Hot-fit Model on E-Learning Success: Innovation and Quality Consciousness

Muhammad Sofwan; Akhmad Habibi; Robin Pratama; Mohd Sofian Omar Fauzee; Hamdy Abdullah

doi:10.24059/olj.v30i1.4861

Authors

Muhammad Sofwan Universitas Jambi
Akhmad Habibi Univeersity of Malaya
Robin Pratama Universitas Jambi
Mohd Sofian Omar Fauzee Inti University
Hamdy Abdullah Universiti Sulthan Zainal Abidin

DOI:

https://doi.org/10.24059/olj.v30i1.4861

Keywords:

Hot-fit, readiness, e-learning implementation, innovation awareness, quality awareness

Abstract

The current research elaborates on the effect of the human organization technology fit model, which consists of human, organizational, and technological dimensions, on e-learning readiness in an elementary school teacher education program. The main dataset, comprising 416 student teachers, was analyzed using partial least squares structural equation modelling procedures. The study tested hypotheses linking various factors to e-learning readiness and usage. Statistically significant results demonstrated that knowledge (p = .008), relative advantage (p < .05), compatibility (p < .05), complexity (p <.001), quality (p <.05), and innovation awareness (p < .05) significantly affect e-learning readiness and actual use of e-learning. Specifically, knowledge, relative advantage, compatibility, quality, and innovation awareness exhibit positive impacts, whereas complexity exerts a negative influence. Conversely, the findings indicated no significant relationships (p > .05) between certain correlations, such as computer self-efficacy and e-learning readiness, innovation and actual use of e-learning, and quality and actual use of e-learning. The findings contribute to the development of e-learning, providing practical and theoretical recommendations for its improvement regarding sustainable development goal 4, quality education.

References

Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating e-learning systems’ success: An empirical study. Computers in Human Behavior, 102, 67-86. https://doi.org/10.1016/j.chb.2019.08.004

Ali, B. J., & Anwar, G. (2021). Implementation of e-learning system readiness: The effect of the cost readiness on implementing e-learning. International Journal of Electrical, Electronics and Computers, 6(3), 27–37. https://doi.org/10.22161/eec.63.4

Aman, L. D. P., Sofwan, M., Mukminin, A., Habibi, A., & Yaqin, L. N. (2020). Factors affecting Indonesian pre-service teachers’ use of m-LMS: A mix method study. International Journal of Interactive Mobile Technologies, 14(6), 137–147. https://doi.org/10.3991/ijim.v14i06.12035

Apriani, E., Syafryadin, Inderawati, R., Arianti, A., Wati, S., Hakim, I. N., & Noermanzah. (2021). Implementing e-learning training toward English virtual lecturers: The process, perspectives, challenges and solutions. International Journal of Emerging Technologies in Learning, 16(4), 240–255. https://doi.org/10.3991/ijet.v16i04.14125

Ayu, M. (2020). Online learning: Leading e-learning at higher education. The Journal of English Literacy Education: The Teaching and Learning of English as a Foreign Language, 7(1), 47–54. https://doi.org/10.36706/jele.v7i1.11515

Basir, M., Ali, S., & Gulliver, S. R. (2021). Validating learner-based e-learning barriers: developing an instrument to aid e-learning implementation management and leadership. International Journal of Educational Management, 35(6), 1277–1296. https://doi.org/10.1108/IJEM-12-2020-0563

Benbya, H., Nan, N., Tanriverdi, H., & Yoo, Y. (2020). Complexity and information systems research in the emerging digital world. MIS Quarterly: Management Information Systems, 44(1), 1–17. https://doi.org/10.25300/MISQ/2020/13304

Chang, H., Varvello, M., Hao, F., & Mukherjee, S. (2021). Can you see me now?: A measurement study of Zoom, Webex, and Meet. Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC. https://doi.org/10.1145/3487552.3487847

Choi, D., Chung, C. Y., Seyha, T., & Young, J. (2020). Factors affecting organizations’ resistance to the adoption of blockchain technology in supply networks. Sustainability (Switzerland), 12(21), 8882–8895. https://doi.org/10.3390/su12218882

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

Eze, S. C., Chinedu-Eze, V. C. A., Okike, C. K., & Bello, A. O. (2020). Factors influencing the use of e-learning facilities by students in a private Higher Education Institution (HEI) in a developing economy. Humanities and Social Sciences Communications, 7(1), 1–15. https://doi.org/10.1057/s41599-020-00624-6

Fauzee, M. S. O., Zhang, S., Ishak, M., Ma, L., Hou, M., Zhang, W., Abdullah, M. N. H., Habibi, A., Singh, D. S. G., Yasin, M. H. M., & Nik, W. S. W. (2026). Enhancing academic resilience through motivation and strategy: Evidence from Malaysian boarding schools using SDT. International Journal of Evaluation and Research in Education, 15(1), 238–257. https://doi.org/10.11591/ijere.v15i1.35494

Goh, E., & Sigala, M. (2020). Integrating information & communication technologies (ICT) into classroom instruction: Teaching tips for hospitality educators from a diffusion of innovation approach. Journal of Teaching in Travel and Tourism, 20(2), 156–165. https://doi.org/10.1080/15313220.2020.1740636

