Interest in science and math plays an important role in encouraging STEM motivation and career aspirations. This interest decreases for girls between late childhood and adolescence. Relatedly, positive mentoring experiences with female teachers can protect girls against losing interest. The present study examines whether visitors to informal science learning sites (ISLS; science centers, zoos, and aquariums) differ in their expressed science and math interest, as well as their science and math stereotypes following an interaction with either a male or female educator. Participants ( = 364; early childhood, = 151, = 6.73; late childhood, = 136, = 10.01; adolescence, = 59, = 13.92) were visitors to one of four ISLS in the United States and United Kingdom. Following an interaction with a male or female educator, they reported their math and science interest and responded to math and science gender stereotype measures. Female participants reported greater interest in math following an interaction with a female educator, compared to when they interacted with a male educator. In turn, female participants who interacted with a female educator were less likely to report male-biased math gender stereotypes. Self-reported science interest did not differ as a function of educator gender. Together these findings suggest that, when aiming to encourage STEM interest and challenge gender stereotypes in informal settings, we must consider the importance of the gender of educators and learners.
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http://dx.doi.org/10.3389/fpsyg.2021.503237 | DOI Listing |
Curr Biol
December 2024
Durrell Institute of Conservation and Ecology, University of Kent, Canterbury CT2 7NR, UK.
Conservation initiatives strive for reliable and cost-effective species monitoring. However, resource constraints mean management decisions are overly reliant on data derived from single methodologies, resulting in taxonomic or geographic biases. We introduce a data integration framework to optimize species monitoring in terms of spatial representation, the reliability of biodiversity metrics, and the cost of implementation, focusing on tigers and their principal prey (sambar deer and wild pigs).
View Article and Find Full Text PDFBioorg Chem
January 2025
Department of Chemistry, Faculty of Sciences and Mathematics, University of Niš, Višegradska 33, 18000 Niš, Serbia. Electronic address:
Numerous compounds with useful biological activities were previously prepared by tethering ferrocene to natural product scaffolds. Some conjugates of ferrocene and steroids in particular were demonstrated to act as both potent and selective antiproliferative agents. Motivated by a lack of structural diversity in the pregnane series of conjugates, we performed chemical modifications of several naturally occurring progestogens, their biosynthetic precursors and chemically related derivatives so as to obtain conjugates 1-8, in which the steroid skeleton and ferrocene core are linked by the steroid sidechain.
View Article and Find Full Text PDFFront Plant Sci
December 2024
Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha, China.
Bacterial canker is a devastating disease in kiwifruit production, primarily caused by pv. . In this study, a strain of named JIN4, isolated from a kiwifruit branch, showed antagonistic activity.
View Article and Find Full Text PDFFront Behav Neurosci
December 2024
Department of Mathematics, University of Texas at Arlington, Arlington, TX, United States.
Introduction: Sustaining attention is a notoriously difficult task as shown in a recent experiment where reaction times (RTs) and pupillometry data were recorded from 350 subjects in a 30-min vigilance task. Subjects were also presented with different types of goal, feedback, and reward.
Methods: In this study, we revisit this experimental data and solve three families of machine learning problems: (i) RT-regression problems, to predict subjects' RTs using all available data, (ii) RT-classification problems, to classify responses more broadly as attentive, semi-attentive, and inattentive, and (iii) to predict the subjects' experimental conditions from physiological data.
Small Methods
January 2025
Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong SAR, 999077, China.
Subcellular Spatial Transcriptomics (SST) represents an innovative technology enabling researchers to investigate gene expression at the subcellular level within tissues. To comprehend the spatial architecture of a given tissue, cell segmentation plays a crucial role in attributing the measured transcripts to individual cells. However, existing cell segmentation methods for SST datasets still face challenges in accurately distinguishing cell boundaries due to the varying characteristics of SST technologies.
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