Assessing the association between parents' math talk and children's math performance: A preregistered meta-analysis.

The home math environment has gained considerable attention as a potential cause of variation in children's math performance, and recent research has suggested positive associations between parents' math talk and children's mathematical performance. However, the extent to which associations reflect robust causal effects is difficult to test. In a preregistered meta-analysis, we assess the association between parents' math talk and children's math performance. Our initial search identified 24,291 potential articles. After screening, we identified 22 studies that were included in analyses (k = 280 effect sizes, n = 35,917 participants). A multilevel random effects meta-analysis was employed, finding that parents' math talk is significantly associated with children's math performance (b = 0.10, SE = 0.03, p = .002). We tested whether associations differ as a function of sample characteristics, observation context, observation length, type of math talk and math performance measured, and modeling approaches to math talk variable analysis. In addition, we tested whether associations are robust to the inclusion of strong baseline covariates and found that effects attenuated when children's domain-general and/or prior math abilities are included. We discuss plausible bounds of the effects of parents' math talk on children's mathematical performance to inform power analyses and experimental work on the impact of parents' math language on children's math learning.

Fraction Ball impact on student and teacher math talk and behavior.

We assessed the impacts of Fraction Ball-a novel suite of games combining the benefits of embodied guided play for math learning-on the math language production and behavior of students and teachers. In the Pilot Experiment, 69 fifth and sixth graders were randomly assigned to play four different Fraction Ball games or attend normal physical education class. The Efficacy Experiment was implemented to test improvements made through co-design with teachers with 160 fourth through sixth graders. Researchers observed and coded for use of math language and behavior. Playing Fraction Ball resulted in consistent increases of students' and teachers' use of fraction (SDs = 0.98-2.42) and decimal (SDs = 0.65-1.64) language and number line arithmetic, but not in whole number, spatial language, counting, instructional gesturing, questioning, and planning. We present evidence of the math language production in physical education and value added by Fraction Ball to support rational number language and arithmetic through group collaboration.

Hedges, mottes, and baileys: Causally ambiguous statistical language can increase perceived study quality and policy relevance.

There is a norm in psychology to use causally ambiguous statistical language, rather than straightforward causal language, when describing methods and results of nonexperimental studies. However, causally ambiguous language may inhibit a critical examination of the study's causal assumptions and lead to a greater acceptance of policy recommendations that rely on causal interpretations of nonexperimental findings. In a preregistered experiment, 142 psychology faculty, postdocs, and doctoral students (54% female), ages 22-67 (M = 33.20, SD = 8.96), rated the design and analysis from hypothetical studies with causally ambiguous statistical language as of higher quality (by .34-.80 SD) and as similarly or more supportive (by .16-.27 SD) of policy recommendations than studies described in straightforward causal language. Thus, using statistical rather than causal language to describe nonexperimental findings did not decrease, and may have increased, perceived support for implicitly causal conclusions.

"You did a great job building that!" Links between parent-child prosocial talk and spatial language.

We investigated the extent to which parents' prosocial talk and negations relate to the quantity and diversity of parents' spatial language production. We also examined similar associations among children. Participants included 51 children of ages 4-7 years and their parents recruited from South Florida. Most of the dyads included mothers and were Hispanic and bilingual. Dyads constructed a Lego house for 10 min. Sessions were transcribed and coded for instances of parent prosocial talk (praises, reflective statements, and behavior descriptions), child general positive statements (all positive contributions to the interaction), and parent and child negations (criticisms, corrections, and disapprovals) using the Dyadic Parent-Child Interaction Coding System. Transcripts were also coded for quantity and diversity of spatial language including shape terms (e.g., square), dimensional adjectives (e.g., little), orientations (e.g., turn), locations (e.g., middle), and spatial features/properties (e.g., edge). Parents' prosocial language, but not negations, were significantly associated with the quantity and diversity of parents' spatial language. Children's general positive statements were significantly associated with children's spatial language quantity. Exploratory data analyses also revealed significant associations between parent-child talk about shapes, dimensions, and spatial features and properties. Findings suggest that variability in parent-child prosocial and spatial talk during collaborative spatial play relates to aspects of their own-and each other's-spatial language production. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Design and Analytic Features for Reducing Biases in Skill-Building Intervention Impact Forecasts.

