Freshman Year Dropouts: Interactions Between Student and School Characteristics and Student Dropout Status

Data from a large school district in the southwestern United States were analyzed to investigate relations between student and school characteristics and high school freshman dropout patterns. Application of a multilevel logistic regression model to student dropout data revealed evidence of school-to-school differences in student dropout rates and school-to-school differences in the relation between student characteristics and student dropout status. Investigation of the school differences revealed that school organization and schools' social context were statistically significant predictors of several of the dropout outcomes. Evidence of school context and school practice effects on student dropout outcomes suggests that school personnel may need to consider how characteristics of the school environment interact with the background characteristics of students when developing and focusing dropout prevention strategies. Implications for school policy and practice are discussed.     

Schulformwechsel im zweigliedrigen Schulsystem

This study focuses on students who change from the academic to the non-academic school track after grade 7 (probationary year) in Berlin. We examined which individual student characteristics (e.?g., performance, school biography, family background) predict school change after the probationary year. We were particularly interested as to whether there are secondary effects of social background, after controlling for differences in performance. Our analyses were based on data from a study which included a whole cohort of school track changers (N?=?754) who were compared with students that remained at the academic track (N?=?1470). In order to predict the change of school type, multivariate logistic regression analyses were performed. Results revealed significant differences between both groups regarding all observed characteristics. Performance-related characteristics were the best predictors of track change. After controlling for these characteristics, no further significant effects for other predictors were observable (i.?e., no secondary effects of social background were present).     

Do school context,student composition and school leadership affect school practice and outcomes in secondary education?

This study examined effects of school context, student composition and school leadership on school practice and outcomes in secondary education in Flanders. The study reveals that relations between school characteristics do exist and that it is possible to explain an important part of the differences in mean effort and mathematics achievement of schools by means of these school characteristics. Furthermore, it was found that school size positively affects school outcomes and that its effect is mediated by school practice characteristics like the amount of cooperation between teachers, which affects school climate and outcomes. School leadership did not affect the school practice much, perhaps because of a lack of a strong educational leadership in most of the Flemish secondary schools. However, the student composition of schools seemed to be very important for school practice, as well as for school outcomes. Nevertheless, the study revealed that schools can affect the outcomes of their students independently of their student composition and context by means of school practice.     

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.     

Associations between school absence and academic achievement: Do socioeconomics matter?

This study examined the extent to which the association between increased student absence and lower achievement outcomes varied by student and school‐level socioeconomic characteristics. Analyses were based on the enrolment, absence and achievement records of 89,365 Year 5, 7 and 9 students attending government schools in Western Australian between 2008 and 2012. Multivariate multi‐level modelling methods were used to estimate numeracy, writing and reading outcomes based on school absence, and interactions between levels of absence and school socioeconomic index (SEI), prior achievement, gender, ethnicity, language background, parent education and occupation status. While the effects of absence on achievement were greater for previously high‐achieving students, there were few significant interactions between absence and any of the socioeconomic measures on achievement outcomes. The results of first‐difference regression models indicated that the negative effect of an increase in absence was marginally larger for students attending more advantaged schools, though most effects were very small. While students from disadvantaged schools have, on average, more absences than their advantaged peers, there is very little evidence to suggest that the effects of absence are greater for those attending lower‐SEI schools. School attendance should therefore be a priority for all schools, and not just those with high rates of absence or low average achievement.     

Variation in Effectiveness Between Private and Public Schools: The Impact of School and Family Networks*

Abstract

Building upon the assumption that cohesion between different levels of the school is essential to the schools’ effectiveness, the hypothesis is tested that a close kinship between school and parental community causes a positive effect on student outcomes in primary schools. Recent theories regarding the effects of ‘functional communities’ on academic achievement mainly focus on the characteristics of the parental community that surrounds a school. Recognizing, however, that schools differ regarding their responsiveness to the role of parents and other actors around the school, our expectation is that a definition of functional community which comprises interactions between characteristics of the parental network around the school and the governance structure of the school offers a better explanation of variation in student achievement. Based on a national sample of 90 schools for primary education in the Netherlands, our analysis shows that the differences in math achievement for public and private primary schools are mediated by characteristics at both the family and the institutional level. It also indicates that characteristics at the institutional level are conditional for the effects of parental networks around schools.

