The TrainAR Authoring Tool

TrainAR is a holistic threefold combination of an interaction concept, didactic framework and authoring tool for Augmented Reality (AR) trainings on handheld Android and iOS devices (Blattgerste et al. 2021). It is completely open source, free and offers non-programmers and programmers without AR-specific expertise aiding in the creation of interactive, engaging, procedural Augmented Reality trainings. This repository contains the technical components of the interaction concept and authoring tool of TrainAR in form of a custom Unity 2022.1. Editor Extension. It can be used with the Unity Windows, macOS (Silicon), macOS (Intel), or Linux Editor and deploy to Android and iOS devices. The authoring tool already offers features like the onboarding animations, tracking solutions, assembly placements, evaluated interaction concepts, layered feedback modalities and training assessments of TrainAR out of the box. This allows authors of AR trainings to focus on the content of the training instead of technical challenges. Authors can simply import 3D models into the tool, convert them to TrainAR objects and reference them in a visual-scripting stateflow (that is inspired by work-process-analyses) to create a procedural flow of instructions, user actions and feedback.
The idea behind TrainAR is simple: Realistic deployments of head-mounted AR devices still remain a challange today because of high costs, missing relevant training, and novelty of interactions that require indepth onboarding. In contrast, smartphone-based AR would be realistically scalable today, while still retaining many of the learning benefits. At least in theory. While possible, most mobile AR learning applications focus on visualization instead of interactions today, severly limiting their application scope. In line with recent findings that, in terms of training outcome, tangible interactions are not significantly increasing retention or transfer of knowledge compared to purely virtual interaction approaches (Knierim et al. 2020), the idea of TrainAR is a holistic and scalable solution for proceudral task training using Augmented Reality on handheld AR devices. Hereby, the idea is not to replace practical trainings but use TrainAR scenarios for concept and procedure understanding in preparation for or retention training after the pracitcal training sessions. In line with Gagne 1984, it is envisioned as a noval type of multimedia source to train intellectual skills and cogntive strategies but does not train associated motor skills.
Open the TrainAR Authoring Tool
Open the TrainAR Documentation

TrainAR Example Trainings

Onboarding Sequence of the TrainAR Training

"Preparation of an emergency tocolysis"

Example Interaction of the TrainAR Training

"Preparation of an emergency tocolysis"

Open Source Project

The full source code is available at  https://github.com/jblattgerste/TrainAR/ with a full documentation at https://jblattgerste.github.io/TrainAR/

TrainAR Open Source Code
TrainAR Documentation

If you find problems, bugs or want to provide feedback or suggestions, contact us through email or post your feedback as an issue on the GitHub project. 

Give Feedback / Report a Bug

Feel free to contribute to our project through suggestions, feedback or by contributing to our open source GitHub repository through pull requests.

Contribute to this Project

Acknowledgement

Responsible Investigators

Prof. Dr. Thies Pfeiffer

Prof. Dr. rer. nat. Thies Pfeiffer

Email: thies.pfeiffer@hs-emden-leer.de

Jonas Blattgerste, PhD., M.Sc. in Informatics

Email: jonas.blattgerste@hs-niederrhein.de

Softwaredevelopment: Jonas Blattgerste, Sven Janßen, Jan Behrends