Effectiveness of a Radiographic Anatomy Software Application for Enhancing Learning of Veterinary Radiographic Anatomy

• Published in: Journal of veterinary medical education Vol. 45; no. 1; p. 131
• Main Authors: Reiter, Rachel, Viehdorfer, Matt, Hescock, Kimmy, Clark, Terri, Nemanic, Sarah
• Format: Journal Article
• Language: English
• Published: Canada 01.03.2018
• Subjects: Anatomy, Veterinary - education; Animals; Clinical Competence; Computer-Assisted Instruction; Dogs - anatomy & histology; Educational Measurement; Humans; Radiology; Software; web-based learning; canine; computer-assisted learning; radiographic anatomy; radiology
• ISSN: 0748-321X
• DOI: 10.3138/jvme.0516-100r

The goal of this study was to determine the effectiveness of an interactive radiology software application that we developed to enhance learning of normal canine radiographic anatomy. All first-year veterinary medical students were eligible to participate in this subject pre-test-post-test experimental design. When presented with the software application, all students had completed two terms of gross anatomy in which the complete anatomy of the dog had been taught using a combination of lectures and laboratory dissections, including radiographic examples. The software application was divided into four body regions: front limb, hind limb, skull/spine, and thorax/abdomen, each with a learning mode and a quiz mode. Quizzes were composed of 15 questions drawn pseudo-randomly without repeat from all structures within a region (median 206 structures). Students were initially given the software application with only the quiz mode activated. After completing four quizzes, one for each body region, students were given access to the software application with both learning mode and quiz mode activated. Students were instructed to spend 30 minutes using the learning mode to study the radiographic anatomy of each region and to retake each quiz. Quiz scores after using the learning mode were significantly higher for each body region (p<.001), with a large effect size for all four regions (Cohen's d=0.83-1.56). These results suggest that this radiographic anatomy software application is an effective tool for students to use to learn normal radiographic anatomy.