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

M. Leyer (Corresponding author), B. Aysolmaz, Ross Brown, Selen Türkay, Hajo A. Reijers

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

6 Citaten (Scopus)
159 Downloads (Pure)

Samenvatting

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.
Originele taal-2Engels
Artikelnummer103346
Aantal pagina's11
TijdschriftComputers in Industry
Volume124
DOI's
StatusGepubliceerd - jan. 2021

Financiering

This work has been partially supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 660646 . This work has been partially supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 660646.

FinanciersFinanciernummer
Horizon 2020 Framework Programme
H2020 Marie Skłodowska-Curie Actions660646
Horizon 2020

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