Preference analysis on the online earning attributes among senior high school students during the COVID – 19 pandemic: A conjoint analysis approach.

ABSTRACT

The COVID-19 pandemic has resulted in the shift from face-to-face to fully online learning. The purpose of this study was to evaluate the preference of senior high school students on online learning attributes during the COVID-19 pandemic by utilizing a conjoint analysis approach. Six attributes which consist of delivery type, assigned tasks, evaluation, virtual laboratory, interface layout, and delivery platform were simultaneously analyzed through orthogonal design. A total of 1189 senior high school students were collected via purposive sampling approach through the social media platform. The respondents voluntarily participated and answered 29 stimuli with 2 holdouts generated by using SPSS 25 utilizing a 7-point Likert scale. The results indicated that evaluation was found to be the most significant attribute and followed by virtual laboratory, delivery type, and delivery platform. Interestingly, multiple choice evaluation, not requiring virtual laboratories, mixed delivery type (synchronous with recorded lectures), and MS Teams as delivery platform were considered as the keys for the preference. This study is the first study that utilized a conjoint approach to analyze the senior high school students’ preference on the online learning attributes during the COVID-19 pandemic. Finally, the conjoint approach can be applied and extended to evaluate the online learning attributes globally by utilizing the attributes and design created in this study.

Keywords: Conjoint analysisOnline LearningCOVID-19Students’ Preference

Citation:

Ong, A.K., Prasetyo Y.T., Chuenyindee, T., Young, M. N., Doma, B. T., Caballes, D. G., Centeno, R. S., Morfe, A. S., & Bautista, C. S. (2022). Preference analysis on the online learning attributes among senior high school students during the COVID-19 pandemic: A conjoint analysis approach. Evaluation and Program Planning, Volume 92, 2022, 102100, ISSN 0149-7189. https://doi.org/10.1016/j.evalprogplan.2022.102100.