Refine
Has Fulltext
- no (20)
Document Type
- Article (20) (remove)
Is part of the Bibliography
- yes (20) (remove)
Keywords
- intelligence (3)
- Mixed-age learning (2)
- ability differentiation (2)
- academic self-concept (2)
- age differentiation (2)
- childhood (2)
- Aptitude (1)
- Assessment (1)
- Attribution theory (1)
- Bayesian reasoning (1)
Institute
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 of intelligence refers to changes in the structure of intelligence that depend on individuals' level of general cognitive ability (ability differentiation hypothesis) or age (developmental differentiation hypothesis). The present article aimed to investigate ability differentiation, developmental differentiation, and their interaction with nonlinear factor analytic models in 2 studies. Study 1 was comprised of a nationally representative sample of 7,127 U.S. students (49.4% female; M-age = 14.51, SD = 1.42, range = 12.08-17.00) who completed the computerized adaptive version of the Armed Service Vocational Aptitude Battery. Study 2 analyzed the norming sample of the Berlin Intelligence Structure Test with 1,506 German students (44% female; M-age = 14.54, SD = 1.35, range = 10.00-18.42). Results of Study 1 supported the ability differentiation hypothesis but not the developmental differentiation hypothesis. Rather, the findings pointed to age-dedifferentiation (i.e., higher correlations between different abilities with increasing age). There was evidence for an interaction between age and ability differentiation, with greater ability differentiation found for older adolescents. Study 2 provided little evidence for ability differentiation but largely replicated the findings for age dedifferentiation and the interaction between age and ability differentiation. The present results provide insight into the complex dynamics underlying the development of intelligence structure during adolescence. Implications for the assessment of intelligence are discussed.
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.
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).
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.
Between-School Variation in Students' Achievement, Motivation, Affect, and Learning Strategies
(2017)
To plan group-randomized trials where treatment conditions are assigned to schools, researchers need design parameters that provide information about between-school differences in outcomes as well as the amount of variance that can be explained by covariates at the student (L1) and school (L2) levels. Most previous research has offered these parameters for U.S. samples and for achievement as the outcome. This paper and the online supplementary materials provide design parameters for 81 countries in three broad outcome categories (achievement, affect and motivation, and learning strategies) for domain-general and domain-specific (mathematics, reading, and science) measures. Sociodemographic characteristics were used as covariates. Data from representative samples of 15-year-old students stemmed from five cycles of the Programme for International Student Assessment (PISA; total number of students/schools: 1,905,147/70,098). Between-school differences as well as the amount of variance explained at L1 and L2 varied widely across countries and educational outcomes, demonstrating the limited generalizability of design parameters across these dimensions. The use of the design parameters to plan group-randomized trials is illustrated.
In many countries, students are asked about their perceptions of teaching in order to make decisions about the further development of teaching practices on the basis of this feedback. The stability of this measurement of teaching quality is a prerequisite for the ability to generalize the results to other teaching situations. The present study aims to expand the extant empirical body of knowledge on the effects of situational factors on the stability of students’ perceptions of teaching quality. Therefore, we investigate whether the degree of stability is moderated by three situational factors: time between assessments, subjects taught by teachers, and students’ grade levels. To this end, we analyzed data from a web-based student feedback system. The study involved 497 teachers, each of whom conducted two student surveys. We examined the differential stability of student perceptions of 16 teaching constructs that were operationalized as latent correlations between aggregated student perceptions of the same teacher’s teaching. Testing metric invariance indicated that student ratings provided measures of teaching constructs that were invariant across time, subjects, and grade levels. Stability was moderated to some extent by grade level but not by subjects taught nor time spacing between surveys. The results provide evidence of the extent to which situational factors may affect the stability of student perceptions of teaching constructs. The generalizability of the students’ feedback results to other teaching situations is discussed.
The present study examines how historical changes in the U.S. socioeconomic environment in the 20th century may have affected core assumptions of the "American Dream." Specifically, the authors examined whether such changes modulated the extent to which adolescents' intelligence (IQ), their grade point average (GPA), and their parents' socioeconomic status (SES) could predict key life outcomes in adulthood about 20 years later. The data stemmed from two representative U.S. birth cohorts of 15- and 16-year-olds who were born in the early 1960s (N = 3,040) and 1980s (N = 3,524) and who participated in the National Longitudinal Surveys of Youth (NLSY). Cohort differences were analyzed with respect to differences in average relations by means of multiple and logistic regression and for specific points in each outcome distribution by means of quantile regressions. In both cohorts, IQ, GPA, and parental SES predicted important educational, occupational, and health-related life-outcomes about 20 years later. Across historical time, the predictive utility of adolescent IQ and parental SES remained stable for the most part. Yet, the combined effects of social-ecological and socioeconomic changes may have increased the predictive utility (that is, the regression weights) of adolescent GPA for educational, occupational, and health outcomes over time for individuals who were born in the 1980s. Theoretical implications concerning adult development, aging, and late life inequality are discussed. (PsycINFO Database Record.
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.
Low-achieving students are at risk of experiencing a pattern of emotional, motivational, and cognitive deficits called school-related helplessness if they attribute their low achievement to low aptitude. Teachers' beliefs about the causes of students' low achievement are important sources of attributional information for students. In a sample of 2117 German ninth-graders attending the lowest track, 118 math and 129 German-language teachers, we tested whether teachers' beliefs about the extent to which aptitude causes achievement moderated the achievement-helplessness relation in students and whether there were differences between math and German. Multilevel analyses revealed that low prior achievement predicted higher helplessness in both subjects but the effect was stronger in math than in German. Teachers' beliefs amplified the achievement-helplessness relation in math but not in German. Results are discussed regarding domain-specific epistemological beliefs, and implications for research and practice are derived.