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Objectives: This study aimed to enhance the learning experience among medical students by empowering them to co-create learning tools and classroom activities.
Methods: A cross-sectional study was conducted with 10 participants from Year 2 of the new curriculum volunteering to participate in this study. Five were selected based on their diversities and empowered to design learning tools and class activities. Student satisfaction was presented as mean scores. A comparison of self-confidence scores in subjects learned before and after the class was analyzed using the paired t-test. Comparisons of multiple-choice question (MCQ) scores before and after the class between Years 2 (n = 96) and Year 3 of the previous curriculum attending inclass teaching (n = 98) were analyzed using the independent sample t-test.
Results: A high level of satisfaction (M=87.5, SD=15.7%) and significant improvements in student self-confidence in subjects learned between before (M=46.4, SD=20.8%) and after (M=82.7, SD=16.9%) the class were noted (t = -23.73, p<.001). Additionally, Year 2 students achieved significantly higher MCQ scores after the class (M=85.6, SD=19.0%) compared with the scores from Year 3 (M=77.3, SD=23.6%) (t = 3.32, p<.001).
Conclusions: Empowering medical students to co-create learning tools and class activities could positively enhance their learning experience. The result of this study addressed the importance of student empowerment with well-designed student-centered learning strategies based on their learning environment. Additional qualitative research is required to better understanding the "why" and "how" behind the findings of this study.
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http://dx.doi.org/10.5116/ijme.6702.4d43 | DOI Listing |
Eur J Case Rep Intern Med
August 2025
Hanoi Heart Hospital, Hanoi, Vietnam.
Background: Perforation of artery causing bleeding is a rare but serious complication of percutaneous coronary intervention (PCI), with potentially life-threatening consequences. Prompt recognition and management are crucial, particularly in high-risk patients or complex procedures. Coils are essential tools for sealing perforated or ruptured vessels, preventing further haemorrhage and stabilising the patient.
View Article and Find Full Text PDFFront Rehabil Sci
August 2025
Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
Introduction: Spinal cord injury (SCI) presents a significant burden to patients, families, and the healthcare system. The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.
Methods: We conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes.
Front Syst Biol
August 2025
Minutia.AI Pte. Ltd., Singapore, Singapore.
A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool for this task. BNs require constructing a structure of dependencies among variables and learning the parameters that govern these relationships.
View Article and Find Full Text PDFFront Vet Sci
August 2025
Pathobiology and Population Science, Royal Veterinary College, Hatfield, United Kingdom.
Diffuse large B-cell lymphoma is the most common type of non-Hodgkin lymphoma (NHL) in humans, accounting for about 30-40% of NHL cases worldwide. Canine diffuse large B-cell lymphoma (cDLBCL) is the most common lymphoma subtype in dogs and demonstrates an aggressive biologic behaviour. For tissue biopsies, current confirmatory diagnostic approaches for enlarged lymph nodes rely on expert histopathological assessment, which is time-consuming and requires specialist expertise.
View Article and Find Full Text PDFJ Coll Sci Teach
March 2025
RCSB Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers University, Piscataway, New Jersey, United States.
Structure-function relationships are a core concept in many STEM disciplines. Most biology curricula introduce students to macromolecules, their building blocks, and other small molecules that play key roles in biological processes. However, the shapes, interactions, and functions of these molecules are often discussed using schematic diagrams, ignoring the vast amounts of three-dimensional structural and bioinformatics data freely available from public data resources.
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