Search for a command to run...
Limited studies were conducted on academic self-concept (ACS) in pure online remote learning classes. This leaves a gap in the literature on how online academic self-concept could be utilized to create an environment conducive to emergency remote online learning. The purpose of this study is to develop a multinomial logistic regression model (subsequently referred to as the model) that can characterize ACS in terms of the perceived academic performance of students in an online learning setting. Understanding the different types of learners in an online learning environment is important because it informs educators and the institution in the development of tailored policies and interventions to satisfy individual requirements, increase engagement, and improve learning results. Furthermore, the developed model can serve as a foundation for identifying specific areas where students may require additional assistance, particularly while introducing online learning during the COVID-19 epidemic. 501 randomly selected students from six colleges of one university in Manila participated in the study. Survey forms created in Google Forms were distributed through the official learning management system of the university. A multinomial logistic regression was employed to determine which of the variables of the student profiles, online learning readiness, attitudes toward online learning, and online academic self-concept could be used to model the perceived online learning academic performance of students in terms of perceived learning and perceived grade achievement. Sex, perceived ease of learning, ability, and interest were the common predictors of perceived learning and grade achievement. Meanwhile, Internet speed and perceived utility are unique predictors of perceived grade achievement, while the major of the students is a unique predictor of perceived learning. The reduced models of multinomial logistic analysis disclosed that different predictors could differentiate the students’ perceived academic performance. Thus, the hypothesized variables in the study partially explain the perceived academic performance of the students. It can also be concluded that perceived grade achievement and learning are two distinct indicators of academic performance in an online learning environment. Implications are offered.