Modeling Computing Students’ Perceived Academic Performance in an Online Learning Environment Rex Bringula College of Computer Studies and Systems University of the East Manila, Philippines rex.bringula@ue.edu.ph Ma. Ymelda Batalla College of Computer Studies and Systems University of the East Manila, Philippines maymelda.batalla@ue.edu.ph Ma. Teresa Borebor College of Computer Studies and Systems University of the East Manila, Philippines teresa.borebor@ue.edu.ph ABSTRACT This study attempted to develop a model that characterized the perceived academic performance of computing students (subsequently referred to as students) in an online learning environment. It was hypothesized that students’ academic performance in online learning could be modeled through their online learning capabilities, attitudes towards online learning, and online learning academic self-concept. Toward this goal, 264 students answered a validated survey form. Multinomial logistic regression analyses showed that perceived academic performance in terms of perceived grade attainment and perceived learning achievements had different sets of predictors. This finding indicates that perceived academic performance in an online learning environment has two distinct measures with distinct sets of predictors. Additional analyses revealed that the students are further distinguished when the predictors were categorized by levels of academic performance. Implications to online teaching and recommendations are discussed. CCS CONCEPTS  Social and professional topics  Professional topics  Computing education  Computing education programs  Information technology education KEYWORDS ability, confidence, COVID-19, interest, self-concept ACM Reference format: Rex Bringula, Ma. Ymelda Batalla and Ma. Teresa Borebor. 2021. Modeling Computing Students Perceived Academic Performance in an Online Learning Environment. In Proceedings of the 22nd Annual Conference on Information Technology Education (SIGITE’21). ACM, New York, NY, USA, 6 pages. https://doi.org/10.1145/3450329.3476856 1 Introduction Academic self-concept (ASC) refers to “students’ interest, enjoyment, and perceptions of his/her own competency in a given academic domain” (p. 132) [28]. It indicates students’ confidence and effort exerted in a particular course [18] and shows a direct relationship between the students' exerted effort and their interest in the course [26]. However, very few studies have been conducted to understand ASC in the context of online learning [15,28]. While predictors of online learning performance were identified, it was still unclear how these predictors differed when categorized according to the different levels of academic performance. In other words, prior studies did not consider the students' different levels of academic performance in the analysis [15,28]. Thus,uncovering how predictors differ based on the academic performance of the students may lead to a more vivid understanding of online learners. This may inform educators to provide helpful supports [28] suitable to online learners with varying degrees of academic competence. To address the gap, this study developed a model of the perceived academic performance of students in an online learning environment in the light of ASC and other related factors. The model aims to provide a portrait of different online learners (i.e., computing students; subsequently referred to as students) based on significant predictors. Specifically, the study sought answers to the following questions: 1)What are the online learning capabilities of the students in terms of number of devices owned, device sharing, number of Internet access, number of Internet subscriptions, Internet speed, personal physical learning space access, and prior learning management system (LMS) usage? 2) What are the students’ attitudes towards online learning in terms of perceived ease of learning, perceived ease of passing, and perceived utility of online learning? 3) What are the online learners’ ASC in terms of abilities, interest, and academic effort? 4) How do students perceive their academic performance in an online learning environment in terms of grade and learning attainment? 5) Can perceived academic performance be modeled using online learning capabilities, attitudes towards online learning, and online ASC of students? 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