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Federico Magnani; Elena Demaria; Francesca Ambrosi; Claudia Sala; Gianandrea Pasquinelli; Michelangelo Fiorentino; Giorgia Gri – Advances in Physiology Education, 2025
Because of the recent pandemic, new teaching methods have been trialed, even in traditional disciplines such as histopathology that typically involve extensive hands-on laboratory work. In this study, we investigated the effects of three different learning modalities in histopathology teaching: optical microscopy, in-class virtual microscopy (VM),…
Descriptors: Pathology, Online Courses, Lecture Method, In Person Learning
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Miguel Ángel Rodriguez-Florido; José Juan Reyes-Cabrera; Aday Melián; Carmen Nieves Hernández-Flores; Juan Ruiz-Azola; Manuel Maynar – Journal of New Approaches in Educational Research, 2024
The metaverse is known as the hypothetical iteration of the Internet as a single, connected, universal and immersive virtual world that can be accessed via immersive technology devices. One approach to this concept can be achieved through the use of multi-user immersive virtual reality applications. Immersive virtual reality (IVR), which uses…
Descriptors: Medical Education, Medical Students, Internet, Computer Simulation
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Henrik Brun; Matthias Lippert; Thomas Langø; Juan Sanchez-Margallo; Francisco Sanchez-Margallo; Ole Jakob Elle – Anatomical Sciences Education, 2025
Learning cardiac morphology largely involves spatial abilities and studies indicate benefits from innovative 3D visualization technologies that speed up and increase the learning output. Studies comparing these teaching tools and their educational output are rare and few studies include complex congenital heart defects. This study compared the…
Descriptors: Anatomy, Human Body, Spatial Ability, Visual Aids
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Marvin Mergen; Lisa Will; Norbert Graf; Marcel Meyerheim – Education and Information Technologies, 2025
Despite growing interest in the inclusion of virtual reality (VR) in medical education, its full potential for immersive and interactive training remains underutilized, particularly in dermatology. As part of a multidisciplinary project, we tested the feasibility of integrating a VR training scenario for a complete skin cancer screening into the…
Descriptors: Medical Students, Medical Education, Cancer, Feasibility Studies
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Nan Zhang; Hongkai Wang; Tianqi Huang; Xinran Zhang; Hongen Liao – IEEE Transactions on Learning Technologies, 2024
Trunk anatomy education is critical in the training of the surgeon. Most trunk anatomy education systems use a personal or synthetic anatomical model. It remains difficult to obtain appropriate population anatomy information and create individualized anatomy customization based on a quantity of diverse data. Furthermore, the naked-eye virtual…
Descriptors: Computer Simulation, Simulated Environment, Human Body, Anatomy
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Jean Langlois; Stanley J. Hamstra; Yvan Dagenais; Renald Lemieux; Marc Lecourtois; Elizabeth Yetisir; Christian Bellemare; Germain Bergeron; George A. Wells – Anatomical Sciences Education, 2024
Haptic perception is used in the anatomy laboratory with the handling of three-dimensional (3D) prosections, dissections, and synthetic models of anatomical structures. Vision-based spatial ability has been found to correlate with performance on tests of 3D anatomy knowledge in previous studies. The objective was to explore whether haptic-based…
Descriptors: Tactual Perception, Visual Perception, Visual Acuity, Spatial Ability
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Tingting Wang; Alejandra Ruiz-Segura; Shan Li; Susanne P. Lajoie – Journal of Computer Assisted Learning, 2024
Background: Scholars have confirmed the vital roles of self-regulated learning (SRL) behaviours in predicting task performance, especially within non-linear technology-rich learning environments (TREs). However, few studies focused on the learning costs (e.g., study effort and time-on-task) related to SRL and the efficiency outcome of SRL (i.e.,…
Descriptors: Problem Solving, Educational Environment, Efficiency, Student Behavior
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Morris Gellisch; Juliane Cramer; Justin Trenkel; Franziska Bäker; Martin Bablok; Gabriela Morosan-Puopolo; Thorsten Schäfer; Beate Brand-Saberi – Anatomical Sciences Education, 2025
