This doctoral thesis investigates the use of immersive technology for workplace training with the purpose of improving competence building and providing a framework for future development. Although rooted in computer science, it reaches out to other disciplines, including technology-enhanced learning, pedagogy, and statistical psychology, in order to inform and evaluate the development of an immersive training system. Built around a core of software engineering principles and practices, this research's theoretical landscape includes Affordance Theory and Social Systems Theory. It takes structure from models of technology acceptance (UTAUT2) and Anderson and Krathwohl's taxonomy of cognitive processes, using these to shed light on the attitudes and expectations that surround the use of this technology. An `experience capture system' is described, which allows an expert to compose sequences of augmented instructions while carrying out the activity. As well as a head-mounted display, the system also used body-worn sensors to capture movement and muscle activation, connecting data streams that could be recorded, stored, and edited through the immersive interface. The inclusion of the recorded data streams connected the trainee to a learning dimension not accessible with flat-screen technology. This system was tested across medical, aeronautic, and astronautic use cases with more than 400 people over two iterations, each of whom also participated in a technology acceptance study investigating their attitudes towards augmented reality and wearable technology. Analysis was done using structural equation modelling, where constructs and relations were investigated with confirmatory factor analysis and path analysis, respectively. Model optimisation was conducted using a combination of theoretical review and statistical metrics, including modification indices and all common absolute and relative fit indices. In the technology acceptance studies, closer interoperability was consistently found to predict a reduction in the expected effort required to use the system. The attitudinal constructs of individual- and activity-technology fit, developed as part of this research, were found to play important roles in predicting the acceptance of immersive technology. Unexpectedly, a closer perceived fit between the technology and the activity was found to accompany a sense of being ill-equipped for the task. As well as methodological contributions on acceptance model optimisation and interpretation, this work also puts forward the affordance as a unit of measurement for technology-enhanced learning and describes three categories of immersive learning affordances: propositional, embodied, and meta-constructive. These are presented alongside cognitive processes as an `affordance dimension', with the goal of operationalising them in the context of immersive technology development. In summary, through this thesis, I have demonstrated a theoretical outline for categorising affordances, examples of their use with immersive technology, and a quantitative evaluation protocol. Despite constraints from device capabilities, I have shown that immersive technology is enjoyable, easy to use, and effective in supporting learning in the workplace.
Permanent link to this resource: https://doi.org/10.24384/2WSN-6J28
Guest, William A. A.
Supervisors: olde Scheper, Tjeerd; Rolf, Matthias; Wild, Fridolin
School of Engineering, Computing and Mathematics
Year submitted for examination: 2023 RADAR publication date: 2023-09-18
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