent years have seen an increased focus on school accountability in Ireland and calls for greater use to be made of student achievement data for monitoring student outcomes. In this paper, it is argued that existing data-sets in Ireland offer limited potential for the value-added modelling approaches used for accountability purposes in many other countries. Some reasons for this include: few longitudinal studies of student achievement, few population data-sets and limited data on student home background in the State examination data-sets. A cross-sectional contextualised attainment model (CAM) is presented using Junior Certificate data from 2009. While the model offers some potential for identifying schools performing significantly above or below average, its explanatory power is limited by the availability of appropriate student background data. It is proposed that the use of statistical models for the purposes of identifying high or low performing schools in Ireland would need to take account of findings from other countries regarding technical difficulties such as variable selection, missing data, and the need to avoid aggregated data. Other practical concerns discussed include the appropriateness of publishing league tables and the usefulness of such information for informing parental choice.     

Educational inequality in Colombia: family background,school quality and student achievement in Cartagena

This study examines the effects of family socio‐economic disadvantage and differences in school resources on student achievement in the city of Cartagena, Colombia. Using data from the ICFES and C‐600 national databases, we conduct a multilevel analysis to determine the unique contribution of school‐level factors above and beyond family background. The results from the hierarchical linear models show that while family socio‐economic background significantly affects student achievement, school composition and school resources explain as much as half of the effects of family background. More specifically, the achievement gap in public schools is explained in large part by differential resource allocation and concentration of poor students in public schools, which in turn lowers student achievement.     

The Sensitivity of Value-Added Teacher Effect Estimates to Different Mathematics Achievement Measures

Using longitudinal data from a cohort of middle school students from a large school district, we estimate separate "value-added" teacher effects for two subscales of a mathematics assessment under a variety of statistical models varying in form and degree of control for student background characteristics. We find that the variation in estimated effects resulting from the different mathematics achievement measures is large relative to variation resulting from choices about model specification, and that the variation within teachers across achievement measures is larger than the variation across teachers. These results suggest that conclusions about individual teachers' performance based on value-added models can be sensitive to the ways in which student achievement is measured.     

Measuring the effect of charter schools on public school student achievement in an urban environment: Evidence from New York City

This paper uses student level data from New York City to study the relationship between a public school losing enrollment to charter school competitors and the academic achievement of students who remain enrolled in it. Geographic measures most often used to study the effect of school choice policies on public school student achievement are not well suited for densely populated urban environments. I adopt a direct approach and measure charter school exposure as the percentage of a public school's students who exited for a charter school at the end of the previous year. Depending on model specification, I find evidence that students in schools losing more students to charter schools either are unaffected by the competitive pressures of the choice option or benefit mildly in both math and English.     

ICT use in mathematics lessons and the mathematics achievement of secondary school students by international comparison: Which role do school level factors play?

By means of an international comparison, the research presented in the article aims to identify supporting and hindering school level factors for the use of ICT in secondary school mathematics lessons. The relationship between ICT use and the performance of Grade 9 students in mathematics is examined and further integrated into a multi-level model including school level factors. Against the background of a theoretical allocation (1) the IT equipment of schools, (2) school leadership, (3) aspects of school goals and educational strategies as well as (4) teachers’ attitudes will be analyzed by means of a multi-level regression model as well as a multi-level path model including the mathematics achievement of students as measured in the context of PISA 2012. Representative school and student data from five countries, namely Australia, Germany, the Netherlands, Norway and Singapore are taken into consideration, as the integration of ICT in teaching and learning is firmly emphasized in these countries (overall 24,579 students in 1263 schools). By modeling the complex structure, school characteristics are examined with respect to their effect on the use of ICT for mathematics teaching. Moreover, the relation between different factors and students’ mathematics achievement will be synchronously assessed in the different educational systems. The results show that characteristics at school level do play a major role in the integration of ICT into teaching and learning and turn out to be relevant across the educational systems. In addition to further in-depth country-specific findings, the results point to cross-national future challenges in the field of using technologies to enhance teaching and learning.     

农村学校布局调整对学生成绩的影响——基于两水平增值模型的分析

文章使用＂西发项目＂广西壮族自治区的面板数据考察农村小学布局调整对学生成绩的影响,对比两水平增值模型和OLS估计结果发现,学校布局调整整体上对小学生成绩具有负向影响,对语文成绩的影响尤为显著。学校办学条件、生均寄宿面积、学校满意度对学生成绩有正向影响,寄宿生的成绩略低于非寄宿生,家校距离、家庭经济负担、学校配套设施不健全、学校心理疏导缺失等因素对学生成绩产生负向影响,这种负向影响已经超出了学校办学条件等因素对学生成绩的正向影响。在实证研究的基础上,文章提出布局调整过程中,在改善办学条件的同时,应当做好硬件配套设施和软件环境的建设,保障相关财政投入,加强监督,以实现提高教育质量的目标。

Abstract：

This paper use the panel data of BEWAP to study the effect of layout adjustment of schools on student achievement in primary school of rural area in Guangxi Zhuang autonomous region.By the comparisons of two-level value-added model and OLS estimation results,the research shows that the layout adjustment policy generally has a negative effect on primary school students＇ achievement,especially on the language achievement.Specifically,the factors of school condition,dormitory area per-student and degree of school satisfaction have positive impacts on student achievement,the achievement of resident student slightly lower than non-resident student.The factors of farther home-school distance,more financial burden of families,inadequate supporting facilities of schools and the absence of psychological or other assistance have negative impacts on students＇ achievement,which are higher than the policy＇s positive effects.Based on the empirical study,this research suggests that the government should construct better hardware establishment and software condition while the improvement of school condition in the process of layout adjustment,ensure relevant financial input and enhance supervision so as to realize the goal of improving education quality.     

The impacts of student-, teacher- and school-level factors on mathematics achievement: an exploratory comparative investigation of Singaporean students and the USA students

Reports from the Trends in International Mathematics and Science Study (TIMSS) consistently show that there is a substantial gap in average mathematics achievement between Singapore and the USA. This study conducts an exploratory comparative investigation on the multilevel factors influencing the mathematics achievement of students from these two countries. A conceptual framework together with an integrated model is proposed for the analysis. The TIMSS 2011 eighth grader mathematics data were chosen for this study. Results reveal that the common features influencing mathematics achievement for the students of both countries are student self-confidence, school composition by student background and teacher confidence in teaching mathematics. The cause of the different effects of American students’ mathematics achievement is more associated with resources, whereas the effects of Singaporean students’ mathematics achievement are more related to attitudes, expectations and motivations. The major elements that affect Singaporean student mathematics performances are at the teacher level. Suggestions for future research are discussed.     

The relationship between approaches to teaching and approaches to studying: a two-level structural equation model for biology achievement in high school

Since the 1970s, a large body of research has reported on the differences between deep and surface approaches to student learning. More recently, however, this metaphor for students’ approaches to learning has been applied to the practice of teaching. Studies at the university level have identified two approaches to teaching: the information transmission/teacher-focused approach and the conceptual change/student-focused approach. The present study analyzes the relationship between teachers’ approaches to teaching and high school students’ approaches to learning. The data were analyzed by fitting a two-level structural equation model based on the hypothesis that student academic achievement is significantly determined by the way they study and that the way they study is partially determined by the way teachers teach. The participants were high school students (778 twelfth graders) enrolled in biology courses and their teachers (40 total). The same model was proposed at both levels (i.e., within and between levels) and fit the data quite well. As expected, within level, the effects of the ‘approaches to learning’ on ‘biology achievement’ regression were far larger than the corresponding effects at between level. The central findings suggest worthy directions for future research.