Background: Problem-solving in early and middle childhood is of high relevance for cognitive developmental research and educational support. Previous research on science problem-solving has focussed on the process and strategies of children handling challenging tasks, but less on providing insights into the cognitive network that enables science problem-solving.
Aims: In this study, we aimed to investigate whether performance in science problem-solving is mainly determined by domain-specific rule knowledge, by domain-general cognitive abilities or both.
Methods: In our study, 215 6- to 8-year-old children completed a set of three domain-specific rule knowledge tasks and three corresponding problem-solving tasks that were content-coherent, as well as a vocabulary task, and a reasoning task.
Results: Correlational and regression analyses revealed a negligible impact of domain-specific rule knowledge on corresponding problem-solving tasks. In contrast, the associations between problem-solving performance in different domains and the associations between problem-solving performance and domain-general abilities (vocabulary and reasoning) were comparably strong.
Conclusions: The findings suggest that science problem-solving in primary school children primarily relies on domain-general cognitive abilities. Implications of these findings are discussed with regard to cognitive theories and early science education.
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http://dx.doi.org/10.1111/bjep.12649 | DOI Listing |
Radiography (Lond)
January 2025
Department of Radiography, School of Allied Health Sciences, Faculty of Health Sciences and Veterinary Medicine, University of Namibia, P.O Box 13301, Windhoek, Namibia. Electronic address:
Introduction: Patient-centred care (PCC) is essential in radiography for polytrauma patients emphasising empathy, clear communication, and patient well-being. Polytrauma patients require tailored imaging approaches, often involving multiple modalities. Managing and handling these patients during imaging are key components of radiography training to develop the necessary competencies.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Cyber Science and Engineering, Liaoning University, Shenyang 110036, China.
Recently, there has been a growing interest in underground construction safety, during activities such as subway construction, underground mining, and tunnel excavation. While Internet of Things (IoT) sensors help to monitor these conditions, large-scale deployment is limited by high power needs and complex tunnel layouts, making real-time response a critical challenge. A delay-sensitive multi-sensor multi-base-station routing scheduling method is proposed for the IoT in underground mining.
View Article and Find Full Text PDFMolecules
January 2025
Department of Physics, School of Physical Science and Technology, Ningbo University, Ningbo 315211, China.
Direct methods based on iterative projection algorithms can determine protein crystal structures directly from X-ray diffraction data without prior structural information. However, traditional direct methods often converge to local minima during electron density iteration, leading to reconstruction failure. Here, we present an enhanced direct method incorporating genetic algorithms for electron density modification in real space.
View Article and Find Full Text PDFSchizophr Res
January 2025
Center for Health Technology and Services Research - Health Research Network (CINTESIS@RISE), Rua Dr. António Bernardino de Almeida 830, 844, 856, 4200-072 Porto, Portugal; Higher Nursing School of Porto, Rua Dr. António Bernardino de Almeida 830, 844, 856, 4200-072 Porto, Portugal. Electronic address:
Background: Promoting positive mental health is crucial for maintaining a healthy balance of mental well-being, both for individuals with and without mental health conditions, including schizophrenia.
Objective: To map interventions that promote positive mental health in individuals with schizophrenia.
Methods: We conducted a scoping review following Joanna Briggs Institute recommendations.
PLoS One
January 2025
Faculty of Education and Arts, Sohar University, Sohar, Oman.
Conjugate Gradient (CG) methods are widely used for solving large-scale nonlinear systems of equations arising in various real-life applications due to their efficiency in employing vector operations. However, the global convergence analysis of CG methods remains a significant challenge. In response, this study proposes scaled versions of CG parameters based on the renowned Barzilai-Borwein approach for solving convex-constrained monotone nonlinear equations.
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