Early mathematics knowledge is a strong predictor of later academic achievement, but children from low-income families enter school with weak mathematics knowledge. An early math trajectories model is proposed and evaluated within a longitudinal study of 517 low-income American children from ages 4 to 11. This model includes a broad range of math topics, as well as potential pathways from preschool to middle grades mathematics achievement. In preschool, nonsymbolic quantity, counting, and patterning knowledge predicted fifth-grade mathematics achievement. By the end of first grade, symbolic mapping, calculation, and patterning knowledge were the important predictors. Furthermore, the first-grade predictors mediated the relation between preschool math knowledge and fifth-grade mathematics achievement. Findings support the early math trajectories model among low-income children.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/cdev.12662 | DOI Listing |
Biom J
February 2025
MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
There is a growing interest in the implementation of platform trials, which provide the flexibility to incorporate new treatment arms during the trial and the ability to halt treatments early based on lack of benefit or observed superiority. In such trials, it can be important to ensure that error rates are controlled. This paper introduces a multi-stage design that enables the addition of new treatment arms, at any point, in a preplanned manner within a platform trial, while still maintaining control over the family-wise error rate.
View Article and Find Full Text PDFBMC Bioinformatics
December 2024
Institute for the Advanced Study of Human Biology, Kyoto University Institute for Advanced Study, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan.
Background: Time-series scRNA-seq data have opened a door to elucidate cell differentiation, and in this context, the optimal transport theory has been attracting much attention. However, there remain critical issues in interpretability and computational cost.
Results: We present scEGOT, a comprehensive framework for single-cell trajectory inference, as a generative model with high interpretability and low computational cost.
Mol Cell Probes
December 2024
Institute of Clinical and Translational Research, Biomedical Research Center of the Slovak Academy of Sciences, Bratislava, Slovakia; Comenius University Science Park, Bratislava, Slovakia; Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Bratislava, Slovakia; G2 Consulting Slovakia Ltd., Slovakia. Electronic address:
Myotonic dystrophy type 1 (DM1) is a serious multisystem disorder caused by GCA repeat expansions in the DMPK gene. Early and accurate diagnosis, often requiring reliable DNA-diagnostic techniques, is critical for preventing life-threatening cardiac complications. Clinically, two main diagnostic challenges exist.
View Article and Find Full Text PDFLancet Digit Health
December 2024
Infectious Disease Epidemiology and Dynamics, London School of Hygiene and Tropical Medicine, London, UK.
Since the COVID-19 pandemic, considerable advances have been made to improve epidemic preparedness by accelerating diagnostics, therapeutics, and vaccine development. However, we argue that it is crucial to make equivalent efforts in the field of outbreak analytics to help ensure reliable, evidence-based decision making. To explore the challenges and key priorities in the field of outbreak analytics, the Epiverse-TRACE initiative brought together a multidisciplinary group of experts, including field epidemiologists, data scientists, academics, and software engineers from public health institutions across multiple countries.
View Article and Find Full Text PDFCBE Life Sci Educ
March 2025
Joint Doctoral Program in Math and Science Education, University of California, San Diego and San Diego State University, La Jolla, CA 92093.
Introductory biology is a gateway course for majors and other science, technology, engineering, and mathematics (STEM) disciplines. Despite the importance of chemistry content knowledge for understanding biology, the relationship between chemistry knowledge and prior coursework and biology course performance is understudied. We used an opportunity gap framework to investigate the extent to which there were opportunity gaps in prior chemistry coursework and knowledge and associated these gaps with subsequent equity gaps in student performance on introductory biology assessments.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!