Train<i>AR</i>: A Scalable Interaction Concept and Didactic Framework for Procedural Trainings Using Handheld Augmented Reality

Abstract

The potential of Augmented Reality (AR) for educational and training purposes is well known. While large-scale deployments of head-mounted AR headsets remain challenging due to technical limitations and cost factors, advances in mobile devices and tracking solutions introduce handheld AR devices as a powerful, broadly available alternative, yet with some restrictions. One of the current limitations of AR training applications on handheld AR devices is that most offer rather static experiences, only providing descriptive knowledge with little interactivity. Holistic concepts for the coverage of procedural knowledge are largely missing. The contribution of this paper is twofold. We propose a scalabe interaction concept for handheld AR devices with an accompanied didactic framework for procedural training tasks called TrainAR. Then, we implement TrainAR for a training scenario in academics for the context of midwifery and explain the educational theories behind our framework and how to apply it for procedural training tasks. We evaluate and subsequently improve the concept based on three formative usability studies (n = 24), where explicitness, redundant feedback mechanisms and onboarding were identified as major success factors. Finally, we conclude by discussing derived implications for improvements and ongoing and future work.

Keywords

• mobile
• handheld
• augmented reality
• mixed reality
• procedural
• education