Method: A quasi-experimental study was conducted using 254 first-year medical students with no prior exposure to the lecture topic during the 2016/17 and 2017/18 academic sessions. The students from each batch were divided into two groups and exposed to different video material. Group A watched an action movie, while Group B watched an educational video related to the lecture topic. After 15 min, both groups attended a lecture on the gross anatomy of the heart, which was delivered by a qualified anatomist. At the end of the lecture, their understanding of the material was measured through a post-lecture test using ten vetted multiple choice true/false questions.
Results: Group B's test scores were found to be significantly higher than Group A's (p > 0.001, t-stats [df] = -4.21 [252]).
Conclusion: This study concluded that the pre-lecture activity had successfully provided the students with some prior knowledge of the subject before they attended the lecture sessions. This finding was aligned with cognitive load theory, which describes a reduction in learners' cognitive load when prior knowledge is stimulated.
METHODS: This was a qualitative phenomenology study conducted on 116 second-year medical students from two Malaysian public universities via teleconferencing applications that allowed synchronous small-group activities. Each group was given a different link to 10 GJ slides that featured plain anatomy diagrams and instructions for the group task. Upon completion of the tasks, the students presented their tasks to the whole class. An online feedback form was distributed at the end of the practical session to explore the experience of the students when using the tool.
RESULTS: Thematic analysis of student responses generated seven themes that reflected perceived learning benefits, challenges faced by the students, and suggestions for future improvement.
CONCLUSIONS: These findings suggest that GJ is a useful tool for promoting collaborative learning in virtual anatomy education. Nevertheless, the impact of this tool on the attainment of learning outcomes remains unknown. Hence, more widescale research is needed to confirm our findings.
METHODS: A cross-sectional study was conducted with 241 medical students. Validated questionnaires were administered to measure burnout, psychological distress, emotional intelligence, personality traits, and academic stress, respectively. A structural equation modelling analysis was performed by AMOS.
RESULTS: The results suggested a structural model with good fit indices, in which psychological distress and academic stress were noted to have direct and indirect effects on burnout. The burnout levels significantly increased with the rise of psychological distress and academic stress. Neuroticism was only found to have significant indirect effects on burnout, whereby burnout increased when neuroticism increased. Emotional intelligence had a significant direct effect on lowering burnout with the incremental increase of emotional intelligence, but it was significantly reduced by psychological distress and neuroticism.
CONCLUSION: This study showed significant effects that psychological distress, emotional intelligence, academic stress, and neuroticism have on burnout. Academic stress and neuroticism significantly increased psychological distress, leading to an increased burnout level, while emotional intelligence had a significant direct effect on reducing burnout; however, this relationship was compromised by psychological distress and neuroticism, leading to increased burnout. Several practical recommendations for medical educators, medical students, and medical schools are discussed.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40670-023-01747-6.
METHODS: A randomised controlled trial involving 197 participants from three institutions was conducted. The control group attended a freestyle lecture on the gross anatomy of the heart, delivered by a qualified anatomist from each institution. The intervention group attended a CLT-bLM-based lecture on a similar topic, delivered by the same lecturer, three weeks thereafter. The lecturers had attended a CLT-bLM workshop that allowed them to prepare for the CLT-bLM-based lecture over the course of three weeks. The students' ratings on their cognitive engagement and internal motivation were evaluated immediately after the lecture using a validated Learners' Engagement and Motivation Questionnaire. The differences between variables were analysed and the results were triangulated with the focus group discussion findings that explored students' experience while attending the lecture.
RESULTS: The intervention group has a significantly higher level of cognitive engagement than the control group; however, no significant difference in internal motivation score was found. In addition, the intervention group reported having a good learning experience from the lectures.
CONCLUSION: The guideline successfully stimulated students' cognitive engagement and learning experience, which indicates a successful stimulation of students' germane resources. Stimulation of these cognitive resources is essential for successful cognitive processing, especially when learning a difficult subject such as anatomy.
METHODS: This series of studies involved 696 participants from May 2022 to December 2022. Following scoping review, invited modified e-Delphi experts developed consensus on the components and related items for measuring online learning environments. A panel of content experts and a group of medical students carried out content and response-process validation to determine Content Validity Index (CVI) and Face Validity Index (FVI) respectively. This was followed by exploratory and confirmatory factor analysis and reliability analysis to determine Digi-MEE's factorial structure and internal consistency using SPSS version 26.0 and AMOS 26.0.
RESULTS: Delphi experts agreed upon nine components with 73 items of initial Digi-MEE version. CVI of Digi-MEE 2.0 was more than 0.90. with FVI of Digi-MEE 3.0 of 0.87. Exploratory factor analysis yielded 46 items with 57.18% variance. Confirmatory factor analysis led to the final Digi-MEE version containing 28 items within nine components with acceptable levels of goodness of fit indices. Overall Cronbach alpha of the final Digi-MEE was more than 0.90, and for the nine components ranged between 0.62 and 0.76.
CONCLUSION: Digi-MEE is a promising valid and reliable instrument to evaluate online education environment in medical education. Content, response-process, factorial structure, and internal consistency evidence support the validity of Digi-MEE. Medical schools can use Digi-MEE as an evaluation tool for the continuous quality improvement of online learning environments.
METHODS: A qualitative phenomenology study using the focus group discussion method was conducted on 30 final-year students from four public universities. Four focus group discussion sessions were conducted, and students' responses were transcribed and converted to electronic formats. The transcripts were analyzed thematically with ATLAS.ti software.
RESULTS: The first-cycle coding of the text analysis generated 157 open codes based on the phrases used by the participants. The subsequent coding cycle produced 16 axial codes-groups of open codes with similar features. During the final coding cycle, the content and interrelations between the axial codes were categorized into six codes: (1) preclinical anatomy learning experience, (2) anatomy content and teaching, (3) anatomy-related competency, (4) the importance of anatomy knowledge in clinical practice, (5) the importance of early exposure to applied clinical anatomy, and (6) suggestions for future anatomy education.
CONCLUSIONS: The six identified themes reflected students' perceptions of their anatomy learning experience, the challenges that they faced during their preclinical years, and their opinions regarding the anatomy knowledge and skills that are functionally relevant during the clinical years. Their responses also echoed the need to improve anatomy teaching and learning, thereby emphasizing the importance of early clinical integration and application.
METHODS: The initial 11-factor and 132-item AEEMI was distributed to 1930 pre-clinical and clinical year medical students from 11 medical schools in Malaysia. The study examined the construct validity of the AEEMI using exploratory and confirmatory factor analyses.
RESULTS: The best-fit model of AEEMI was achieved using 5 factors and 26 items (χ 2 = 3300.71 (df = 1680), P