Socio-demographics, access to technological resources, and preferred online learning attributes of senior high school learners

Using quantitative study, the researcher examined the senior high school learners’ socio-demographic characteristics and access to technological resources, preferred online learning attributes, and their segmentation. Using Cochran's formula and disproportionate stratified random sampling technique, 300 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 the 16 profiles with 2 holdouts generated by the orthogonal design using a 5-point Likert scale through online. The raw dataset was analyzed using descriptive statistics and multivariate tools such as conjoint analysis and cluster analysis to answer the research questions of the study through SPSS 22.0. More so, the clustered dataset was the result of the cluster analysis and it was used to profile and determine the preferences of each segment. The SPSS 22.0 outputs were analyzed and interpreted to delineate definitive conclusions on how to leverage online learning based on learners' preferences and segmentation.