Emergency remote CAD teaching using licensed software in apparel during the COVID-19 pandemic: a collaborative learning approach

  • Ranapanada Kelum Jayamali De Silva Department of Textile and Apparel Engineering, University of Moratuwa, Moratuwa, Sri Lanka
  • Anuradha Peramunugamage Department of Electrical and Computer Engineering, The Open University of Sri Lanka, Nugegoda, Sri Lanka
Keywords: apparel industry, CAD teaching, COVID-19, emergency remote teaching, online collaborative learning


Computer-Aided Design (CAD) training has become essential in apparel education as it is widely applied in design and development activities in the industry. This study presents how physical CAD teaching converted to remote delivery during the emergency COVID-19 pandemic using online technologies. This study evaluated five distinct methods adopted in this period: online Zoom sessions, pre-recorded practical demonstrations, guided hand-outs, online collaborative learning methods and forum discussions using Moodle. TeamViewer application was utilised for real-time remote access and support during teaching. This study instrumented two online questionnaires intended to assess the effectiveness of online hands-on sessions and collaborative learning in a remote online environment. This study was conducted with 58 participants at a recognised Sri Lankan state university. More importantly, the results confirmed the feasibility of collaborative engagement within the online learning environment. This study discovered students’ preferences for synchronous teaching and learning approaches. Also, it revealed the limitations of remote CAD teaching using online technologies. Finally, this study underlined the success of the collaborative learning approach and students’ perspectives on flipped classroom model for apparel CAD training.


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How to Cite
De Silva R. K. J., & Peramunugamage A. (2023). Emergency remote CAD teaching using licensed software in apparel during the COVID-19 pandemic: a collaborative learning approach. Research in Learning Technology, 31. https://doi.org/10.25304/rlt.v31.2821
Original Research Articles