Acceptance of E-learning Technology by Using the Technology Acceptance Model (TAM) Method
DOI:
https://doi.org/10.51601/ijse.v5i3.209Abstract
The main aim of the study is to investigate the relationship between the variables included in the Technology Acceptance Model (TAM), and the core variables and the extended variables of the TAM. The research method is a quantitative research that tests hypotheses derived from variables extracted from the Technology Acceptance Model (TAM), which include the variables of perceived ease of use, perceived usefulness, attitude towards use, actual use, e-learning self- efficiency, and a set of variables. complexity To test the relationship between each variable, this study uses statistical tests using structural equation modeling (SEM) application tools SmartPLS. The results of the research hypothesis are (H1) the positive effect of e-learning self-efficacy (learning self-efficacy online) on the perception of comfort (perceived ease of use). (H2) positive effect of e-learning self-efficacy on perceived usefulness (perceived usefulness), (H3) positive effect of complexity on perceived ease of use. (H4) complexity has a positive effect on perceived usefulness. (H5) perception of ease of use (perceived ease of use) the use of e-learning affects the attitude to use (attitude to use). (H6) view of usefulness (perceived usefulness) positive effect of e-learning on usage attitude (attitude towards usage). (H7) perceived ease (perceived ease of use) negative effect on actual use e-learning (actual use). (H8) perceived usefulness of e-learning (perceived usefulness) positively affects actual use (actual use). (H9) usage attitude (attitude towards usage) positive effect on actual usage (actual usage). The practical implication of the research include conducting an extension study of external TAM variables, conducting a study with different objects and subjects and conducting a pretest of the samples to be studied in the prior to the research.
Downloads
References
G. Vial, “Understanding digital transformation: A review and a research agenda,” The Journal of Strategic Information Systems, vol. 28, no. 2, pp. 118–144, 2019, doi: https://doi.org/10.1016/j.jsis.2019.01.003.
J. Kern, “The Digital Transformation of Logistics,” in The Digital Transformation of Logistics, Wiley, 2021, pp. 361–403. doi: 10.1002/9781119646495.ch25.
J. R. Saura, M. Skare, and S. Ribeiro-Navarrete, “How Does Technology Enable Competitive Advantage? Reviewing State of the Art and Outlining Future Directions,” Journal of Competitiveness, vol. 14, no. 4, pp. 172–188, 2022, doi: https://doi.org/10.7441/joc.2022.04.10.
H. D. Sundari and P. Utomo, “Five E-Learning for Education in Indonesia,” in Proceedings of the International Conference on Online and Blended Learning 2019 (ICOBL 2019), Paris, France: Atlantis Press, 2020. doi: 10.2991/assehr.k.200521.010.
A. Johnson, “eLearning Industry. Retrieved from The Transformative Impact Of eLearning: Embracing The Digital Classroom.” [Online]. Available: https://elearningindustry.com/transformative-impact-of-elearning-embracing-the-digital-classroom
L. Shahmoradi, V. Changizi, E. Mehraeen, A. Bashiri, B. Jannat, and M. Hosseini, “The challenges of E-learning system: Higher educational institutions perspective,” J Educ Health Promot, vol. 7, no. 1, p. 116, 2018, doi: 10.4103/jehp.jehp_39_18.
W. A. Harsanto, N. Matondang, and R. P. Wibowo, “The Use of Technology Acceptance Model (TAM) to Analyze Consumer Acceptance Towards E-Commerce Websites. A Case of the Plantage.id Digital Transformation Solution,” Journal of Environmental and Development Studies, vol. 4, no. 2, pp. 206–213, Sep. 2023, doi: 10.32734/jeds.v4i2.13144.
Venkatesh, Morris, Davis, and Davis, “User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly, vol. 27, no. 3, p. 425, 2003, doi: 10.2307/30036540.
V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly, vol. 23, no. 3, p. 425, 2003, doi: doi:10.2307/30036540.
F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, vol. 13, no. 3, pp. 319–340, 1989, doi: https://doi.org/10.2307/249008.
Y. Lee, K. A. Kozar, and K. R. T. Larsen, “The Technology Acceptance Model: Past, Present, and Future,” Communications of the Association for Information Systems, vol. 12, 2003, doi: 10.17705/1CAIS.01250.
V. Venkatesh and F. D. Davis, “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Manage Sci, vol. 46, no. 2, pp. 188–204, 2000.
M. McCord, “Technology Acceptance Model,” in Handbook of Research on Electronic Surveys and Measurements, IGI Global, 2007, pp. 306–308. doi: 10.4018/978-1-59140-792-8.ch038.
F. D. Davis, A Technology Acceptance Model for Empirically Testing New-end User Information Systems: Theory and Result, Unpublishe. Sloan: Sloan School of Management, 1986.
N. Charness and W. R. Boot, “‘Technology, Gaming, and Social Networking,’” in In Handbook of the Psychology of Aging, Elsevier, 2016, pp. 389–407.
