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  • 标题:User Preference Analysis of a Sustainable Workstation Design for Online Classes: A Conjoint Analysis Approach
  • 本地全文:下载
  • 作者:Gumasing, Ma. Janice J. ; Ong, Ardvin Kester S. ; Bare, Maria Angelica D.
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2022
  • 卷号:14
  • 期号:19
  • 页码:1-23
  • DOI:10.3390/su141912346
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:The impact of the COVID-19 pandemic has caused the sudden shift of the interactions between students and teachers from the four corners of the classroom to fully online learning through the workstations. By using a conjoint analysis approach, this study aimed to evaluate the preference of undergraduate students from the Philippines on the workstation design attributes during the pandemic. Seven attributes were examined through orthogonal design: the type of gadget, keyboard, mouse, earpiece, desk, kind of chair, and light device. Through a purposive sampling approach, a total of 315 undergraduate students from the Philippines were gathered. Through an online survey with two holdouts, the respondents voluntarily responded to 51 stimuli produced by IBM SPSS using a 7-point Likert scale. Type of gadget (37.925%) was found to be the most significant attribute preferred by the students, followed by the type of mouse (28.345%), kind of chair (14.840%), type of keyboard (7.548%), earpiece (7.177%), light device (2.109%), and desk (2.056%). It is worth noting that the preferred workstation design combination is the personal computer, mechanical keyboard, wired mouse, headset, height-adjustable table, high-back office chair with neck support, and floor lamp. This study is the first to use a conjoint technique to examine undergraduate students’ preferences for workstation design attributes during the COVID-19 pandemic. Finally, by applying the attributes and design developed in this study, the conjoint method can be used and expanded to evaluate the workstation design attributes of other courses and even employees worldwide.
  • 关键词:workstation design; online classes; user preference; conjoint analysis
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