Refine
Is part of the Bibliography
- yes (24)
Keywords
- intelligence (3)
- large-scale assessment (3)
- Mixed-age learning (2)
- ability differentiation (2)
- academic self-concept (2)
- affect (2)
- age differentiation (2)
- childhood (2)
- design parameters (2)
- intraclass correlation (2)
- learning styles (2)
- motivation (2)
- multilevel models (2)
- student achievement (2)
- Aptitude (1)
- Assessment (1)
- Attribution theory (1)
- Bayesian reasoning (1)
- Big Five (1)
- Domain differences (1)
- Dynamic Structural Equation Modeling (DSEM) (1)
- ESEM (1)
- Educational reform (1)
- Entwicklungsbedarf (1)
- Generalizability (1)
- Helplessness (1)
- Implementation success (1)
- Implementation von Schulreformen (1)
- Instruction (1)
- Instructional quality (1)
- Intraclass correlation (1)
- Jahrgangsübergreifendes Lernen (1)
- Linda problem (1)
- Literature review (1)
- Longitudinal analyses (1)
- Monty Hall (1)
- PISA (1)
- Primary and secondary education (1)
- Professional development (1)
- Professional identity (1)
- Programme for International Student (1)
- Reformbereitschaft (1)
- SLODR (1)
- School effectiveness (1)
- Schulinspektion (1)
- Schülerleistungen (1)
- Situation (1)
- Stability (1)
- Student perception (1)
- Student ratings (1)
- Teacher beliefs (1)
- Teacher education (1)
- Teacher educator (1)
- Teacher effectiveness (1)
- Teacher learning (1)
- Value-added modeling (1)
- Wason task (1)
- Zusammensetzung Schülerschaft hinsichtlich Erstsprache (1)
- Zusammensetzung Schülerschaft hinsichtlich Lernmittelzuzahlungsbefreiung (1)
- academic achievement (1)
- academic performance (1)
- adolescence (1)
- autoregressive wage growth (1)
- cognitive illusion (1)
- cohort differences (1)
- comparison (1)
- complex survey designs (1)
- cumulative advantage (CA) (1)
- dimensional comparisons (1)
- educational large-scale assessments (1)
- elementary school students (1)
- ethnic student composition (1)
- explained variance (1)
- factor analysis (1)
- frame of reference (1)
- grade point average (1)
- hospital problem (1)
- human capital theory (1)
- implementation of school reform (1)
- individual (1)
- instructional quality (1)
- internal/external frame-of-reference model (1)
- late (1)
- late childhood (1)
- life span research (1)
- lifespan (1)
- logical thinking (1)
- longitudinal data (1)
- machine learning (1)
- mathematics (1)
- measurement invariance (1)
- meta-analysis (1)
- model (1)
- multilevel latent (covariate) model (1)
- multitrait-multimethod (1)
- nonlinear (1)
- nonlinear relations (1)
- openness to reform (1)
- participant data (1)
- personality ratings (1)
- personality traits (1)
- power analysis (1)
- problem (1)
- reading (1)
- school composition (1)
- school effectiveness (1)
- school inspection (1)
- school quality (1)
- socioeconomic status (1)
- socioeconomic student composition (1)
- special measure (1)
- statistical reasoning (1)
- student performance (1)
- value-added modeling (1)
- wage dynamics (1)
Institute
Adults' ratings of children's personality have been found to be more closely associated with academic performance than children's self-reports. However, less is known about the relevance of the unique perspectives held by specific adult observers such as teachers and parents for explaining variance in academic performance. In this study, we applied bifactor (S-1) models for 1411 elementary school children to investigate the relative merits of teacher and parent ratings of children's personalities for academic performance above and beyond the children's self-reports. We examined these associations using standardized achievement test scores in addition to grades. We found that teachers' unique views on children's openness and conscientiousness had the strongest associations with academic performance. Parents' unique views on children's neuroticism showed incremental associations above teacher ratings or self-reports. For extraversion and agreeableness, however, children's self-reports were more strongly associated with academic performance than teacher or parent ratings. These results highlight the differential value of using multiple informants when explaining academic performance with personality traits.
