.png)
Applying Structural Equation Modelling for Examining the Impact of Quality Dimensions in Improving the Adoption of Digital-Learning Platforms
Abstract
Although a number of studies have proved the significance of quality characteristics in improving Digital-learning platforms success, there is few research about the impact of quality dimensions in increasing system adoption and usage. As a result, our research investigated the impact of quality indicators such as Quality of Service, quality of learning content and information, and quality of system on Digital-learning platforms usability. Quality of Service, quality of learning content and information, and quality of system characteristics were determined to be the essential components impacting Digital-learning platforms adoption among learners. The study revealed that system quality was the most critical factor influencing the perceived ease of use and usefulness of Digital-learning platforms. Information quality also had a significant impact on both perceived ease of use and usefulness. Additionally, service quality affected these usability factors as well. The findings indicate that system quality significantly influenced usability factors, specifically perceived ease of use and perceived usefulness (H1: β = 0.321; H2: β = 0.366). Additionally, service quality is found to have a significant effect on both usability factors, ease of use and usefulness (H5: β = 0.371; H6: β = 0.366). Furthermore, the results are essential in determining the importance of those quality components that can be utilized by developers in institutions of higher education to enhance their Digital-learning platforms experiences.
Keywords
Full Text:
PDFReferences
Almaiah MA, Alamri MM, Al-Rahmi W. Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. IEEE Access. 2019 Dec 2;7:174673-86.
Almaiah, M.A. Acceptance and usage of a mobile information system services in University of Jordan. Educ. Inf. Technol. 2018, 23, 1873–1895. https://doi.org/10.1007/s10639-018-9694-6.
Al Mulhem A. Investigating the effects of quality factors and organizational factors on university students’ satisfaction of e-learning system quality. Cogent Education. 2020 Jan 1;7(1):1787004.
Almaiah, M.A.; Jalil, M.M.A.; Man, M. Empirical investigation to explore factors that achieve high quality of mobile learning system based on students’ perspectives. Eng. Sci. Technol. Int. J. 2016, 19, 1314–1320. https://doi.org/10.1016/j.jestch.2016.03.004.
Al Mulhem, Ahmed. "Exploring the key factors in the use of an e-learning system among students at King Faisal University, Saudi Arabia." (2020): 19-37.
Almaiah, M.A.; Alamri, M.M. Proposing a new technical quality requirements for mobile learning applications. J. Theor. Appl. Inf. Technol. 2018, 96, 6955–6968.
S. A. Alsheibani, D. Cheung, and D. Messom, “Factors inhibiting the adoption of artificial intelligence at organizational-level: A preliminary investigation,” 2019.
Almaiah, M.A.; Al Mulhem, A. Thematic Analysis for Classifying the Main Challenges and Factors Influencing the Successful Implementation of E-Learning System Using NVivo. Int. J. Adv. Trends Comput. Sci. Eng. 2020, 9, 32–44. https://doi.org/10.30534/ijatcse/2020/22912020.
X. Chen, D. Zou, H. Xie, G. Cheng, and C. Liu, “Two Decades of Artificial Intelligence in Education,” Educ. Technol. Soc., vol. 25, no. 1, pp. 28–47, 2022.
Lutfi, A.; Alsyouf, A.; Almaiah, M.A.; Alrawad, M.; Abdo, A.A.K.; Al-Khasawneh, A.L.; Ibrahim, N.; Saad, M. Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs. Sustainability 2022, 14, 1802. https://doi.org/10.3390/su14031802.
J. C. Ho, “Disruptive innovation from the perspective of innovation diffusion theory,” Technol. Anal. Strateg. Manag., vol. 34, no. 4, pp. 363–376, 2022.
Althunibat, A.; Almaiah, M.A.; Altarawneh, F. Examining the Factors Influencing the Mobile Learning Applications Usage in Higher Education during the COVID-19 Pandemic. Electronics 2021, 10, 2676.
Lutfi, A. Factors Influencing the Continuance Intention to Use Accounting Information System in Jordanian SMEs from the Perspectives of UTAUT: Top Management Support and Self-Efficacy as Predictor Factors. Economies 2022, 10, 75. https://doi.org/10.3390/economies10040075.
G. Malik, D. K. Tayal, and S. Vij, “An analysis of the role of artificial intelligence in education and teaching,” in Recent Findings in Intelligent Computing Techniques, Springer, 2019, pp. 407–417.
N. Sandu and E. Gide, “Adoption of AI-Chatbots to enhance student learning experience in higher education in India,” in 2019 18th International Conference on Information Technology Based Higher Education and Training (ITHET), 2019, pp. 1–5.
S. F. Ahmad, M. M. Alam, M. K. Rahmat, M. S. Mubarik, and S. I. Hyder, “Academic and Administrative Role of Artificial Intelligence in Education,” Sustainability, vol. 14, no. 3, p. 1101, 2022.
M. A. Chaudhry and E. Kazim, “Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021,” AI Ethics, vol. 2, no. 1, pp. 157–165, 2022.
W. Yang, “Artificial intelligence education for young children: Why, what, and how in curriculum design and implementation,” Comput. Educ. Artif. Intell., vol. 3, p. 100061, 2022.
X. Huang, Z. O. U. Di, G. Cheng, C. Xieling, and X. I. E. Haoran, “Trends, research issues and applications of artificial intelligence in language education,” Educ. Technol. Soc., vol. 26, no. 1, 2023.
