Task complexity and learning styles in situated virtual learning environments for construction higher education

Publisher:
Elsevier BV
Publication Type:
Journal Article
Citation:
Automation in Construction, 2020, 113, pp. 103148-103148
Issue Date:
2020-05-01
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© 2020 Elsevier B.V. This paper contributes to the ongoing discussion and research on the role of 3D virtual learning environments in teaching and learning. It specifically focuses on the use of video games as an enabling technology in construction higher education. As such, it investigates whether task complexity has any influence on an individual's preferred learning style while learning through virtual reality (VR) technology. To answer this question and address relevant issues, an educational experiment has been designed and conducted. An experimental virtual learning environment, the Situation Engine, was set up as a virtual construction site for undergraduate construction students to experience construction work in progress. The design and development of the Situation Engine has drawn on powerful pedagogical theories such as situated and experiential learning. 253 undergraduate students participated in the educational experiment. Three tasks of different complexity levels were designed as the experimental environments; with level of complexity being the independent variable. The hypothesis that students would adopt different learning styles when engaged in learning tasks of different complexities was rejected. No significant difference in the preferred learning styles was identified among the three experimental groups. It was concluded, therefore, that when using virtual reality technology for construction education there is no evidence to suggest the level of task complexity has significant influence on how people learn. The study presented in this paper is the first empirical study in the construction higher education field that reveals the relationship between the task complexity and students learning styles when Virtual Learning Environments are engaged.
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