Evaluating the effectiveness of VR in a working at height training program: a crossover design experiment

dc.contributor.advisorDr. Ratvinder Grewal
dc.contributor.authorG C, Pranil
dc.date.accessioned2025-06-02T18:52:38Z
dc.date.available2025-06-02T18:52:38Z
dc.date.issued2024-05-22
dc.description.abstractFalling from height is considered one of the top causes of workplace injuries and fatalities in the construction industry. Safety training employing virtual reality has demonstrated its effectiveness in enhancing learning outcomes as compared to traditional methods of training. However, there is a research gap in integrating and evaluating the effect of VR in traditional forms of training. The main objective of this study is to assess the impact on user performance when VR is integrated with traditional methods in working at height programs. A cross-over experimental design was employed, allowing participants to experience VR both before and after traditional training across two distinct groups. Both between-subject and within-subject analyses were conducted to gauge the individual effects and determine the superior sequence or group performance. User performance was significantly enhanced in both groups using pre-test and post-test measures, with no notable difference observed between the groups. However, the group experiencing VR after the traditional training improved their self-efficacy score in both trainings. This study implies that introducing VR after traditional training could potentially bolster participant confidence in safety training scenarios.
dc.identifier.urihttps://laurentian.scholaris.ca/handle/10219/4297
dc.language.isoen_CA
dc.publisherLaurentian University Library & Archives
dc.rights.holderPranil G C
dc.rights.licenseLaurentian University ETD license
dc.subjectvirtual reality
dc.subjectworking at heights training
dc.subjectcrossover experiment
dc.titleEvaluating the effectiveness of VR in a working at height training program: a crossover design experiment
dc.typeThesis
thesis.degree.disciplineComputational Sciences
thesis.degree.grantorLaurentian University of Sudbury
thesis.degree.level1
thesis.degree.nameMaster of Science (MSc) in Computational Sciences

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