Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7854
Title: Doing textiles experiments in game-based virtual reality: A design of the stereoscopic chemical laboratory (SCL) for textiles education
Authors: Prof. LAU Kung Wong, Nick 
Kan, Chi Wai 
Lee,Pui Yuen 
Issue Date: 2017
Source: International Journal of Information and Learning Technology, 2017, Vol. 34 No. 3, pp. 242-258
Journal: International Journal of Information and Learning Technology 
Abstract: Purpose The purpose of this paper is to discuss the use of stereoscopic virtual technology in textile and fashion studies in particular to the area of chemical experiment. The development of a designed virtual platform, called Stereoscopic Chemical Laboratory (SCL), is introduced. Design/methodology/approach To implement the suggested educational approaches of SCL, a set of teaching and learning materials with emphasis on the application methods was revised from the existing subjects. The architecture of SCL includes building of virtual objects with the Autodesk software Maya and designing of interactivity by using Unity, a game engine system. Prototype version of the SCL has been passed to selected academic colleagues and students for further evaluation and application feedback. Findings Textile students can conduct laboratory experiments associated with coloration and finishing of textile technologies in a stereoscopic 3D and multisensory laboratory, and hence enhance their learning experience. With the use of SCL, students can learn relevant experiment tools, experimental processes, procedures, and safety and health precautions. Originality/value There is very limited educational or training approach in applying stereoscopic virtual reality in teaching activities. In the area of textile experiment, the authors could say it is virtual and does not exist in current research domains.
Type: Peer Reviewed Journal Article
URI: http://hdl.handle.net/20.500.11861/7854
ISSN: 2056-4880
DOI: 10.1108/IJILT-05-2016-0016
Appears in Collections:Applied Data Science - Publication

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