Process training for industrial organisations using 3D environments: An empirical analysis

Publication date

2021-01

Authors

Leyer, M.
Aysolmaz, Banu
Brown, Ross
Türkay, Selen
Reijers, Hajo A.ORCID 0000-0001-9634-5852ISNI 0000000037238136

Editors

Advisors

Supervisors

Document Type

Article
Open Access logo

License

taverne

Abstract

Industrial organisations spend considerable resources on training employees with respect to the organisations’ business processes. These resources include business process models, diagrams depicting vital activities, workflows, roles, systems, and data within these processes. However, these models are difficult to comprehend, partly because they possess minimal connection to real-world concepts. Alternately, 3D environments allow greater learning opportunities for process-related knowledge. To this end, we designed a non-interactive 3D environment for process training purposes that allows learners to apply the method of loci, which has been shown to improve learning by helping associate visuospatial elements with learning material. The prototype environment, which was developed using simple visualisations, can be adapted across industrial organisations and domains. In order to test the effectiveness of the 3D environments in comparison with 2D environments, we conducted a between-subjects experiment with two conditions. The results show that 3D environments result in more accurate and faster recall of process knowledge, suggesting that such an environment can provide a better affective learning experience. These findings have important implications for how organisations can train their employees with the aim of improving the acquisition of process knowledge.

Keywords

3D environments, Job training, Method of loci, Process learning, Situated learning, Taverne, General Computer Science, General Engineering

Citation

Leyer, M, Aysolmaz, B, Brown, R, Türkay, S & Reijers, H A 2021, 'Process training for industrial organisations using 3D environments: An empirical analysis', Computers in Industry, vol. 124, 103346, pp. 1-11. https://doi.org/10.1016/j.compind.2020.103346