Ultrasound imaging in teaching cardiovascular physiology: disruption and challenge to foster learning

This work extends previously described applications of ultrasound technology in illustrating cardiovascular phenomena to investigation of learning effectiveness. To this end, learning in ultrasound-enhanced classes was assessed by quantifying the improvement in single best answer (SBA) exams conducted before and after an ultrasound practical class. This improvement was then compared to that seen in the same SBA exams conducted in matched groups that undertook similar classes conducted without ultrasound equipment. The SBA exams were designed to include questions that directly related to the phenomena being investigated in the practical classes as well as other "filler" questions to disguise the intent of the exam and ensure that standards of physiology knowledge were similar between the two groups. Any small statistically significant gains in performance observed between the two groups were confounded by differences in baseline (pretest) performance between the groups. These results contradict our previous work, which showed that self-reported measures of learning increased after ultrasound classes. It may be optimistic to expect improvements in deep learning and test performance immediately after even the most effective educational intervention. Direct measurement of the phenomena that bring about deep, long-term learning in classes remains problematic. Notwithstanding this, there is much evidence for the value of enhancing physiology learning by providing varying contexts in the physical, semantic, and cognitive domains. Ultrasound technology is a cheap and effective means of providing such context in physiology practical classes.NEW & NOTEWORTHY This work compares learning in cardiovascular physiology classes enhanced by using cheap ultrasound equipment with learning in comparable control classes without ultrasound. Performance improvement in single best answer tests between pre- and postclass tests were compared for the ultrasound and control classes, with little difference shown between the two classes. We question whether it is appropriate to measure deep learning after 2-h classes or whether other, phenomenological, qualitative measures of educational effectiveness would be better.