Having good spatial skills strongly predicts achievement and attainment in science, technology, engineering, and mathematics fields (e.g., Shea, Lubinski, & Benbow, 2001; Wai, Lubinski, & Benbow, 2009). Improving spatial skills is therefore of both theoretical and practical importance. To determine whether and to what extent training and experience can improve these skills, we meta-analyzed 217 research studies investigating the magnitude, moderators, durability, and generalizability of training on spatial skills. After eliminating outliers, the average effect size (Hedges's g) for training relative to control was 0.47 (SE = 0.04). Training effects were stable and were not affected by delays between training and posttesting. Training also transferred to other spatial tasks that were not directly trained. We analyzed the effects of several moderators, including the presence and type of control groups, sex, age, and type of training. Additionally, we included a theoretically motivated typology of spatial skills that emphasizes 2 dimensions: intrinsic versus extrinsic and static versus dynamic (Newcombe & Shipley, in press). Finally, we consider the potential educational and policy implications of directly training spatial skills. Considered together, the results suggest that spatially enriched education could pay substantial dividends in increasing participation in mathematics, science, and engineering.
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http://dx.doi.org/10.1037/a0028446 | DOI Listing |
PLoS One
January 2025
Division of Biological Sciences, US Fish and Wildlife Southwest Regional Office, Albuquerque, New Mexico, United States of America.
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge in interpreting aerial imagery of complex environments, which may result in downstream instability of models. In this study, we present a framework for assessing annotation reliability by calculating agreement metrics for individual observers against an aggregated set of annotations generated by clustering multiple observers' observations and selecting the mode classification.
View Article and Find Full Text PDFHeliyon
January 2025
Laboratory of Social and Solidarity Economy Governance and Development (LARESSGD), Department of Economics, Faculty of Law Economics and Social Sciences, Cadi Ayyad University, Marrakech, Morocco.
Early school dropout rates in Morocco exhibit widespread spatial imbalances leading to adverse consequences. Indeed, there is thus a pressing need to investigate the factors contributing to the phenomenon. To this end, this study conducts a multivariate spatial analysis of 75 provinces in Morocco.
View Article and Find Full Text PDFEarly Hum Dev
January 2025
Department of Neonatology, Máxima Medical Center, Veldhoven, Noord-Brabant, the Netherlands.
Background: Although preterm birth is associated with deficits in both motor and cognitive functioning, the association between early motor skills and cognitive outcomes at a later age remains underexplored.
Aim: To evaluate associations between motor skills at age 5.5 and cognitive functioning at age 8.
BMC Psychol
January 2025
School of teachers education, Huzhou University, Huzhou, 313000, Zhejiang, China.
It is well established in the literature that the relation of spatial ability and the number representation, but the intrinsic relation of spatial visualization ability and number representation are not well understood. In the Current study, Chinese Preschool children (N = 200; 107 girls; Mage = 5.47years, SD = 0.
View Article and Find Full Text PDFSurg Endosc
January 2025
Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
Objectives: This study aimed to develop an automated skills assessment tool for surgical trainees using deep learning.
Background: Optimal surgical performance in robot-assisted surgery (RAS) is essential for ensuring good surgical outcomes. This requires effective training of new surgeons, which currently relies on supervision and skill assessment by experienced surgeons.
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