Predictors of Online Academic Self-Concept of Computing Students

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Annaliza E. Catacutan-Bangit, Rex P. Bringula, Saida Ulfa

2021 IEEE Region 10 Annual International Conference, Proceedings/TENCON Vol. 2021-December Conference paper Cited by 2 SDG 17SDG 4 Quartile

Abstract

This descriptive study determined the predictors that influenced the online academic self-concept of 484 computing students. It was shown the participants of this study did not experience technical barriers. However, they perceived they had an intermittent Internet connection. There was almost an equal number of participants in terms of access or lack thereof to a personal physical learning space for online classes. It was revealed they prefer to be assisted by their teachers or their classmates to understand the course content. They perceived online learning as more difficult than the face-To-face mode and they would achieve a lower grade in online learning. They had low perceptions of their abilities for coping with online learning and had a negative interest in it. Pearson correlation analysis showed academic self-concept in terms of abilities and interests had a significant moderate positive relationship with perceived online academic performance. Multiple regression analyses showed personal learning space and year level were consistent predictors of online academic self-concept. Recommendations and implications are offered. © 2021 IEEE.

Affiliations

National University, Manila, College of Computing and Information Technologies, Manila, Philippines; University of the East, College of Computer Studies and Systems, Manila, Philippines; Universitas Negeri Malang, Faculty of Education, Educational Technology Department, Malang, Indonesia

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