Habibi, A., Mukminin, A., Octavia, A., Wahyuni, S., Danibao, B. K., & Wibowo, Y. G. (2024). ChatGPT acceptance and use through UTAUT and TPB: A big survey in five Indonesian Universities. Social Sciences & Humanities Open, 10 (101136), 1–11. https://doi.org/10.1016/j.ssaho.2024.101136

Habibi, A., Mukminin, A., & Sofyan, S. (2024). Access to the digital technology of urban and suburban vocational schools. Education and Information Technologies, 29(4). https://doi.org/10.1007/s10639-023-12006-x

Habibi, A., Sofyan, S., & Mukminin, A. (2023). Factors affecting digital technology access in vocational education. Scientific Reports, 13(1), 5682. https://doi.org/10.1038/s41598-023-32755-6

Habibi, A., Yusop, F. D., & Razak, R. A. (2020). The role of TPACK in affecting pre-service language teachers’ ICT integration during teaching practices: Indonesian context. Education and Information Technologies, 25(3), 1929–1949. https://doi.org/10.1007/s10639-019-10040-2

Hair, J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). PLS-SEM book: A Primer on PLS-SEM (3rd ed.). Sage.

Huang, T., Hochbein, C., & Simons, J. (2020). The relationship among school contexts, principal time use, school climate, and student achievement. Educational Management Administration & Leadership, 48(2), 305–323. https://doi.org/10.1177/1741143218802595

Ifinedo, E., Rikala, J., & Hämäläinen, T. (2020). Factors affecting Nigerian teacher educators’ technology integration: Considering characteristics, knowledge constructs, ICT practices and beliefs. Computers and Education, 146, 1–17. https://doi.org/10.1016/j.compedu.2019.103760

Liljenström, H. (2022). Consciousness, decision making, and volition: Freedom beyond chance and necessity. Theory in Biosciences, 141(2), 125–140. https://doi.org/10.1007/s12064-021-00346-6

Mahoney, J. L., Weissberg, R. P., Greenberg, M. T., Dusenbury, L., Jagers, R. J., Niemi, K., Schlinger, M., Schlund, J., Shriver, T. P., VanAusdal, K., & Yoder, N. (2021). Systemic social and emotional learning: Promoting educational success for all preschool to high school students. American Psychologist, 76(7), 1128–1142. https://doi.org/10.1037/amp0000701

Maphalala, M. C., & Adigun, O. T. (2020). Academics’ experience of implementing e-learning in a South African higher education institution. International Journal of Higher Education, 10(1), 1–13. https://doi.org/10.5430/ijhe.v10n1p1

Maswadi, K., Ghani, N. A., & Hamid, S. (2022). Factors influencing the elderly’s behavioural intention to use smart home technologies in Saudi Arabia. PLoS ONE, 17(8Au), 1–30. https://doi.org/10.1371/journal.pone.0272525

Mirabolghasemi, M., Choshaly, S. H., & Iahad, N. A. (2019). Using the HOT-fit model to predict the determinants of E-learning readiness in higher education: A developing Country’s perspective. Education and Information Technologies, 24, 3555–3576.

Mustafa, M. H., Ahmad, M. B., Shaari, Z. H., & Jannat, T. (2021). Integration of TAM, TPB, and TSR in understanding library user behavioral utilization intention of physical vs. E-book format. Journal of Academic Librarianship, 47(5), 1–11. https://doi.org/10.1016/j.acalib.2021.102399

Olugbara, C. T., Imenda, S. N., Olugbara, O. O., & Khuzwayo, H. B. (2020). Moderating effect of innovation consciousness and quality consciousness on intention-behavior relationship in E-learning integration. Education and Information Technologies, 25(1), 329–350. https://doi.org/10.1007/s10639-019-09960-w

Onyekwere, J., & Enamul Hoquei, K. (2023). Relationship between technological change, digitization, and students’ attitudes toward distance learning in Lagos Higher Education institutes. Innoeduca. International Journal of Technology and Educational Innovation, 9(1), 126–142. https://doi.org/10.24310/innoeduca.2023.v9i1.15286

Panigrahi, R., Srivastava, P. R., & Panigrahi, P. K. (2021). Effectiveness of e-learning: the mediating role of student engagement on perceived learning effectiveness. Information Technology and People, 34(7), 1840–1862. https://doi.org/10.1108/ITP-07-2019-0380

Polat, E., Hopcan, S., & Yahşi, Ö. (2022). Are K-12 teachers ready for e-learning? International Review of Research in Open and Distance Learning, 23(2), 214–241. https://doi.org/10.19173/irrodl.v23i2.6082

Pratama, H., Azman, M. N. A., Kassymova, G. K., & Duisenbayeva, S. S. (2020). The trend in using online meeting applications for learning during the period of pandemic Covid-19: A literature review. Journal of Innovation in Educational and Cultural Research, 1(2), 28–68. https://doi.org/10.46843/jiecr.v1i2.15

Prifti, R. (2022). Self–efficacy and student satisfaction in the context of blended learning courses. Open Learning, 37(2), 111–125. https://doi.org/10.1080/02680513.2020.1755642

Purwanto, E., & Tannady, H. (2020). The factors affecting intention to use Google Meet amid online meeting platform competition in Indonesia. Technology Reports of Kansai University, 62(6), 2829–2839.

