ABSTRACT
Medical educators are in a continuous quest to close the gap between the needs of medical practice and the rising expectations of the communities in their countries. During the past two decades, competency-based medical education has been evolving as an appealing strategy to close this gap. In 2017, the Egyptian medical education authorities mandated all medical schools to change their curricula to comply with revised national academic reference standards, which changed from outcome-based to competency-based. In parallel, they also changed the timeline of all medical programs for six years of studentship and one-year internship to five years and two years, respectively. This substantial reform involved the assessment of the existing situation, an awareness campaign for the proposed changes and an extensive national faculty development program. Monitoring the implementation of this substantial reform was performed through surveys, field visits and meetings with students, teaching staff and program directors. In addition to the expected challenges, the COVID-19-associated restrictions presented a significant further challenge during the implementation of this reform. This article presents the rationale for and steps of this reform, the challenges faced and how they were addressed.
Subject(s)
COVID-19 , Education, Medical, Undergraduate , Education, Medical , Humans , Developing Countries , EgyptABSTRACT
BACKGROUND: While online education is by no means a new concept, it was recently thrust into the spotlight after school campuses all over the world were forced to close because of the COVID-19 pandemic. The sudden need to shift revealed emerging challenges to online teaching, both logistic and personal. One important challenge is the ability to assess the readiness of educators for online teaching, so that appropriate and specific feedback/training can be offered to those in need. This study aims at developing, validating, and implementing a tool to measure the teachers' readiness for online teaching in three medical schools from three different countries. METHODS: This was a multi-center, cross-sectional study that involved developing a survey through review of literature and previous studies, item development and revision, and pilot testing. The survey was then distributed electronically to a convenient sample of 217 teaching faculty members of different academic ranks from three medical schools in Egypt, Saudi Arabia, and Bahrain. Exploratory factor analysis and reliability study were performed. Descriptive statistics were applied, and the statistical significance level was set at 0.05. RESULTS: Factor analysis produced the following five factors: "Online Teaching and Course Design Skills", "Digital Communication", "Basic Computer Skills", "Advanced Computer Skills" and "Using Learning Management Systems". The tool showed high reliability (alpha = 0.94). Survey results showed highest mean scores for Basic Computer Skills with lower scores for Online Teaching and Course Design Skills and Using Learning Management Systems. ANOVA revealed statistically significant differences between the three studied schools regarding Digital Communication (F=5.13; p=0.007) and Basic Computer Skills (F=4.47; p=0.012) factors. CONCLUSION: The tool proved to be reliable and valid. Results indicated an overall acceptable readiness in the three involved schools, with a need for improvement in "Online Teaching and Course Design" and Using Learning Management Systems.
ABSTRACT
Artificial intelligence has found its way into numerous fields of medicine in the past decade, spurred by the availability of big data and powerful processors. For the COVID-19 pandemic, aside from predicting its onset, artificial intelligence has been used to track disease spread, detect pulmonary involvement in computed tomography scans, risk-stratify patients, and model virtual protein structure and potential therapeutic agents. This mini-review briefly discusses the potential applications of artificial intelligence in COVID-19 microscopy.