Body-worn sensors can be used to capture, analyze, and replay human performance for training purposes. The key challenge to any such approach is to establish validity that the captured expert experience is actually suitable for training. In this paper, to evaluate this, we apply a questionnaire-based expert assessment and a complementary trainee knowledge assessment to study the approach adopted and the models generated with the WEKIT solution, a hardware and software application that complements Augmented Reality glasses with wearable sensor-actuator experience. This solution was developed using the ID4AR framework which as also developed within the WEKIT project. ID4AR framework is a domain agnostic framework which can be used to design augmented reality and sensor based applications for training. The study presented triangulates validity across three independent test-beds in the professional domains of aircraft maintenance, medical imaging, and astronaut training, with 61 experts completing the expert survey and 337 students completing the trainee knowledge test. Results show that the captured expert models were positively received in all three domains and the identified level of acceptance suggests that the solution is capable of capturing models for training purposes at large.@en

The WEKIT.one prototype is a platform for immersive procedural training with wearable sensors and Augmented Reality. Focusing on capture and re-enactment of human expertise, this work looks at the unique affordances of suitable hard- and software technologies. The practical challenges of interpreting expertise, using suitable sensors for its capture and specifying the means to describe and display to the novice are of central significance here. We link affordances with hardware devices, discussing their alternatives, including Microsoft Hololens, Thalmic Labs MYO, Alex Posture sensor, MyndPlay EEG headband, and a heart rate sensor. Following the selection of sensors, we describe integration and communication requirements for the prototype. We close with thoughts on the wider possibilities for implementation and next steps.@en

Augmented reality and sensor technologies have been analysed extensively in several domains including education and training. Although, varieties of use cases and applications exist, these studies were conducted in controlled laboratory environments. This paper reports on the first user study of augmented reality prototype developed to support students to learn from trainers in professional domains using augmented reality and sensors. The prototype records the performance of trainers in the first phase to support students by making it available during practice in the second phase. The performance data is made available to both the students and trainers in the third phase for reflection. A total of 142 participants which included trainers and students from three professional domains, namely 1) aircraft maintenance 2) medical imaging and 3) astronaut training, evaluated the prototype. The trainers used the prototype to record their performance while the students used the prototype to learn from the recorded performance. Participants from the three professional domains evaluated the usability of the prototype by means of a questionnaire. Randomly selected participants were also interviewed to collect their opinions and suggestion for further usability improvement. Furthermore, they also evaluated the implementation of the instructional design methods, which were identified prior in a literature review, with a brief questionnaire. The questionnaire was designed to measure the acceptance of the implementation of instructional design methods and to evaluate its adherence to the authors definition. The results of this study show that the usability of the prototype is below expected standard acceptable level. The results of the questionnaire on the implementation of the instructional design methods varied show above average acceptance levels by both the trainers and the students in the three professional domains. To conclude, the prototype shows potential to be used in different domains to support expertise development.@en