Self‐Directed Learning Modules Enhance Mastery of Diagnostic Imaging in a Dissection‐Based Anatomy Course for Physician Assistant Students

Abstract

The virtues of using computer‐based learning modules as an alternative to traditional didactic lectures were tested in a human anatomy course for Physician Assistant (PA) students. Self‐directed learning modules on diagnostic imaging were created using Articulate™ software and provided online as homework assignments for PA students taking a human anatomy lecture and dissection laboratory course. These interactive self‐learning modules replaced the content of traditional didactic lectures on the same topics that had been given in previous years. For the PA class of 2016 (n=104), diagnostic imaging was taught via traditional lectures, whereas for the PA class of 2017 (n=100), students studied the same content online using self‐learning modules. An identical set of 21 questions on diagnostic imaging was used for both lecture (2016) and self‐learning (2017) groups of students, and student performance on these examinations was compared between the two groups. Our results indicate that PA students with access to online self‐learning modules performed as well or significantly better on the diagnostic imaging questions (p<0.05 for 5 of 21 questions). Moreover, the average on the diagnostic imaging questions improved from 86.29 (class of 2016) to 89.19 (class of 2017). The overall course grade for students using self‐learning modules for diagnostic imaging was also higher (class mean 87.76) than that of students receiving lectures for diagnostic imaging (class mean 86.08), suggesting that self‐learning modules may have a positive influence on students' overall understanding of the anatomical material. Our results indicate that online self‐study modules are highly effective teaching tools for pre‐clinical basic science medical education.Support or Funding InformationNoneThis abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.