Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers

Abstract

The decline of enrollees for industrial engineering during the COVID-19 pandemic and the increasing demand for professional industrial engineers should be explored. The purpose of this study was to determine the preference of industrial engineering students of different educational levels on online learning during the COVID-19 pandemic. Specifically, this study utilized conjoint analysis with orthogonal design considering seven attributes: delivery type, layout, term style, final requirements, Coursera requirements, seatwork and practice sets, and platforms. Among the attributes, 20 stimuli were created through SPSS and were answered voluntarily by 126 respondents utilizing a 7-point Likert Scale. The respondents were comprised of 79 undergraduate, 30 fully online master’s degree, and 17 master’s and doctorate degree students collected through purposive sampling. One university from the two available universities that offer all educational levels of IE in the Philippines was considered. The results showed that undergraduate students considered the final requirements with multiple-choice as the highest preference, followed by non-modular term style, and no seatwork and practice sets. In addition, fully online master’s degree students considered delivery type with the mix as the highest preference, followed by layout, and no seatwork and practice sets. Finally, master’s and doctorate degree students considered final requirements with publication as the highest preference, followed by no seatwork and practice sets, and mix delivery type. The students are technologically inclined, want to learn at their own pace, know where and how to get additional online learning materials, but still need the guidance of teachers/professors. The results would help contribute to the theoretical foundation for further students’ preference segmentation, specifically on online learning during the COVID-19 pandemic worldwide. Moreover, the design created could be utilized for other courses in measuring students’ preference for online learning even after the COVID-19 pandemic.

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“…There was a total of 22 stimuli generated by the SPSS. The orthogonal design was utilized to have a reasonable number of stimuli that the participants evaluated with 2 holdouts considered in this study [30,31]. The different stimuli were evaluated using a 7-point Likert scale with a range from 1 as "strongly disagree" to 7 as "strongly agree".…”

“…The implementation stage ran a preliminary test to determine the validity of the conjoint analysis orthogonal design. According to Hair [57], a Pearson's Rvalue greater than or equal to 0.70 indicates that the orthogonal design may be considered acceptable [30,31,46]. This study had an initial result of 0.912-considered to be a high relationship among the responses and attribute of preference.…”

“…The results prompt the rankings or ratings of the consumers from a hypothetical service that is presented from the survey questionnaire. Studies such as food and beverages preferences, such as milk and tea [23,30], online learning attributes [21,31,32], park preferences [17,27], musical instruments [22], education [33,34], public e-services [26], and even health risks and vaccine preferences [35,36] have been conducted. Therefore, conjoint analysis as a tool for evaluating the complete set-up of group attributes highlights consumer preferences and can lead to businesses being able to understand customer preference and, if delivered, can lead to customer satisfaction [30].…”

“…[30], the Pearson's R-value indicates the relationship of the responses and the attributes in this study. From the results, it could be seen that Pearson's R had a value of 0.979, indicating a high relationship [30,31,57]. The Kendall's Tau presents the validity and reliability of the constructs [31,57].…”

“…From the results, it could be seen that Pearson's R had a value of 0.979, indicating a high relationship [30,31,57]. The Kendall's Tau presents the validity and reliability of the constructs [31,57]. Hair [57] indicated that Kendall's Tau and Pearson's R-value should have a value greater than 0.70 to be considered acceptable.…”