Highlights
- •Several effective strategies can be used before, during, and after the workstation readout to improve resident education.
- •Perform lower volume readouts at more frequent intervals throughout the day, especially with junior residents.
- •Using soundbites during the readout helps to improve retention of key teaching points.
Abstract
Resident education is a complex process that requires many inputs from both the learner
and the educator. As teaching faculty, many radiologists rely on two main methods
to impart knowledge to their residents; namely didactic/case-based lectures and workstation
teaching. The traditional lecture format is well known to both the learner and the
educator, as this has been the primary platform that has been used almost universally.
In addition, there are a multitude of excellent recorded and live lectures that faculty
members can access from national society meetings that can be used as an example of
how to give an effective well-organized lecture. Workstation teaching, on the other
hand, is instead a more individualistic endeavor that is quite heterogeneous across
institutions. In addition, there is very little in the literature that describes effective
strategies that can be used to optimize the educational experience for the resident.
This discussion will focus on pre-readout, readout, and post-readout strategies that
educators can use at the workstation. Implementation of these techniques can be extremely
helpful in accelerating resident progression through their training.
Keywords
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References
- Running a radiology residency program: strategies for success.Radiographics. 2018; 38: 1729-1743
- Effects of repetition learning on associative recognition over time: role of the hippocampus and prefrontal cortex.Front Hum Neurosci. 2018; 12: 277
- Teaching radiology in the millennial era.Acad Radiol. 2013; 20: 387-389
- On the Internet.Routledge, New York, NY2001
Article info
Publication history
Published online: January 24, 2022
Accepted:
January 14,
2022
Received in revised form:
January 6,
2022
Received:
July 28,
2021
Identification
Copyright
© 2022 Elsevier Inc. All rights reserved.
