Blended learning of radiology improves medical students’ performance, satisfaction, and engagement

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Abstract

Purpose: To evaluate the impact of blended learning using a combination of educational resources (flipped classroom and short videos) on medical students’ (MSs) for radiology learning. Material and methods: A cohort of 353 MSs from 2015 to 2018 was prospectively evaluated. MSs were assigned to four groups (high, high-intermediate, low-intermediate, and low achievers) based on their results to a 20-MCQs performance evaluation referred to as the pretest. MSs had then free access to a self-paced course totalizing 61 videos based on abdominal imaging over a period of 3 months. Performance was evaluated using the change between posttest (the same 20 MCQs as pretest) and pretest results. Satisfaction was measured using a satisfaction survey with directed and spontaneous feedbacks. Engagement was graded according to audience retention and attendance on a web content management system. Results: Performance change between pre and posttest was significantly different between the four categories (ANOVA, P = 10−9): low pretest achievers demonstrated the highest improvement (mean ± SD, + 11.3 ± 22.8 points) while high pretest achievers showed a decrease in their posttest score (mean ± SD, − 3.6 ± 19 points). Directed feedback collected from 73.3% of participants showed a 99% of overall satisfaction. Spontaneous feedback showed that the concept of “pleasure in learning” was the most cited advantage, followed by “flexibility.” Engagement increased over years and the number of views increased of 2.47-fold in 2 years. Conclusion: Learning formats including new pedagogical concepts as blended learning, and current technologies allow improvement in medical student’s performance, satisfaction, and engagement.

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APA

Vavasseur, A., Muscari, F., Meyrignac, O., Nodot, M., Dedouit, F., Revel-Mouroz, P., … Mokrane, F. Z. (2020). Blended learning of radiology improves medical students’ performance, satisfaction, and engagement. Insights into Imaging, 11(1). https://doi.org/10.1186/s13244-020-00865-8

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