Eva Van de gaer

Effects of single-sex versus co-educational classes and schools on gender differences in progress in language and mathematics achievement

In this study, the effects of single‐sex versus co‐educational classes and schools on the progress in language and mathematics of boys and girls at the end of the second year of secondary education are investigated. Data from the Longitudinaal Onderzoek Secundair Onderwijs project are used. Multilevel analyses were carried out on a sample of approximately 4000 pupils, 330 classes (190 single‐sex), 180 teachers and 50 schools (20 single‐sex). The results indicate that for boys the gender composition of the classes has more impact than the gender composition of the schools, whereas for girls the gender composition of the schools is more important. Boys make more progress for language (and not for mathematics) in co‐educational classes even after we have taken into account the selective nature of the classes. Girls, on the other hand, make more progress for mathematics (but not for language) in single‐sex than in co‐educational schools.

Tracking and the effects of school‐related attitudes on the language achievement of boys and girls

In this study we examined whether the underachievement of boys in language at the end of secondary education is related to school‐related attitudes. Data were drawn from the LOSO project, a longitudinal research project in secondary education. The results showed that there were gender differences in language achievement in favour of girls in the lower tracks, but not in the highest track. The underachievement of boys was associated with boys’ less positive relationships with teachers, less positive well‐being at school and less positive attitude towards schoolwork. Furthermore, the results showed that—in the lower tracks—boys who were the least attentive in the classroom, the least interested in learning tasks and the least motivated towards learning tasks achieved better than expected. Post‐hoc analyses revealed that these are the more intelligent boys. Possible explanations of the demotivation of the more intelligent boys in the lower tracks are discussed.

Impact of Attitudes of Peers on Language Achievement: Gender Differences

The authors examined whether gender differences in language achievement were related not only to gender differences in attitudes toward schooling but also to the attitudes toward schooling of peers (i.e., peers in classes and in schools). The authors used multilevel analysis on data compiled from a longitudinal research project in secondary education. The primary results revealed that all boys who had negative school-related attitudes were underachievers in language. Furthermore, boys were more influenced by the attitudes of their peers in classes than were girls. The attitudes of peers in schools did not affect the gender gap in language achievement.

School effects on the development of motivation toward learning tasks and the development of academic self-concept in secondary education: a multivariate latent growth curve approach

The main objective of the present study is to gain more insight into the school effects on the development of 2 noncognitive student outcomes, namely, the motivation toward learning tasks and the academic self-concept, and, more specifically, on the consistency of the school effects on these 2 outcomes. Data were drawn from the “Longitudinaal Onderzoek Secundair Onderwijs” (LOSO)-project and consisted of 2,687 students in 50 schools that were tested repeatedly at 4 different time points during secondary education (Grades 7–12). A multivariate multilevel latent growth curve model was used to analyze the data. The results showed that the school effects on the development of the noncognitive outcomes were considerable, and, more importantly, the school effects were larger on growth than on student status. Schools that were effective for the development of the motivation toward learning tasks also proved to be effective for the development of academic self-concept. However, the consistency of the school effects resulted largely from intake differences between schools.

Curriculum choice and success in the first two grades of secondary education: students, classes, or schools?

The major aim of educational effectiveness research is to examine and explain school, class, and teacher differences with respect to relevant educational criteria. Until now, in the large majority of studies, language and mathematics scores were used as a criterion. In the present study, the educational track students choose at the start of secondary education (at the age of 12) and their success in the chosen curriculum are examined in relation to primary school and classes (Grades 1 to 6). Two-level models show that students had higher aims in secondary education if they had attended primary Catholic schools and/or primary schools with high average curriculum advice. The latter schools were also highly effective with respect to achievement, and their students had a high socioeconomic status and background. Multilevel models with a cross-classified structure showed no direct long-term effects of primary schools and classes.

Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data

In the behavioral sciences, many research questions pertain to a regression problem in that one wants to predict a criterion on the basis of a number of predictors. Although in many cases, ordinary least squares regression will suffice, sometimes the prediction problem is more challenging, for three reasons: first, multiple highly collinear predictors can be available, making it difficult to grasp their mutual relations as well as their relations to the criterion. In that case, it may be very useful to reduce the predictors to a few summary variables, on which one regresses the criterion and which at the same time yields insight into the predictor structure. Second, the population under study may consist of a few unknown subgroups that are characterized by different regression models. Third, the obtained data are often hierarchically structured, with for instance, observations being nested into persons or participants within groups or countries. Although some methods have been developed that partially meet these challenges (i.e., principal covariates regression (PCovR), clusterwise regression (CR), and structural equation models), none of these methods adequately deals with all of them simultaneously. To fill this gap, we propose the principal covariates clusterwise regression (PCCR) method, which combines the key idea’s behind PCovR (de Jong & Kiers in Chemom Intell Lab Syst 14(1–3):155–164, 1992) and CR (Späth in Computing 22(4):367–373, 1979). The PCCR method is validated by means of a simulation study and by applying it to cross-cultural data regarding satisfaction with life.