Learning Management System Acceptance Analysis Using Hedonic Motivation System Adoption Model

  • Victor Alva Andrian Rehy Universitas Kristen Satya Wacana
  • Johan J.C. Tambotoh Universitas Kristen Satya Wacana
Keywords: LMS, HMSAM, PLS-SEM, Online learning


Online learning using LMS (Learning Management System) results in demotivation for Lecturers and Students. This study aims to explore the relationship between the contentment of using LMS with the behavioural intentions and user focus while using the LMS. The present study employed the user's perception of using LMS with HMSAM (Hedonic Motivation System Adoption Model) as the theoretical basis. The quantitative research method employed a questionnaire as a data collection method. The collected data were analysed statistically using the PLS-SEM method with SmartPLS 3.2.9 application. The results of the study showed that of the 10 (ten) hypotheses, 9 (nine) were accepted, and 1 (one) was rejected. In particular, the hypothesis indicating excitement affects behavioural intentions using the LMS shows a t-statistic value of 1.887 (t-statistics < t-value) hence being rejected. This study also provides recommendations for LMS development based on usability, curiosity, excitement, and control factors. 



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L. M. C. Benavides, J. A. T. Arias, M. D. A. Serna, J. W. B. Bedoya, and D. Burgos, “Digital transformation in higher education institutions: A systematic literature review,” Sensors (Switzerland), vol. 20, no. 11, pp. 1–23, 2020, doi: 10.3390/s20113291.

M. K. Alsmadi et al., “Digitalization of learning in Saudi Arabia during the COVID-19 outbreak: A survey,” Informatics Med. Unlocked, vol. 25, no. December 2020, p. 100632, 2021, doi: 10.1016/j.imu.2021.100632.

C. Damşa, M. Langford, D. Uehara, and R. Scherer, “Teachers’ agency and online education in times of crisis,” Comput. Human Behav., vol. 121, no. March, 2021, doi: 10.1016/j.chb.2021.106793.

Y. M. Tang et al., “Comparative analysis of Student’s live online learning readiness during the coronavirus (COVID-19) pandemic in the higher education sector,” Comput. Educ., vol. 168, no. March, 2021, doi: 10.1016/j.compedu.2021.104211.

S. Dhawan, “Online Learning: A Panacea in the Time of COVID-19 Crisis,” J. Educ. Technol. Syst., vol. 49, no. 1, pp. 5–22, 2020, doi: 10.1177/0047239520934018.

D. Oluwajana, A. Idowu, M. Nat, V. Vanduhe, and S. Fadiya, “The adoption of students’ hedonic motivation system model to gamified learning environment,” J. Theor. Appl. Electron. Commer. Res., vol. 14, no. 3, pp. 156–167, 2019, doi: 10.4067/S0718-18762019000300109.

J. A. Kumar and B. Bervell, “Google Classroom for mobile learning in higher education: Modelling the initial perceptions of students,” Educ. Inf. Technol., vol. 24, no. 2, pp. 1793–1817, 2019, doi: 10.1007/s10639-018-09858-z.

S. R. Natasia, Y. T. Wiranti, and A. Parastika, “Acceptance analysis of NUADU as e-learning platform using the Technology Acceptance Model (TAM) approach,” Procedia Comput. Sci., vol. 197, no. 2021, pp. 512–520, 2021, doi: 10.1016/j.procs.2021.12.168.

V. M. Bradley, “Learning Management System (LMS) Use with Online Instruction,” Int. J. Technol. Educ., vol. 4, no. 1, p. 68, 2020, doi: 10.46328/ijte.36.

S. R. Raharjo, P. W. Handayani, and P. O. H. Putra, “Active Student Learning through Gamification in a Learning Management System,” Electron. J. e-Learning, vol. 19, no. 6, pp. 601–613, 2021, doi: 10.34190/EJEL.19.6.2089.

A. Raman, R. Thannimalai, M. Rathakrishnan, and S. N. Ismail, “Investigating the influence of intrinsic motivation on behavioral intention and actual use of technology in moodle platforms,” Int. J. Instr., vol. 15, no. 1, pp. 1003–1024, 2022, doi: 10.29333/iji.2022.15157a.

E. Chan, F. F. Nah, Q. Liu, and Z. Lu, “Effect of Gami fi cation on Intrinsic Motivation,” vol. 3, pp. 445–454, 2018, doi: 10.1007/978-3-319-91716-0.

D. M. Hull, P. B. Lowry, J. E. Gaskin, and K. Mirkovski, “A storyteller’s guide to problem-based learning for information systems management education,” Inf. Syst. J., vol. 29, no. 5, pp. 1040–1057, 2019, doi: 10.1111/isj.12234.

J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “The Results of PLS-SEM Article information,” Eur. Bus. Rev., vol. 31, no. 1, pp. 2–24, 2018.

G. Shmueli et al., “Predictive model assessment in PLS-SEM: guidelines for using PLSpredict,” Eur. J. Mark., vol. 53, no. 11, pp. 2322–2347, 2019, doi: 10.1108/EJM-02-2019-0189.

M. Sarstedt, C. M. Ringle, J. H. Cheah, H. Ting, O. I. Moisescu, and L. Radomir, “Structural model robustness checks in PLS-SEM,” Tour. Econ., vol. 26, no. 4, pp. 531–554, 2020, doi: 10.1177/1354816618823921.

A. Rizal and D. Yusup, “Integrasi Microlecture pada Kelas Virtual Berbasis 3D Virtual Learning Environment,” J. Edukasi dan Penelit. Inform., vol. 6, no. 1, p. 39, 2020, doi: 10.26418/jp.v6i1.37588.

P. Bongale, S. R. R, C. Tandon, H. Palivela, A. T. M, and N. C. R, “Effect of the Pandemic on Students’ Learning Habits in India,” no. April, pp. 1–13, 2021, doi: 10.20944/preprints202104.0725.v1.

J. F. Hair, G. T. Hult, C. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) - Joseph F. Hair, Jr., G. Tomas M. Hult, Christian Ringle, Marko Sarstedt. 2017.

R. S. Hamid and S. M. Anwar, STRUCTURAL EQUATION MODELING (SEM) BERBASIS VARIAN: Konsep Dasar dan Aplikasi dengan Program SmartPLS 3.2.8 dalam Riset Bisnis. PT Inkubator Penulis Indonesia (Institut Penulis Indonesia), 2019.

S. M. Rasoolimanesh, “Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach,” Data Anal. Perspect. J., vol. 3, no. 2, pp. 1–8, 2022.

How to Cite
Rehy, V. A. A., & Johan J.C. Tambotoh. (2022). Learning Management System Acceptance Analysis Using Hedonic Motivation System Adoption Model. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 6(6), 930 - 938. https://doi.org/10.29207/resti.v6i6.4233
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