Automation of Educational Tasks for Academic Radiology

Abstract

Rationale and objectives: The process of education involves a variety of repetitious tasks. We believe that appropriate computer tools can automate many of these chores, and allow both educators and their students to devote a lot more of their time to actual teaching and learning. This paper details tools that we have used to automate a broad range of academic radiology-specific tasks on Mac OS X, iOS, and Windows platforms. Some of the tools we describe here require little expertise or time to use; others require some basic knowledge of computer programming.

Materials and methods: We used TextExpander (Mac, iOS) and AutoHotKey (Win) for automated generation of text files, such as resident performance reviews and radiology interpretations. Custom statistical calculations were performed using TextExpander and the Python programming language. A workflow for automated note-taking was developed using Evernote (Mac, iOS, Win) and Hazel (Mac). Automated resident procedure logging was accomplished using Editorial (iOS) and Python. We created three variants of a teaching session logger using Drafts (iOS) and Pythonista (iOS). Editorial and Drafts were used to create flashcards for knowledge review. We developed a mobile reference management system for iOS using Editorial. We used the Workflow app (iOS) to automatically generate a text message reminder for daily conferences. Finally, we developed two separate automated workflows-one with Evernote (Mac, iOS, Win) and one with Python (Mac, Win)-that generate simple automated teaching file collections.

Results: We have beta-tested these workflows, techniques, and scripts on several of our fellow radiologists. All of them expressed enthusiasm for these tools and were able to use one or more of them to automate their own educational activities.

Conclusions: Appropriate computer tools can automate many educational tasks, and thereby allow both educators and their students to devote a lot more of their time to actual teaching and learning.

Keywords: Automation; education; productivity; research.