     

Assessing the impact of learning environments: How to use student ratings of classroom or school characteristics in multilevel modeling

In educational research, characteristics of the learning environment (e.g., social climate, instructional quality, goal orientation) are often assessed via student reports, and their associations with outcome variables such as school achievement or student motivation then tested. However, studying the effects of the learning environment presents a series of methodological challenges. This article discusses three crucial elements in research that uses student reports to gauge the impact of the learning environment on student outcomes. First, from a conceptual point of view, it is argued that ratings aggregated at the relevant level (e.g., class or school level), and not individual student ratings, are of primary interest in these studies. Second, the reliability of aggregated student ratings must be routinely assessed before these perceptions are related to outcome variables. Third, researchers conducting multilevel analyses need to make very clear which centering option was chosen for the predictor variables. This article shows that conclusions about the impact of learning environments can be substantially affected by the choice of a specific centering option for the individual student ratings.     

Students' Perceptions of Interpersonal Aspects of the Learning Environment

This study examined variables associated with differences in students' perceptions of interpersonal teacher behavior. The perceptions of 3023 students and 74 teachers in 168 classes in seven secondary schools were used in the analyses. Investigating variance at the student, class, teacher and school levels revealed that several variables are significantly related to students' perceptions: student and teacher gender, student and teacher ethnic background, student age and grade, class size, grade level, subject taught and teacher experience. There were interaction effects between some variables, such as student ethnicity and student gender, as well as student and teacher gender. While significant, the amount of variance explained by these was low (around 10%). The outcomes generally confirmed earlier research, although some new effects were found. Perhaps the main result of the study was its verification of the complex and interactive nature of students' perceptions of the learning environment and researchers' understanding of it.     

Effects of school quality,school citizenship policy,and student body composition on the acquisition of citizenship competences in the final year of primary education

This study examines the effects of general educational quality of schools, school citizenship policy, and ethnic homogeneity of the student body on the acquisition of citizenship competences in the final year of primary education. The theoretical framework is based on developmental, psychological, and sociological studies into effects of social context on educational outcomes and research into effective schools. The effects of school quality, school policy, and student population were analysed using 2-level (students, school) multilevel models. The results show that differences in citizenship competences between students and schools are mainly explained by factors at student level. Although the school also appeared to play a role, the school variables used in the analysis did not offer sufficient explanation for these differences. In order to further investigate the relationship between school factors and students’ citizenship, more insight is needed into characteristics of citizenship practices of schools.     

Research Findings from the Tennessee Value-Added Assessment System (TVAAS) Database: Implications for Educational Evaluation and Research

The Tennessee Value-Added Assessment System determines the effectiveness of school systems, schools, and teachers based on student academic growth over time. An integral part of TVAAS is a massive, longitudinally merged database linking students and student outcomes to the schools and systems in which they are enrolled and to the teachers to whom they are assigned as they transition from grade to grade. Research conducted utilizing data from the TVAAS database has shown that race, socioeconomic level, class size, and classroom heterogeneity are poor predictors of student academic growth. Rather, the effectiveness of the teacher is the major determinant of student academic progress. Teacher effects on student achievement have been found to be both additive and cumulative with little evidence that subsequent effective teachers can offset the effects of ineffective ones. For these reasons, a component linking teacher effectiveness to student outcomes is a necessary part of any effective educational evaluation system.     