To plan cluster-randomized trials with sufficient statistical power to detect intervention effects on student achievement, researchers need multilevel design parameters, including measures of between-classroom and between-school differences and the amounts of variance explained by covariates at the student, classroom, and school level. Previous research has mostly been conducted in the United States, focused on two-level designs, and limited to core achievement domains (i.e., mathematics, science, reading). Using representative data of students attending grades 1-12 from three German longitudinal large-scale assessments (3,963 <= N <= 14,640), we used three- and two-level latent (covariate) models to provide design parameters and corresponding standard errors for a broad array of domain-specific (e.g., mathematics, science, verbal skills) and domain-general (e.g., basic cognitive functions) achievement outcomes. Three covariate sets were applied comprising (a) pretest scores, (b) sociodemographic characteristics, and (c) their combination. Design parameters varied considerably as a function of the hierarchical level, achievement outcome, and grade level. Our findings demonstrate the need to strive for an optimal fit between design parameters and target research context. We illustrate the application of design parameters in power analyses.
Die Schulinspektion evaluiert Schulen mit dem Ziel der Qualitätssicherung von Unterrichts- und Schulqualität.
Dies gilt insbesondere für Schulen, an denen „erheblicher Entwicklungsbedarf“ festgestellt wurde.
Diese Schulen bekommen zusätzliche Unterstützung, erfahren aber auch zusätzlichen Druck durch diese Einordnung.
Die weitere Entwicklung dieser Schulen ist bisher kaum erforscht. Diese Studie untersucht mit Daten der Schulinspektion, der amtlichen Statistik und Leistungsdaten von 333 Berliner Grundschulen Veränderungen in Indikatoren der Unterrichts- und Schulqualität, der Schulleistung, und der Zusammensetzung der Schülerschaft (SES und Anteil mit nicht-deutscher Herkunftssprache) nach der Diagnose „erheblicher Entwicklungsbedarf“.
Die empirischen Analysen zeigten, dass sich bei diesen Schulen die Unterrichts- und Schulqualität nur geringfügig veränderte, sich der Leistungsabstand zu allen anderen Grundschulen nicht statistisch signifikant verringerte, und sich die Zusammensetzung der Schülerschaft hinsichtlich des sozioökonomischen Status (SES) nicht veränderte. Jedoch erhöhte sich der Anteil von Kindern mit nicht-deutscher Herkunftssprache statistisch signifikant.
Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences.
Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational large-scale assessments (ELSAs) or social, health, and economic survey and panel studies. The meta-analytic integration of these results offers unique and novel research opportunities to provide strong empirical evidence of the consistency and generalizability of important phenomena and trends.
Using ELSAs as an example, this tutorial offers methodological guidance on how to use the two-stage approach to IPD meta-analysis to account for the statistical challenges of complex survey designs (e.g., sampling weights, clustered and missing IPD), first, to conduct descriptive analyses (Stage 1), and second, to integrate results with three-level meta-analytic and meta-regression models to take into account dependencies among effect sizes (Stage 2).
The two-stage approach is illustrated with IPD on reading achievement from the Programme for International Student Assessment (PISA). We demonstrate how to analyze and integrate standardized mean differences (e.g., gender differences), correlations (e.g., with students' socioeconomic status [SES]), and interactions between individual characteristics at the participant level (e.g., the interaction between gender and SES) across several PISA cycles.
All the datafiles and R scripts we used are available online. Because complex social, health, or economic survey and panel studies share many methodological features with ELSAs, the guidance offered in this tutorial is also helpful for synthesizing research evidence from these studies.
In the present paper we empirically investigate the psychometric properties of some of the most famous statistical and logical cognitive illusions from the "heuristics and biases" research program by Daniel Kahneman and Amos Tversky, who nearly 50 years ago introduced fascinating brain teasers such as the famous Linda problem, the Wason card selection task, and so-called Bayesian reasoning problems (e.g., the mammography task). In the meantime, a great number of articles has been published that empirically examine single cognitive illusions, theoretically explaining people's faulty thinking, or proposing and experimentally implementing measures to foster insight and to make these problems accessible to the human mind. Yet these problems have thus far usually been empirically analyzed on an individual-item level only (e.g., by experimentally comparing participants' performance on various versions of one of these problems). In this paper, by contrast, we examine these illusions as a group and look at the ability to solve them as a psychological construct. Based on an sample of N = 2,643 Luxembourgian school students of age 16-18 we investigate the internal psychometric structure of these illusions (i.e., Are they substantially correlated? Do they form a reflexive or a formative construct?), their connection to related constructs (e.g., Are they distinguishable from intelligence or mathematical competence in a confirmatory factor analysis?), and the question of which of a person's abilities can predict the correct solution of these brain teasers (by means of a regression analysis).