In recent years, there has been a growing trend toward the digitization of education, highlighting the need to understand how different learning modalities impact medical student outcomes. This study analyzes user behavior among medical students in Microscopic Anatomy, focusing on preferences for digital versus face-to-face guided self-study. A…
Descriptors: Educational Technology, Technology Uses in Education, Anatomy, In Person Learning
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Amanda J. Meyer; Jamie A. Chapman – Anatomical Sciences Education, 2024
Australia and Aotearoa New Zealand (AANZ) medical schools have been impacted by curricular changes and the introduction of virtual microscopy (VM). No survey has explicitly described the outcome of these events on histology education in AANZ. This study provides a cross-sectional overview of histology education in accredited medical schools across…
Descriptors: Foreign Countries, Medical Schools, Medical Education, Anatomy
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Tingting Wang; Juan Zheng; Susanne P. Lajoie – Educational Technology & Society, 2025
Previous studies have confirmed the pivotal roles of student engagement in predicting learning achievements; however, only a few emphasized the patterns of different engagement dimensions within individuals (i.e., co-occurrences of behavioral, cognitive, and emotional engagement). Thus, this study identifies engagement profiles and explores their…
Descriptors: Medical Students, Technology Uses in Education, Educational Technology, Computer Simulation
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Bindu Menon; Meghana Reddy Ranabothu; Krissy Elizabeth Tarter; Tyrone Deonte Oneal Layson; Deepa Mukundan; Jeremy J. Laukka – Advances in Physiology Education, 2025
Cognitive science principles can facilitate integrating and retaining basic science concepts during the clinical years of undergraduate medical education. We hypothesized that reinforcing foundational science concepts during the core clerkship experiences fosters the development of clinical reasoning in medical students. A patient simulation…
Descriptors: Undergraduate Students, Medical Education, Medical Students, Clinical Experience
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Yew Kong Lee; Ping Yein Lee; Yee Ling Lau; Chirk Jenn Ng; Wei Leik Ng; Thiam Kian Chiew; Adina Abdullah; Jamuna Vadivelu; Amirah Amir; Christina Phoay Lay Tan; Caroline Kwong Leng Chin – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to evaluate the effectiveness of using a virtual patient (VP) software program in increasing clinical reasoning skills confidence among medical students. Design/methodology/approach: A quasi-experimental design was used to compare the outcomes of students' confidence levels on clinical reasoning between problem-based…
Descriptors: Foreign Countries, Medical Students, Clinical Diagnosis, Computer Simulation
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Feroza Daroowalla; David M. Harris; Jonathan Kibble – Advances in Physiology Education, 2024
Integrating physiology core concepts into the clinical years of medical education has been challenging despite efforts. This article describes a fourth-year medical school elective, Advanced Physiology in Critical Care Medicine, that focused on integrating physiology core concepts in a case-based learning approach. The elective used…
Descriptors: Elective Courses, Student Attitudes, Physiology, Scientific Concepts
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Martonia Gaskill; Paul Dye – Journal of Interactive Learning Research, 2024
The pursuit of improved patient outcomes through the evolution in medical education is ongoing. Traditional, didactic learning methods are still utilized as a primary modality throughout medical learning (Newman & Lattouf, 2020). To address deficits in understanding and retention of learning material, experiential learning methods are…
Descriptors: Computer Simulation, Online Courses, Blended Learning, Educational Technology
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Vladimir Beketov; Marina Lebedeva; Marina Taranova – Interactive Learning Environments, 2024
The use of the innovative technologies, in particular virtual and augmented reality technologies, can have a significant impact on the training of future doctors. The sample set of the experiment consisted of 211 students from I.M. Sechenov First Moscow State Medical University. The students were divided into 4 age groups: full-time students of…
Descriptors: Artificial Intelligence, Computer Simulation, Academic Achievement, Influence of Technology