Anti-school attitudes,school culture and friendship networks

This article explores the relationship between educational outcomes and anti-school attitudes at different levels of social organization in schools. Data were collected in St. Petersburg, Russia (104 schools, 7300 students) and analyzed using multi-level regression models that included three levels: individual, clique of friends and school. A clique is defined as a tight group of friends in a school class; we used social network analysis software Kliquefinder for clique identification. We demonstrate that friends’ attitudes are strongly related to the educational outcomes of a student (net of person’s individual attitudes and socio-demographic characteristics). In contrast, school-level effects disappear in the multi-level model when individual characteristics are included. The results of the study clearly demonstrate that the socio-economic and curricular differentiation of schools does not always lead to the polarization of ‘school academic cultures’. A school social environment is sufficiently heterogeneous, and different value systems in small peer groups may coexist.     

EQUITY IN MATHEMATICS AND SCIENCE OUTCOMES: CHARACTERISTICS ASSOCIATED WITH HIGH AND LOW ACHIEVEMENT ON PISA 2006 IN IRELAND

Equity in education is a key concern internationally; however, it is rare that this issue is examined separately for low- and high-achieving students and concurrently across different subject domains. This study examines student and school background characteristics associated with low and high achievement in mathematics and science on the Programme for International Student Assessment. Based on the results of a multilevel multinomial model of achievement for each domain, findings indicate that a greater number of the variables examined are associated with low rather than high achievement. At student level, home language, intention to leave school early, socioeconomic status, grade level, cultural capital, and books in the home are significantly associated with achievement in mathematics and science. At school level, only school average socioeconomic status is statistically significant in the models. Significant gender differences are found in the distribution of high and low achievers, which vary across the domains. In mathematics, females are more likely to be low achievers while males are more likely to be high achievers. In science, gender interacts with early school-leaving intent whereas males intending to leave school early are more likely to be in the low-achieving group than females intending to leave early. Conclusions emphasise the need for targeting resources aimed at promoting equity in outcomes at student level as well as at school level. Future work may extend the current analyses by incorporating domain-specific variables or examining cross-country differences.     

The effects of school social mix: unpacking the differences

Whether school composition makes a difference for student outcomes has been the subject of much controversy. This article draws on Growing Up in Ireland data, a rich source of information on nine-year-old children along with the characteristics of their school and classroom teacher. In contrast to many studies which rely on a single measure of social background, the use of a range of measures (including social class, parental education and income) allows us to provide precise estimates of differences in performance between schools designated as disadvantaged and other schools. The analyses also provide new insights into the processes underlying such differences. Only the most disadvantaged schools, those in Urban Band 1, are found to have a contextual effect for both reading and mathematics. This achievement gap is found to reflect differences in teacher experience and turnover, the concentration of additional learning needs, absenteeism levels and children's engagement in school.     

Generating Hypotheses and Upper-Bound Effect Sizes Using a Large Number of School Characteristics and Student Outcomes

ABSTRACT

Using a “naïve” specification, this paper estimates the relationship between 36 high school characteristics and 24 student outcomes controlling for students' pre-high school characteristics. The goal of this exploration is not to generate casual estimates, but rather to: (a) compare the size of the relationships to determine which inputs seem most promising and to identify which student outcomes appear most susceptible to being affected; (b) obtain likely upper-bound effect sizes that are useful information for power analyses used to establish minimum sample sizes for more robust designs capable of revealing causal impacts; and (c) illustrate how small effects over many outcomes (which are cumulatively important) can be easily missed. I find that most of the 36 inputs appear to have affected more outcomes than one would expect by chance, but that the apparent effects were generally small. Further, I find a higher frequency of large and significant apparent effects on educational achievement and attainment outcomes than labor market and other outcomes for young adults.     

Motivation matters? The relationship among different types of learning motivation,engagement behaviors and learning outcomes of undergraduate students in Taiwan

The purpose of this study is to understand predictors of different learning outcomes among various student background characteristics, types of learning motivation and engagement behaviors. 178 junior students were surveyed at a 4-year research university in Taiwan. The scales of motivation, engagement and perceived learning outcomes were adapted from the Motivated Strategies for Learning Questionnaire and the National Survey of Student Engagement College Student Report. Multiple hierarchical regression analysis was used in data analysis. Findings confirm that different student background characteristics and learning motivation can predict different learning outcomes. However, student engagement behaviors cannot significantly predict different types of learning outcomes when student background and learning motivation variables are included. This study also finds that student’s majors play an important role in explaining learning outcomes. Overall, the findings highlight the importance of learning motivation and suggest that instructors can provide students with more successful learning experiences to ensure more confidence in their learning abilities.     