P. de C. Fiorini, B. M. R. P. Seles, C. J. C. Jabbour, E. B. Mariano, and A. B. L. de S. Jabbour, “Management theory and big data literature: From a review to a research agenda,” Int J Inf Manage, vol. 43, pp. 112–129, 2018, doi: https://doi.org/10.1016/j.ijinfomgt.2018.07.005.
F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, vol. 13, no. 3, p. 319, Sep. 1989, doi: 10.2307/249008.
E. Karahanna, D. W. Straub, and N. L. Chervany, “Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs,” MIS Quarterly, vol. 23, no. 2, p. 183, Jun. 1999, doi: 10.2307/249751.
G. B. Davis, Kerangka Dasar Sistem Informasi Manajemen. Jakarta: PT. Pustaka Binaman Pressindo, 1993.
N. Ramdhani, “Model Perilaku Penggunaan Tik ‘NR2007’ Pengembangan dari Technology Acceptance Model (TAM),” BULETIN PSIKOLOGI, vol. 17, no. 1, pp. 17–27, 2009, [Online]. Available: https://pdfcoffee.com/model-perilaku-penggunaan-tik-nr2007- pengembangan-dari-technology-acceptance-model-tam-pdf-free.html.
R. G. Saade, F. Nebebe, and W. Tan, “Viability of the ‘Technology Acceptance Model’ in Multimedia Learning Environments: A Comparative Study,” Interdisciplinary Journal of Knowledge and Learning Objects, vol. 37, pp. 175–184, 2007.
N. Tangke, “Analisa Penerimaan Penerapan Tehnik Audit Berbatuan Komputer (TABK) dengan menggunakan Technology Acceptance Model (TAM) pada Badan Pemeriksaan Keuangan (BPK) RI,” Journal Akuntanasi Keuangan, vol. 6, no. 1, pp. 10–28, 2004.
H. M. Jogiyanto, Sistem Informasi Keperilakuan. Edisi Revisi. Yogyakarta: ANDI, 2008.
F. Nasution, ,Use of Technology Based on Behavioral Aspects. Behavioral Aspects. USU Digital Library, 2004.
Y. Li, “Empirical Study of Influential Factors of Online Customers’ Repurchase Intention,” iBusiness, vol. 08, no. 03, pp. 48–60, 2016, doi: 10.4236/ib.2016.83006.
Y. Malhotra and D. Galletta, “Extending the Technology Acceptance Model to Account for Social Influence: Theoritical Bases and Empirical Validationn,” Proccedinngs of the 32th Hawaii International Conference on System Sciences., 1999.
M. Tan and T. S. H. Teo, “Factors Influencing The Adoption of Internet Bangking,” Journal of the Assocation for Information System, vol. 1, no. 5, pp. 1–42, 2000.
Y. Lee, K. A. Kozar, and K. R. Larsen, “The Technology Acceptance Model: Past, Present, and Future,” Communications of the Association for Information Systems, vol. 12, no. 50, pp. 752–780, 2003, doi: DOI:10.17705/1CAIS.01250.
M. F. Hill, T., Smith, N. D., and Mann, Communicating innovations: Convincing computer phobics to adopt innovative technologies. In R. J. Lutz. 1986.
A. Ferdinand, Structural Equation Modeling Dalam Penelitian Manajemen Edisi Ketiga. Semarang: Badan Penerbit Universitas Diponegoro, 2005.
S. Santoso, Structural Equation Modelling: Konsep dan Aplikasi dengan AMOS. Jakarta: Alex Media Komputindo, 2007.
I. dan H. L. Ghozali, “Partial Least Squares Konsep Teknik dan Aplikasi dengan Program Smart PLS 3.0. Semarang:,” Universitas Diponogoro, Semarang, 2015.
S. Abdullah and T. E. Sutanto, Statistika Tanpa Stress. Jakarta: Transmedia Pustaka, 2015.
H. M. Jogiyanto, Concepts and Applications of Variant-Based Structural Equation Modeling in ResearchUPP. Yogyakarta: STIM YKPN, Yogyakarta, 2011.
et. al Hair, J. F, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM),. new york: SAGE Publications, 2017.
J. C. Hong, M. Y. Hwang, C. K. Wang, T. F. Hsu, Y. J. Chen, and C. H. Chan, “Effect of self-worth and parenting style on the planned behavior in an online moral game,” Turkish Online Journal of Educational Technology, vol. 10, no. 2, pp. 82–90, 2011.
W. W. Chin, B. L. Marcolin, and P. R. Newsted, “A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study,” Information Systems Research, vol. 14, no. 2, pp. 189–217, Jun. 2003, doi: 10.1287/isre.14.2.189.16018.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Ibrahim Hasan, Sait Abdullah, Darojat Tubagus Ahmad
This work is licensed under a Creative Commons Attribution 4.0 International License.
