Background: Active learning improves learner engagement and knowledge retention. The application of continuous quality improvement methodologies, such as the Plan-Do-Study-Act (PDSA) framework, may be useful for optimizing medical education, including active learning sessions. We aimed to enhance student satisfaction and achievement of learning outcomes by applying the PDSA framework to an antibiotic utilization curriculum for medical students.
Methods: Guided by the Plan-Do-Study-Act framework, between February 2017 and July 2019, we developed, implemented, and revised an active learning session for medical students, focused on appropriate utilization of antibiotics during their Internal Medicine clerkship.
Results: Across twelve sessions, 367 students (83.4%) completed the post-evaluation survey. Although baseline ratings were high (97% of respondents enjoyed the "active learning" format), constructive comments informed iterative improvements to the session, such as modifying session timing, handouts and organization of the gaming component. Intervention 3, the last improvement cycle, resulted in more favorable ratings for the active learning format (p = 0.015) improvement in understanding antibiotics and their clinical application (p = 0.001) compared to Baseline ratings.
Conclusions: This intervention suggests that active learning, with regular incorporation of student feedback vis-à-vis a PDSA cycle, was effective in achieving high student engagement in an Internal Medicine core clerkship session on antibiotic therapy. Iterative interventions based on student feedback, such as providing an antibiotic reference table and answer choices for each case, further improved student receptivity and perceived educational value. The study findings have potential implications for medical education and suggest that the application of the PDSA cycle can optimize active learning pedagogies and outcomes.
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http://dx.doi.org/10.1186/s12909-021-02886-3 | DOI Listing |
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental questions in robotics concerns this characteristic: How can linguistic compositionality be developed concomitantly with sensorimotor skills through associative learning, particularly when individuals only learn partial linguistic compositions and their corresponding sensorimotor patterns? To address this question, we propose a brain-inspired neural network model that integrates vision, proprioception, and language into a framework of predictive coding and active inference on the basis of the free-energy principle.
View Article and Find Full Text PDFCureus
December 2024
Medical Education, Shalamar Medical and Dental College, Lahore, PAK.
Objective: To investigate the dynamics of collaborative learning in team-based learning (TBL) through students' reflections and feedback.
Methods: A phenomenological mixed-methods approach was adopted where the survey and reflections were conducted concurrently after the TBL session and the results were analyzed. The study employed a mini-cluster technique to include all first-year MBBS students of batch 2023-24 with an age range between 19 and 22 years.
Front Med (Lausanne)
January 2025
Department of Gynecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background: Supervised Teaching Clinics (STCs) have emerged as an innovative approach to medical education, particularly in specialties like gynecology, where hands-on experience is crucial. Traditional clinical rotations often leave students in passive roles, limiting their active participation and the development of essential clinical skills.
Aim: This study aimed to evaluate the impact of STCs on the clinical competencies and professional development of medical students within a gynecological clinic, comparing the outcomes with those of traditional clinic shadowing.
Quant Imaging Med Surg
January 2025
Department of Ophthalmology, Key Lab of Ocular Fundus Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background: Age-related macular degeneration (AMD) represents a significant clinical concern, particularly in aging populations, and recent advancements in artificial intelligence (AI) have catalyzed substantial research interest in this domain. Despite the growing body of literature, there remains a need for a comprehensive, quantitative analysis to delineate key trends and emerging areas in the field of AI applications in AMD. This bibliometric analysis sought to systematically evaluate the landscape of AI-focused research on AMD to illuminate publication patterns, influential contributors, and focal research trends.
View Article and Find Full Text PDFBMC Med Educ
January 2025
Department of Biochemistry, Manipal Tata Medical College, Manipal Academy of Higher Education, Manipal, 576104, India.
Background: In contemporary medical education, it is essential to raise student involvement and active participation in the learning process. By contrasting small-group peer learning modules with teacher-led conventional tutorial sessions, we aim to provide insights into their respective influences on learning outcomes and the overall learning experience among 150 first-year medical students.
Methods: Each group consisted of 50 students.
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