IJIET 2026 Vol.16(1): 91-101
doi: 10.18178/ijiet.2026.16.1.2486
doi: 10.18178/ijiet.2026.16.1.2486
Augmented Reality in Computer Network Learning: How to Improve Students’ Self-Efficacy?
Ika Parma Dewi1,*, Hendra Hidayat1, Dedy Irfan1, Andi Asrifan2,
Muhammad Dhanil3, Suriani Abu Bakar4, and Asmaa Bengueddach5
1. Department of Electronic Engineering, Universitas Negeri Padang, Padang, Indonesia
2. Universitas Negeri Makasar, Makasar, Indonesia
3. Department of Physics, Faculty of Science and Mathematics, Universitas Negeri Padang, Padang, Indonesia
4. Department of Physics, Faculty of Science and Mathematics, Sultan Idris Education University, Malaysia
5. LIO Laboratory, University Oran 1-Algeria, Saudi Arabia
Email: ika_parma@ft.unp.ac.id (I.P.M.); hendra.hidayat@ft.unp.ac.id (H.H.); dedy_irf@ft.unp.ac.id (D.I.), andi.asrifan@unm.ac.id(A.A.), muhammaddhanil22@gmail.com (M.D.), suriani@fsmt.upsi.edu.my (S.A.B.), asmaa.bengueddach@univ-oran1.dz (A.B.)
*Corresponding author
2. Universitas Negeri Makasar, Makasar, Indonesia
3. Department of Physics, Faculty of Science and Mathematics, Universitas Negeri Padang, Padang, Indonesia
4. Department of Physics, Faculty of Science and Mathematics, Sultan Idris Education University, Malaysia
5. LIO Laboratory, University Oran 1-Algeria, Saudi Arabia
Email: ika_parma@ft.unp.ac.id (I.P.M.); hendra.hidayat@ft.unp.ac.id (H.H.); dedy_irf@ft.unp.ac.id (D.I.), andi.asrifan@unm.ac.id(A.A.), muhammaddhanil22@gmail.com (M.D.), suriani@fsmt.upsi.edu.my (S.A.B.), asmaa.bengueddach@univ-oran1.dz (A.B.)
*Corresponding author
Manuscript received February 19, 2025; revised March 19, 2025; accepted April 2, 2025; published January 13, 2026
Abstract—This study aims to develop and test a conceptual model comprising six hypotheses focusing on the impact of Augmented Reality (AR) on students’ academic self-efficacy. The research addresses the need to explore how AR technology can improve students’ academic self-efficacy by examining the relationships between AR technology features, task value, usage intention, and personal cognitive approach. A total of 340 students participated in this research, completing online questionnaires as part of a controlled experiment. The Structural Equation Modeling-Partial Least Square was used to assess, test, and analyze the conceptual model. The results of this study indicate that the personal cognitive approach, tech features, and task value implemented by students all positively affect their academic self-efficacy in learning. The personal cognitive approach directly contributes to influencing task values and technological features. Task value and tech features contribute to improving usage intention in students while learning with AR. The personal cognitive approach and the usage intention of use contribute directly and significantly to enhancing students’ academic self-efficacy. Overall, implementing a personal cognitive approach, tech features, task value, and usage intention positively boosted students’ academic self-efficacy in learning with AR.
Keywords—augmented reality, computer networks, self-efficacy
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—augmented reality, computer networks, self-efficacy
Cite: Ika Parma Dewi, Hendra Hidayat, Dedy Irfan, Andi Asrifan, Muhammad Dhanil, Suriani Abu Bakar, and Asmaa Bengueddach, "Augmented Reality in Computer Network Learning: How to Improve Students’ Self-Efficacy?," International Journal of Information and Education Technology, vol. 16, no. 1, pp. 91-101, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).