Evaluation of three educational use cases for using Virtual Patients in Massive Open Online Courses (MOOCs): a Delphi study

Abstract

Abstract Background: Massive Open Online Courses (MOOCs) extended with Virtual Patients (VPs) may foster specific medical skills. In particular, three educational use cases have been proposed to enable interactivity and foster clinical reasoning skills training: collective evaluation of decision making in the context of uncertainty, collective repurposing of cases with division of discussion into subgroups, and computational models in short cases for flexible selection and adaptive learning with VPs. The aim of this study was to evaluate the educational strengths and weaknesses of the proposed use cases. Methods: We went through a two-round modified Delphi process. A panel of experts was formed and asked with open-ended questions to identify the strengths and weaknesses of each use case. The obtained responses were categorized thematically; four specific aspects of the use cases were isolated. In the second phase, the panel was asked to read the collected, categorized responses and prioritize the use cases focusing on each of the four identified aspects. Results: Six experts participated in the process. According to their opinion, decision making in uncertain context was the most feasible in implementation and in fostering clinical reasoning skills training; cultural repurposing was judged to leverage the MOOC potential the most; and computational models in short cases were considered the most interesting use case for the learners. Conclusions: The use cases were validated and prioritized; the Delphi approach brought insights into the use cases’ potential benefits, threats, and challenges.