It is well-documented that academic achievement is associated with students' self-perceptions of their academic abilities, that is, their academic self-concepts. However, low-achieving students may apply self-protective strategies to maintain a favorable academic self-concept when evaluating their academic abilities. Consequently, the relation between achievement and academic self-concept might not be linear across the entire achievement continuum. Capitalizing on representative data from three large-scale assessments (i.e., TIMSS, PIRLS, PISA; N = 470,804), we conducted an integrative data analysis to address nonlinear trends in the relations between achievement and the corresponding self-concepts in mathematics and the verbal domain across 13 countries and 2 age groups (i.e., elementary and secondary school students). Polynomial and interrupted regression analyses showed nonlinear relations in secondary school students, demonstrating that the relations between achievement and the corresponding self-concepts were weaker for lower achieving students than for higher achieving students. Nonlinear effects were also present in younger students, but the pattern of results was rather heterogeneous. We discuss implications for theory as well as for the assessment and interpretation of self-concept.
Wages and wage dynamics directly affect individuals' and families' daily lives. In this article, we show how major theoretical branches of research on wages and inequality-that is, cumulative advantage (CA), human capital theory, and the lifespan perspective-can be integrated into a coherent statistical framework and analyzed with multilevel dynamic structural equation modeling (DSEM). This opens up a new way to empirically investigate the mechanisms that drive growing inequality over time. We demonstrate the new approach by making use of longitudinal, representative U.S. data (NLSY-79). Analyses revealed fundamental between-person differences in both initial wages and autoregressive wage growth rates across the lifespan. Only 0.5% of the sample experienced a "strict" CA and unbounded wage growth, whereas most individuals revealed logarithmic wage growth over time. Adolescent intelligence and adult educational levels explained substantial heterogeneity in both parameters. We discuss how DSEM may help researchers study CA processes and related developmental dynamics, and we highlight the extensions and limitations of the DSEM framework.
Personality is a relevant predictor for important life outcomes across the entire lifespan. Although previous studies have suggested the comparability of the measurement of the Big Five personality traits across adulthood, the generalizability to childhood is largely unknown. The present study investigated the structure of the Big Five personality traits assessed with the Big Five Inventory-SOEP Version (BFI-S; SOEP = Socio-Economic Panel) across a broad age range spanning 11-84 years. We used two samples of N = 1,090 children (52% female, M-age = 11.87) and N = 18,789 adults (53% female, M-age = 51.09), estimating a multigroup CFA analysis across four age groups (late childhood: 11-14 years; early adulthood: 17-30 years; middle adulthood: 31-60 years; late adulthood: 61-84 years). Our results indicated the comparability of the personality trait metric in terms of general factor structure, loading patterns, and the majority of intercepts across all age groups. Therefore, the findings suggest both a reliable assessment of the Big Five personality traits with the BFI-S even in late childhood and a vastly comparable metric across age groups.
Differentiation hypotheses concern changes in the structural organization of cognitive abilities that depend on the level of general intelligence (ability differentiation) or age (developmental differentiation). Part 1 of this article presents a review of the literature on ability and developmental differentiation effects in children, revealing the need for studies that examine both effects simultaneously in this age group with appropriate statistical methods. Part 2 presents an empirical study in which nonlinear factor analytic models were applied to the standardization sample (N = 2,619 German elementary schoolchildren; 48% female; age: M = 8.8 years, SD = 1.2, range 6-12 years) of the THINK 1-4 intelligence test to investigate ability differentiation, developmental differentiation, and their interaction. The sample was nationally representative regarding age, gender, urbanization, and geographic location of residence but not regarding parents' education and migration background (overrepresentation of children with more educated parents, underrepresentation of children with migration background). The results showed no consistent evidence for the presence of differentiation effects or their interaction. Instead, different patterns were observed for figural, numerical, and verbal reasoning. Implications for the construction of intelligence tests, the assessment of intelligence in children, and for theories of cognitive development are discussed.
The aim of educational policy should be to provide a good education to all students. Thus, a key question arises regarding the extent to which key characteristics of school composition (proportion of students with migration background, socioeconomic status [SES], prior school achievement, and achievement heterogeneity), instructional quality, school quality, and later school achievement are interrelated. The present study addressed this research question by examining school inspection data, official school statistics, and large-scale achievement data from all primary schools in Berlin, Germany (N = 343). The results of correlation and path analyses showed that school composition (average SES, average prior school achievement) predicted components of instructional quality (SES: classroom management, cognitive activation; achievement: cognitive activation, individual learning support). The relation between school composition characteristics and most components of school quality was close to zero. Contrary to our expectations, only the effect of school SES on later achievement was mediated by instructional quality.