A longitudinal study of how women's prenatal and postnatal concerns related to the COVID-19 pandemic predicts their infants' social–emotional development

Infant social–emotional development may be impacted by the COVID-19 pandemic. This study investigated associations between maternal pre- and postnatal pandemic-related concerns and social–emotional developmental risk. Data, collected in 2020–2021, came from 220 mothers (87% white, 6% Hispanic, 1% Black, 3% Asian, 1% American Indian, M_age = 32.46 years), and infants (53.18% male, M_age = 12.98 months) in the United States. Maternal postnatal pandemic-related concerns were associated with total risk scores (B = 6.09, p-value <.001) and offspring risk of scoring positive for problems related to inflexibility (B = 4.07, p-value = .006). The total score association was moderated by self-reported social support. Infants may be detrimentally impacted by the pandemic via maternal pandemic-related concerns. Maternal social support may buffer infants.     

Immediate Dissemination of Student Discoveries to a Model Organism Database Enhances Classroom-Based Research Experiences

Use of inquiry-based research modules in the classroom has soared over recent years, largely in response to national calls for teaching that provides experience with scientific processes and methodologies. To increase the visibility of in-class studies among interested researchers and to strengthen their impact on student learning, we have extended the typical model of inquiry-based labs to include a means for targeted dissemination of student-generated discoveries. This initiative required: 1) creating a set of research-based lab activities with the potential to yield results that a particular scientific community would find useful and 2) developing a means for immediate sharing of student-generated results. Working toward these goals, we designed guides for course-based research aimed to fulfill the need for functional annotation of the Tetrahymena thermophila genome, and developed an interactive Web database that links directly to the official Tetrahymena Genome Database for immediate, targeted dissemination of student discoveries. This combination of research via the course modules and the opportunity for students to immediately “publish” their novel results on a Web database actively used by outside scientists culminated in a motivational tool that enhanced students’ efforts to engage the scientific process and pursue additional research opportunities beyond the course.     

LEARNING IN HIGHER EDUCATION AND ITS OUTCOMES

The increasing diversity and internationalization of higher education in Europe require greater sophistication in the means of assessment of individual higher education institutions, individual units within given institutions, and learning outputs and outcomes. A short historical overview of assessment in Europe and in the United States is given followed by proposals to refine and to broaden specific aspects of evaluation. The authors suggest the development of instruments and procedures aimed at measuring learned abilities and adressing them in the context of curricula, learning environment, teaching, and learning; instruments which can measure both vertical and horizontal differences; and instruments suitable for measuring both outputs and outcomes. They further suggest a number of study design elements and conclude with a recommendation that CHER stimulate research in this crucial domain.     

MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus

MplusAutomation is a package for R that facilitates complex latent variable analyses in Mplus involving comparisons among many models and parameters. More specifically, MplusAutomation provides tools to accomplish 3 objectives: to create and manage Mplus syntax for groups of related models; to automate the estimation of many models; and to extract, aggregate, and compare fit statistics, parameter estimates, and ancillary model outputs. We provide an introduction to the package using applied examples including a large-scale simulation study. By reducing the effort required for large-scale studies, a broad goal of MplusAutomation is to support methodological developments in structural equation modeling using Mplus.     

Note on Sources of Sampling Variability in Science Performance Assessments

In 1993, we reported in Journal of Educational Measurement that task-sampling variability was the Achilles' heel of science performance assessment. To reduce measurement error, tasks needed to be stratified before sampling, sampled in large number, or possibly both. However, Cronbach, Linn, Brennan, & Haertel (1997) pointed out that a task-sampling interpretation of a large person x task variance component might be incorrect. Task and occasion sampling are confounded because tasks are typically given on only a single occasion. The person x task source of measurement error is then confounded with the pt x occasion source. If pto variability accounts for a substantial part of the commonly observed pt interaction, stratifying tasks into homogenous subsets—a cost-effective way of addressing task sampling variability—might not increase accuracy. Stratification would not address the pro source of error. Another conclusion reported in JEM was that only direct observation (DO) and notebook (NB) methods of collecting performance assessment data were exchangeable; computer simulation, short-answer, and multiple-choice methods were not. However, if Cronbach et al. were right, our exchangeability conclusion might be incorrect. After re-examining and re-analyzing data, we found support for Conbach et al. We concluded that large task-sampling variability was due to both the person x task interaction and person x task x occasion interaction. Moreover, we found that direct observation, notebook and computer simulation methods were equally exchangeable, but their exchangeability was limited by the volatility of student performances across tasks and occasions.     

The social and emotional world of gifted students: Moving beyond the label

Students who are identified as gifted have academic, social, and emotional experiences that are informed by both their cognition and their identification. Similarly, highly able students who are overlooked and remain unidentified have extra layers of social and emotional complexity to negotiate. While the label should not uniquely define the treatment of the student, this review of the literature offers some supported themes that might inform service. Research on traditional and contemporary concerns is placed in the context of conceptual and methodological limitations, concluding with recommendations for the practitioner as a beginning to the conversation.