A Conjoint Study and Segmentation on the Preferred Online Learning Attributes of Senior High School Learners

Abstract

The educational systems have been disrupted due to the COVID-19 pandemic that has resulted in the sudden shift in the instructional implementation from face-to-face to fully online distance learning. This quantitative study examined the learners’ socio-demographic characteristics and access to technological resources, preferred online learning attributes, and their segmentation. The study employed a descriptive and exploratory research design. Using Cochran's formula and disproportionate stratified random sampling technique, 300 senior high school learners were identified as respondents of the study. Five online learning attributes consisting of delivery type, lecture, learning tasks, learning materials, and assessment methods were analyzed through the orthogonal plan component of SPSS 22.0. Respondents voluntarily answered 16 profiles with 2 holdouts generated by the orthogonal design using an online 5-point Likert scale. The conjoint analysis revealed that learners' most preferred online learning attributes were assessment methods using multiple-choice and multiple types of exams; synchronous online lectures with slides as the delivery type; individual tasks; and learning materials utilizing visual aids. Further analysis revealed that learners, considering their preferences and profiles, could be classified into two segments based on grade level. Grade 12 learners comprised segment one, and Grade 11 dominated segment two. The results provide insights for academic institutions that learners in different grade levels differ in their learning preferences in an online setup and to reconsider the appropriate pedagogical activities to be utilized in an online learning setup to ensure educational advantage. Therefore, it would be ideal to redesign the curricula and innovate pedagogical approaches based on learners’ preferences and segmentation (grade level) to leverage learning in online education.