This article reviews the methodologies used in 76 empirical studies conducted on creative thinking in primary school education and published between 2011 and 2021. The studies were analysed for their context, foci of investigation and the methodologies used. Each study was coded and analysed quantitatively and qualitatively. The findings are…

Despite a surge of empirical work on student participation in online learning environments, the causal links between the learning-related factors and processes with the desired learning outcomes remain unexplored. This study presents a systematic literature review of approaches to model learning in Massive Open Online Courses offering an analysis…

Amid recent progress in cognitive development research, high-quality data resources are accumulating, and data sharing and secondary data analysis are becoming increasingly valuable tools. Integrative data analysis (IDA) is an exciting analytical framework that can enhance secondary data analysis in powerful ways. IDA pools item-level data across…

Baby sign language is advocated to improve children's communication development. However, the evidence to support the advantages of baby sign has been inconclusive. A systematic review was undertaken to summarize and appraise the research related to the effectiveness of symbolic gestures for typically developing, hearing infants with hearing…

Background: Accumulating data from animal and human studies indicate that the prenatal environment plays a significant role in shaping children's neurocognitive development. Clinical, epidemiologic, and basic science research suggests that two experiences relatively common in pregnancy--an unhealthy maternal diet and psychosocial…

Data collection can be the most time- and cost-intensive part of developmental research. This article describes some long-proposed but little-used research designs that have the potential to maximize data quality (reliability and validity) while minimizing research cost. In "planned missing data designs", missing data are used…

An analysis using data drawn from Nancy Bayley's Berkeley Growth Study is performed for didactic purposes to illustrate the use of structural equation modeling on a child development data set. Alternatives to standard latent factor approaches are demonstrated for use in research situations in which the subject-to-variable ratio is less than…

The Little Jiffy" consists of principal components analysis and varimax rotation of all components with eigenvalues greater than one. (DG)

Used latent class analysis to test statistically Siegler's rule assessment methodology, the number of rules needed to fit a set of data. Found that rules can be identified, that some are different from those proposed by Siegler, the correct rule is not acquired by subjects, and that the rules in the transitional period are difficult to identify.…

The methodological issue of qualitative versus quantitative research is addressed, and the argumentation of research using interview methods for research is explored. Warrants of the type that are used in arguments generating conclusions from interview data are included. (KR)

Demonstrates the use of Rasch models to assess the dimensionality of an item set across cohorts in longitudinal studies. Presents data from a study on adolescents' deductive reasoning ability showing that the same test items can be measuring qualitatively different latent traits in different subsamples or at different time points. (JPB)

More research is needed to distinguish between actual and artificial sex differences, and greater attention should be paid to individual differences, since at this point sex appears to account for very little variability in human performance. (JC)

Describes a variety of analytic tools available to address questions about development, including growth-curve methods, hierarchical regressions, and both primary and secondary data analysis of project and extant data. Demonstrates some of these techniques using extant data from two projects to examine questions about treatment efficacy and…

Uses structural equation modeling to combine traditional ideas from repeated-measures ANOVA with some traditional ideas from longitudinal factor analysis. The model describes a latent growth curve model that permits the estimation of parameters representing individual and group dynamics. (Author/RH)