Qoriawan, T., & Apriliyanti, I. D. (2023). Exploring connections within the technology-based entrepreneurial ecosystem (EE) in emerging economies: understanding the entrepreneurship struggle in the Indonesian EE. Journal of Entrepreneurship in Emerging Economies, 15(2), 301–332. https://doi.org/10.1108/JEEE-02-2021-0079

Rahman, M. M., Lesch, M. F., Horrey, W. J., & Strawderman, L. (2017). Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accident Analysis and Prevention, 108, 361–372. https://doi.org/10.1016/j.aap.2017.09.011

Ramadiani, Azainil, Hidayanto, A. N., Khairina, D. M., & Jundillah, M. L. (2020). Teacher and student readiness using e-learning and m-learning. Bulletin of Electrical Engineering and Informatics, 9(3), 1176–1182. https://doi.org/10.11591/eei.v9i3.2006

Rejón-Guardia, F., Polo-Peña, A. I., & Maraver-Tarifa, G. (2020). The acceptance of a personal learning environment based on Google apps: The role of subjective norms and social image. Journal of Computing in Higher Education, 32(2), 2023–233. https://doi.org/10.1007/s12528-019-09206-1

Rocca, L., Veneziani, M., & Carini, C. (2023). Mapping the diffusion of circular economy good practices: Success factors and sustainable challenges. Business Strategy and the Environment, 32(4), 2035–2048. https://doi.org/10.1002/bse.3235

Santos, G., Marques, C. S., Justino, E., & Mendes, L. (2020). Understanding social responsibility’s influence on service quality and student satisfaction in higher education. Journal of Cleaner Production, 256, 1–10. https://doi.org/10.1016/j.jclepro.2020.120597

Sattin, D., Magnani, F. G., Bartesaghi, L., Caputo, M., Fittipaldo, A. V., Cacciatore, M., Picozzi, M., & Leonardi, M. (2021). Theoretical models of consciousness: A scoping review. Brain Sciences, 11(5), 1–58 . https://doi.org/10.3390/brainsci11050535

Şimşek, A. S., & Ateş, H. (2022). The extended technology acceptance model for Web 2.0 technologies in teaching. Innoeduca. International Journal of Technology and Educational Innovation, 8(2). https://doi.org/10.24310/innoeduca.2022.v8i2.15413

Sivagurunathan, R., Senathirajah, A. R. B. S., Ramasamy, G., Isa, M. B. M., Haque, R., Chanjin, Y., & Sivagurunathan, L. (2024). A study on development of educational leadership program using equine assisted experiential learning. Eurasian Journal of Educational Research, (112), 1–14. https://doi.org/10.14689/ejer.2024.112.01

Sofwan, M., Habibi, A., Attar, R. W., Alqahtani, T. M., Alahmari, S. A., & Alhazmi, A. H. (2024). Factors affecting teachers’ behavior of innovative teaching with technology: Structural equation modelling. Sustainability, 16(19), 8496–8509. https://doi.org/10.3390/su16198496

Sofwan, M., Yaakob, M. F. M., & Habibi, A. (2024). Technological, pedagogical, and content knowledge for technology integration: A systematic literature review. International Journal of Evaluation and Research in Education (IJERE), 13(1), 212–222. https://doi.org/10.11591/ijere.v13i1.26643

Tabandeh, A., Jia, G., & Gardoni, P. (2022). A review and assessment of importance sampling methods for reliability analysis. Structural Safety, 97, 1–18. https://doi.org/10.1016/j.strusafe.2022.102216

Toufaily, E., Zalan, T., & Dhaou, S. Ben. (2021). A framework of blockchain technology adoption: An investigation of challenges and expected value. Information and Management, 58(3), 1–17. https://doi.org/10.1016/j.im.2021.103444

Turnbull, D., Chugh, R., & Luck, J. (2021). Transitioning to E-Learning during the COVID-19 pandemic: How have higher education institutions responded to the challenge? Education and Information Technologies, 26(5), 6401–6419. https://doi.org/10.1007/s10639-021-10633-w

Yuanjue, Y., Senathirajah, A. R. B. S., Ramasamy, G., Qazi, S. Z., Fauzee, M. S. O., Haque, R., & Lertatthakornkit, T. (2025). Sports products and services: Technological acceptance and psychological factors influencing online purchase behavior amongst university students. WSEAS Transactions on Business and Economics, 22, 2444–2455. https://doi.org/10.37394/23207.2025.22.192

Wang, G., Tan, G. W. H., Yuan, Y., Ooi, K. B., & Dwivedi, Y. K. (2022). Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis. Technological Forecasting and Social Change, 175, 1–15. https://doi.org/10.1016/j.techfore.2021.121345