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Optimising Immersive Virtual Reality Training to Improve Human Performance in Industry

A quantitative analysis of Immersive Virtual Reality industrial assembly training in three levels of design element optimisation and on two platforms
: Zürcher, Paul-David
: Bohné, Thomas; Kuijper, Arjan

Darmstadt, 2021, 248 S.
Darmstadt, TU, Bachelor Thesis, 2021
Bachelor Thesis
Fraunhofer IGD ()
Lead Topic: Digitized Work; Research Line: Human computer interaction (HCI); simulation based training; Skill Training; user interfaces for virtual environments; virtual reality modeling

This thesis investigates the potentials of Immersive Virtual Reality training for assembly skill acquisition by analysing the effects of discrete design element optimisations on worker productivity and human factor considerations. The research’s driving questions are: 1. Can Crowdsourcing platfoms enable effective testing and optimisation of Immersive Virtual Reality training? 2. Can strategic optimisation of educational design elements enhance Immersive Virtual Reality training? A literature review and an experiment provide the empirical ground to answer these questions. In the experiment, an Immersive Virtual Reality training teaches the assembly of a technical converter. The experiment’s assembly training scene has three treatment groups using two recruitment channels - traditional recruiting and Crowdsourcing (via Amazon Mechanical Turk (MTurk)). Each of the resulting six groups is individually evaluated regarding their training effectiveness based on performance indicators, affective indicators, and usability aspects of Immersive Virtual Reality training. The treatment groups contain the same content with different design elements. The first treatment group (control group) is a basic Immersive Virtual Reality training developed in collaboration with an industry partner. The second treatment group (optimised performance) modifies the control group’s design elements based on Cognitive Load Theory (CLT) to optimise training performance. The third treatment group (optimised affectivity) optimises the training effectiveness of the second treatment group using motivation and satisfaction promoting design elements. Comparing the different treatment groups’ results indicates whether strategic optimisation of educational design elements enhances training effectiveness. Comparing the recruiting channels’ results indicates whether Crowdsourcing recruiting is comparable to traditional recruitment techniques and thus whether Crowdsourcing is an appropriate recruiting alternative.