Australia's economic need for innovation has led to Science, Technology, Engineering and Mathematics (STEM) education becoming an essential investment for the future. This study utilised a mixed-methods approach involving a pre-validated quantitative questionnaire together with qualitative semi-structured focus groups with students across four Year 5 classrooms. Students provided their perceptions of their STEM learning environment and their interactions with their teacher to identify factors influencing their engagement for pursuing these disciplines. The questionnaire comprised of scales from three different instruments: Classroom Emotional Climate, Test of Science Related Attitudes, and Questionnaire on Teacher Interaction. Several key factors were identified through student responses, including Student Freedom, Peer Collaboration, Problem Solving, Communication, Time, and Preferred Environments. 33 out of possible 40 correlations between scales were statistically significant, but eta values were considered low (0.12-0.37). Overall, the students expressed positive perceptions about their STEM learning environment, with Student Freedom, Peer Collaboration, Problem Solving, Communication and Time appearing to impact their perceptions of STEM education. Three focus groups with a total of 12 students identified suggestions for improving STEM learning environments. Implications from this research include the importance of considering student perceptions when measuring the quality of STEM learning environments, as well as how facets of these environments can impact student attitudes towards STEM.
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http://dx.doi.org/10.1007/s10984-023-09463-z | DOI Listing |
Sci Rep
January 2025
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
For decades, Agrobacterium tumefaciens-mediated plant transformation has played an integral role in advancing fundamental and applied plant biology. The recent omnipresent emergence of synthetic biology, which relies on plant transformation to manipulate plant DNA and gene expression for novel product biosynthesis, has further propelled basic as well as applied interests in plant transformation technologies. The strong demand for a faster design-build-test-learn cycle, the essence of synthetic biology, is, however, still ill-matched with the long-standing issues of high tissue culture recalcitrance and low transformation efficiency of a wide range of plant species especially food, fiber and energy crops.
View Article and Find Full Text PDFCell Syst
December 2024
Center for Bioinformatics and Computational Medicine, Ann Arbor, MI 48109, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Program in Chemical Biology, University of Michigan, Ann Arbor, MI, USA; Rogel Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Electronic address:
While proliferating cells optimize their metabolism to produce biomass, the metabolic objectives of cells that perform non-proliferative tasks are unclear. The opposing requirements for optimizing each objective result in a trade-off that forces single cells to prioritize their metabolic needs and optimally allocate limited resources. Here, we present single-cell optimization objective and trade-off inference (SCOOTI), which infers metabolic objectives and trade-offs in biological systems by integrating bulk and single-cell omics data, using metabolic modeling and machine learning.
View Article and Find Full Text PDFGigascience
January 2025
School of Life, Health & Chemical Sciences, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK.
Background: Bioinformatics is fundamental to biomedical sciences, but its mastery presents a steep learning curve for bench biologists and clinicians. Learning to code while analyzing data is difficult. The curve may be flattened by separating these two aspects and providing intermediate steps for budding bioinformaticians.
View Article and Find Full Text PDFACS Nano
January 2025
Department of Materials Chemistry, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia.
Nanoparticulate electrocatalysts for the oxygen reduction reaction are structurally diverse materials. Scanning transmission electron microscopy (STEM) has long been the go-to tool to obtain high-quality information about their nanoscale structure. More recently, its four-dimensional modality has emerged as a tool for a comprehensive crystal structure analysis using large data sets of diffraction patterns.
View Article and Find Full Text PDFJ Transl Med
January 2025
State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, School of Medicine, Shanghai East Hospital, Tongji University, Shanghai, 200120, China.
Background: Dilated cardiomyopathy (DCM) is one of the most common causes of heart failure. Infiltration and alterations in non-cardiomyocytes of the human heart involve crucially in the occurrence of DCM and associated immunotherapeutic approaches.
Methods: We constructed a single-cell transcriptional atlas of DCM and normal patients.
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