Despite policy relevance, longer-term evaluations of educational interventions are relatively rare. A common approach to this problem has been to rely on longitudinal research to determine targets for intervention by looking at the correlation between children's early skills (e.g., preschool numeracy) and medium-term outcomes (e.g., first-grade math achievement). However, this approach has sometimes over-or under-predicted the long-term effects (e.g., 5th-grade math achievement) of successfully improving early math skills. Using a within-study comparison design, we assess various approaches to forecasting medium-term impacts of early math skill-building interventions. The most accurate forecasts were obtained when including comprehensive baseline controls and using a combination of conceptually proximal and distal short-term outcomes (in the nonexperimental longitudinal data). Researchers can use our approach to establish a set of designs and analyses to predict the impacts of their interventions up to two years post-treatment. The approach can also be applied to power analyses, model checking, and theory revisions to understand mechanisms contributing to medium-term outcomes.

Triangulating on developmental models with a combination of experimental and nonexperimental estimates.

Plausible competing developmental models show similar or identical structural equation modeling model fit indices, despite making very different causal predictions. One way to help address this problem is incorporating outside information into selecting among models. This study attempted to select among developmental models of children's early mathematical skills by incorporating information about the extent to which models forecast the longitudinal pattern of causal impacts of early math interventions. We tested for the usefulness and validity of the approach by applying it to data from three randomized controlled trials of early math interventions with longitudinal follow-up assessments in the United States (Ns = 1,375, 591, 744; baseline age 4.3, 6.5, 4.4; 17%-69% Black). We found that, across data sets, (a) some models consistently outperformed other models at forecasting later experimental impacts, (b) traditional statistical fit indices were not strongly related to causal fit as indexed by models' accuracy at forecasting later experimental impacts, and (c) models showed consistent patterns of similarity and discrepancy between statistical fit and models' effectiveness at forecasting experimental impacts. We highlight the importance of triangulation and call for more comparisons of experimental and nonexperimental estimates for choosing among developmental models. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Spatial anxiety mediates the sex difference in adult mental rotation test performance.

Mental rotation ability is associated with successful advances in STEM (science, technology, engineering, and mathematics) education and occupations. Meta-analyses have shown consistent sex disparities in mental rotation, where men outperform women on one measure of mental rotation ability, the Mental Rotations Test (MRT). Spatial anxiety, or the fear and apprehension felt when completing a task that requires spatial thinking, was proposed as a mechanism explaining the relation between sex and mental rotation test performance. This study modified the Spatial Anxiety Scale (SAS) to include questions about how anxious individuals feel when they must mentally rotate items to accomplish a task (e.g., playing Tetris). An exploratory factor analysis was conducted to assess the factorial structure of the modified spatial anxiety scale. Three factor loadings were extracted representing the ability to navigate, mentally rotate objects, and visualize objects. Furthermore, we analyzed the role of spatial anxiety and trait anxiety as potential mediators of the relation between participant sex and mental rotation performance. Spatial anxiety partially mediated the link between the sex of the participants and the MRT performance controlling for trait anxiety. Only navigation and mental rotation anxiety significantly mediated the relation between participant sex and mental rotation performance. We posit spatial anxiety as a barrier to efficient and accurate spatial thinking, and suggest that reducing spatial anxiety has the potential to improve spatial skills and reduce sex differences in mental rotation test performance. To ascertain this, an experimental design can determine whether a reduction in spatial anxiety causes changes in mental rotation test scores.

Complementarities between Early Educational Intervention and Later Educational Quality? A Systematic Review of the Sustaining Environments Hypothesis.

The sustaining environments hypothesis refers to the popular idea, stemming from theories in developmental, cognitive, and educational psychology, that the long-term success of early educational interventions is contingent on the quality of the subsequent learning environment. Several studies have investigated whether specific kindergarten classroom and other elementary school factors account for patterns of persistence and fadeout of early educational interventions. These analyses focus on the statistical interaction between an early educational intervention - usually whether the child attended preschool - and several measures of the quality of the subsequent educational environment. The key prediction of the sustaining environments hypothesis is a positive interaction between these two variables. To quantify the strength of the evidence for such effects, we meta-analyze existing studies that have attempted to estimate interactions between preschool and later educational quality in the United States. We then attempt to establish the consistency of the direction and a plausible range of estimates of the interaction between preschool attendance and subsequent educational quality by using a specification curve analysis in a large, nationally representative dataset that has been used in several recent studies of the sustaining environments hypothesis. The meta-analysis yields small positive interaction estimates ranging from approximately .00 to .04, depending on the specification. The specification curve analyses yield interaction estimates of approximately 0. Results suggest that the current mix of methods used to test the sustaining environments hypothesis cannot reliably detect realistically sized effects. Our recommendations are to combine large sample sizes with strong causal identification strategies, and to study combinations of interventions that have a strong probability of showing large main effects.