Background: Physical therapy educators strive to achieve excellence in education and develop clinicians who are prepared to meet the health needs of society. Previous research has focused on describing the traits, beliefs, and experiences of exemplary educators and clinicians to inform didactic and clinical curricula and serve as a model for expert practice. However, no studies have explored the experiences and perspectives of exemplary students.
Purpose: The aim of this phenomenological study was to describe the traits, beliefs, and experiences of exemplary physical therapist (PT) students in clinical education.
Methods: A phenomenological design was utilized to gather data through semi-structured interviews with 26 students from the United States who met the criteria for exemplary and were completing their terminal clinical experience or were within six months of graduation. Data were analyzed using constant comparison and methodological rigor was maintained using an inquiry audit, peer debriefing, member checking, and pilot interviewing.
Results: A emerged as an overarching theme. The essence of being exemplary was further elucidated through the following themes: (1)
Conclusion: Given the emphasis on excellence in physical therapy education, these results can provide insights for defining the necessary qualities for achieving excellence in both classroom and clinical environments. Additionally, these findings can assist educators in fostering excellence-driven attributes among entry-level students.
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http://dx.doi.org/10.1080/09593985.2024.2376677 | DOI Listing |
Philos Trans A Math Phys Eng Sci
January 2025
Institute of Computer Science, University of Bremen, Bremen, Germany.
With the ongoing digitization, digital circuits have become increasingly present in everyday life. However, as circuits can be faulty, their verification poses a challenging but essential challenge. In contrast to formal verification techniques, simulation techniques fail to fully guarantee the correctness of a circuit.
View Article and Find Full Text PDFJ Phys Chem A
January 2025
Liaoning Key Laboratory of Manufacturing System and Logistics Optimization, Shenyang 110819, China.
Artificial intelligence technology has introduced a new research paradigm into the fields of quantum chemistry and materials science, leading to numerous studies that utilize machine learning methods to predict molecular properties. We contend that an exemplary deep learning model should not only achieve high-precision predictions of molecular properties but also incorporate guidance from physical mechanisms. Here, we propose a framework for predicting molecular properties based on data-driven electron density images, referred to as D3-ImgNet.
View Article and Find Full Text PDFNano Lett
January 2025
State Key Laboratory of Surface Physics and Department of Physics, Fudan University, Shanghai 200433, China.
The moiré system provides a tunable platform for investigating exotic quantum phases. Particularly, the displacement field is crucial for tuning the electronic structures and topological properties of twisted double bilayer graphene (TDBG). Here, we present a series of -tunable topological transitions by the evolution of quantum Hall phases (QHPs) in the valence bands of TDBG.
View Article and Find Full Text PDFMolecules
November 2024
School of Materials Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Pinhole defects in thin films can significantly degrade their physical and chemical properties and act as sites for electrochemical corrosion. Therefore, the development of methods for the preparation of pinhole-free films is crucial. Electrodeposition, recognised for its efficiency and cost-effectiveness, shows great potential for applications in electrochemistry, biosensors, solar cells and electronic device fabrication.
View Article and Find Full Text PDFCell Insight
February 2025
State Key Laboratory (SKL) of Biobased Transportation Fuel Technology, Ocean College, Zhejiang University, Hangzhou, 316021, China.
While genomic alterations are fundamental to biological evolution, enabling adaptation and diversity, they can also result in detrimental outcomes, such as the development of genetic diseases including cancer. The budding yeast serves as an exemplary model for investigating the mechanisms behind various genomic alterations, including point mutations, chromosomal rearrangements, and whole-chromosome aneuploidy. In this review, we highlight the application of genetic screening systems to assess the mutagenic effects of physical and chemical agents efficiently.
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