J. C. Machicao, “Artificial Intelligence as a General Resource for All Professions: Towards a Higher Education Pedagogy Framework,” in Strategy, Policy, Practice, and Governance for AI in Higher Education Institutions, IGI Global, 2022, pp. 156–180.
H. Pallathadka, B. Sonia, D. T. Sanchez, J. V De Vera, J. A. T. Godinez, and M. T. Pepito, “Investigating the impact of artificial intelligence in education sector by predicting student performance,” Mater. Today Proc., vol. 51, pp. 2264–2267, 2022.
Almaiah, M.A.; Al-Khasawneh, A.; Althunibat, A.; Almomani, O. Exploring the Main Determinants of Mobile Learning Application Usage During Covid-19 Pandemic in Jordanian Universities. In Emerging Technologies during the Era of COVID-19 Pandemic; Springer: Cham, Switzerland, 2021; pp. 275–290. https://doi.org/10.1007/978-3-030-67716-9_17.
E. M Rogers, Diffusion of innovations. The Free Press, 1983.
Mulhem, A.A.; Almaiah, M.A. A conceptual model to investigate the role of mobile game applications in education during the COVID-19 pandemic. Electronics 2021, 10, 2106.
Al Amri, M.M.; Almaiah, M.A. The use of mobile gamification technology for sustainability learning in Saudi higher education. Int. J. 2020, 9, 8236–8244.
T. Teo and L. Tan, “The theory of planned behavior (TPB) and pre-service teachers’ technology acceptance: A validation study using structural equation modeling,” J. Technol. Teach. Educ., vol. 20, no. 1, pp. 89–104, 2012.
V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Q., pp. 425–478, 2003.
Almaiah, M.A.; Almomani, O.; Al-Khasawneh, A.; Althunibat, A. Predicting the Acceptance of Mobile Learning Applications During COVID-19 Using Machine Learning Prediction Algorithms. In Emerging Technologies During the Era of COVID-19 Pandemic; Springer: Cham, Switzerland, 2021; pp. 319–332. https://doi.org/10.1007/978-3-030-67716-9_20
Al Amri, M.; Almaiah, M.A. Sustainability Model for Predicting Smart Education Technology Adoption Based on Student Perspectives. Int. J. Adv. Soft Comput. Its Appl. 2021, 13, 60-7
R. S. Al-Maroof et al., “The effectiveness of online platforms after the pandemic: will face-to-face classes affect students’ perception of their Behavioural Intention (BIU) to use online platforms?,” in Informatics, 2021, vol. 8, no. 4, p. 83.
S. A. Babatunde, M. K. Ajape, K. D. Isa, O. Kuye, E. O. Omolehinwa, and S. A. Muritala, “Ease of Doing Business Index: An Analysis of Investors Practical View,” J. Econ., vol. 17, no. 1, pp. 101–123, 2021.
Almaiah, M.A.; Al-lozi, E.M.; Al-Khasawneh, A.; Shishakly, R.; Nachouki, M. Factors Affecting Students’ Acceptance of Mobile Learning Application in Higher Education during COVID-19 Using ANN-SEM Modelling Technique. Electronics 2021, 10, 3121.
Almaiah MA, Jalil MM. Investigating Students' Perceptions on Mobile Learning Services. Int. J. Interact. Mob. Technol. 2014 Oct;8(4):31-6.
Almaiah, M.A.; Hajjej, F.; Lutfi, A.; Al-Khasawneh, A.; Shehab, R.; Al-Otaibi, S.; Alrawad, M. Explaining the Factors Affecting Students’ Attitudes to Using Online Learning (Madrasati Platform) during COVID-19. Electronics 2022, 11, 973. https://doi.org/10.3390/electronics11070973.
R. V Krejcie and D. W. Morgan, “Determining sample size for research activities,” Educ. Psychol. Meas., vol. 30, no. 3, pp. 607–610, 1970.
S. A. Salloum and K. Shaalan, “Adoption of E-Book for University Students,” in International Conference on Advanced Intelligent Systems and Informatics, 2018, pp. 481–494.
Almaiah, M.A.; Hajjej, F.; Lutfi, A.; Al-Khasawneh, A.; Alkhdour, T.; Almomani, O.; Shehab, R. A Conceptual Framework for Determining Quality Requirements for Mobile Learning Applications Using Delphi Method. Electronics 2022, 11, 788. https://doi.org/10.3390/electronics11050788.
D. Hooks, Z. Davis, V. Agrawal, and Z. Li, “Exploring factors influencing technology adoption rate at the macro level: A predictive model,” Technol. Soc., vol. 68, p. 101826, 2022.
Alsyouf, A.; Lutfi, A.; Al-Bsheish, M.; Jarrar, M.T.; Al-Mugheed, K.; Almaiah, M.A.; Alhazmi, F.N.; Masa’deh, R.E.; Anshasi, R.J.; Ashour, A. Exposure Detection Applications Acceptance: The Case of COVID-19. Int. J. Environ. Res. Public Health 2022, 19, 7307.
DOI: https://doi.org/10.47738/jads.v6i1.518
Refbacks
- There are currently no refbacks.
Journal of Applied Data Sciences
| ISSN | : | 2723-6471 (Online) |
| Publisher | : | Bright Publisher |
| Website | : | http://bright-journal.org/JADS |
| : | taqwa@amikompurwokerto.ac.id (principal contact) | |
| support@bright-journal.org (technical issues) |
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0