Student engagement as a mediator of the effects of socio-economic status on academic performance among secondary school students in Australia

In this article, we contribute to understanding of the mechanisms through which students’ socio-economic family background can translate into academic performance by focusing on the concept of student engagement. Drawing on theoretical perspectives from disciplines across the social sciences, and a major nationally representative dataset from Australia, which links survey responses with administrative records on school performance, we conduct a series of multiple regression models to investigate the mediating role of student engagement on the relationship between students’ socio-economic status (SES) and academic achievement. We find that, first, low-SES students show lower levels of engagement than other students, particularly in terms of behavioural and cognitive aspects; they also have lower achievement levels as measured by standardised test scores. We further find that lower engagement is associated with lower achievement levels, and that the effects of SES on achievement are partially mediated through student engagement. Although there are clearly other mechanisms in place that operate at the same time, it is important to focus on student engagement since it can be directly influenced by teachers and school leaders, as well as curriculum choices and school resources. This makes it a ripe target for government policies aimed at improving educational outcomes for students from low-SES families, compared with approaches targeting the influences of family environment or peer groups.     

School Size Effects on Achievement in Secondary Education Evidence from the Netherlands,Sweden and the USA 1

ABSTRACT

In this article the results of an investigation into the relation between school size and achievement are reported. The findings relate to mathematics achievement in Dutch, Swedish and American secondary education and to science achievement in the Netherlands. The analyses sought to provide an answer to the following questions:

(1) Is school size related to achievement independently of student background characteristics such as sex, achievement motivation, socio‐economic status and cognitive aptitude? (2) Is the effect of school size related to any of the aforementioned background characteristics? (3) Does the effect of school size on achievement differ between the educational systems of the Netherlands, Sweden and the USA? (4) Is the effect of school size the same for different measures of student achievement (mathematics versus science)?

It was hypothesized that school size would be most strongly related to achievement in the USA. The analyses, however, revealed little empirical evidence for the existence of school size effects on achievement in any of the three countries, possibly because school size and curriculum comprehensiveness are not strongly related in these countries.

Because the investigations involved the analysis of five separate datasets, the research outcomes revealed some useful additional information with respect to the robustness of the detected relations between the five covariates and student achievement.

     

Unpacking the inequality among Turkish schools: Findings from PISA 2006

The study investigates the effects of certain school characteristics on students’ mathematics performances in Turkey in the PISA 2006 while controlling for family background and demographic characteristics. Three models of Hierarchical Linear Modeling (HLM) are constructed. The results reveal that 55% of the variance is attributable to between-schools and the remaining 45% to individual student characteristics. About two-thirds of the 55% is explained by selectivity in admissions, time to study mathematics and students’ SES, gender and the geographical region. The findings are interpreted to explain why Turkish schools differed greatly in average student performance in PISA 2006 by using the conceptual efforts on school quality factors and family background characteristics.     

Willingness to Pay and Preference for Private Institutions

This study focuses on the correlates of student preference for private institutions over public institutions in their senior year in high school, with a particular focus on the effects of students' subjective responses to tuition costs and to financial aid availability. The data for this study were drawn from a longitudinal study of postsecondary educational choice of high school students in the state of Indiana. The results indicate that in addition to student and family background and student academic characteristics, students' subjective responses to tuition costs and to financial aid availability have a substantial linkage with student preference for private or public institutions. This study suggests that family and ascribed characteristics alone do not explain student preference for the type of postsecondary institution. Students' subjective responses to tuition costs and to financial aid availability are also directly related to student preference for a certain type of postsecondary institution, independent of student family background and academic characteristics. This suggests that the willingness to pay, not only the ability to pay, plays a direct role in student college choice decisions. The implications for policy making are discussed.