Perceived Usefulness, Hedonic Motivation, and Gamification in the Adoption of MOOCs for Teacher Training

Authors

DOI:

https://doi.org/10.32870/Ap.v17n2.2641

Keywords:

Educational Training, Educational Technology, MOOCs, Gamification

Abstract

A theoretical model was proposed and validated, whereby the Technology Acceptance Model (TAM), the Information Systems Success Model (ISSM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) were integrated, and additional variables such as trust and gamification were incorporated. The objective was to analyze the factors that influence the use of Massive Open Online Courses (MOOCs) for the training of educational personnel in Tamaulipas, Mexico. A total of 470 surveys were collected and the proposed model was evaluated using the partial least squares structural equation modeling technique (PLS-SEM). The results revealed that perceived usefulness, hedonic motivation, and gamification significantly influence the use of MOOCs, highlighting the importance of offering courses that are functional, engaging, and socially integrated. From a theoretical perspective, the research model demonstrated the feasibility of assessing MOOC quality in an integrated manner, contributing to the literature on educational quality and technology acceptance. On a practical level, actionable practices were suggested for the design of effective courses focused on quality, enjoyment, and user engagement, thereby strengthening the professional competencies of educational staff and promoting continuous training for higher-quality education

Author Biography

  • Demian Abrego-Almazán, Autonomous University of Tamaulipas

    Demian Abrego-Almazán (dabrego@uat.edu.mx, Teléfono: 834-31-8-18-00, Extensión: 2417, CP: 87100, CVU: 246856). Es Doctor en Ciencias Administrativas por la Universidad Autónoma de Tamaulipas (UAT), México. Actualmente, es profesor de tiempo completo en la UAT, donde imparte clases en licenciatura, maestría y doctorado.

    En el ámbito de la divulgación científica, ha publicado artículos en revistas de alto impacto a nivel nacional e internacional. Además, es coautor de ponencias, libros y capítulos de libros enfocados en tecnologías, sistemas de información, administración estratégica y estadística multivariante.

    Desde 2017, forma parte del Sistema Nacional de Investigadores del CONACYT (nivel 2).

References

Ahmad, S., Bhatti, S., & Hwang, Y. (2020). E-service quality and actual use of e-banking: Explanation through the Technology Acceptance Model. Information Development, 36(4), 503-519. doi:https://doi.org/10.1177/0266666919871611

Alalwan, A., Dwivedi, Y., & Rana, N. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110. doi:https://doi.org/10.1016/j.ijinfomgt.2017.01.002

Al-Azawei, A., & Alowayr, A. (2020). Predicting the intention to use and hedonic motivation for mobile learning: A comparative study in two Middle Eastern countries. Technology in Society, 62, 101325. doi:https://doi.org/10.1016/j.techsoc.2020.101325

Albashrawi, M., & Motiwalla, L. (2020). An integrative framework on mobile banking success. Information Systems Management, 37(1), 16-32. doi:https://doi.org/10.1080/10580530.2020.1696530

Aldholay, A., Abdullah, Z., Isaac, O., & Mutahar, , A. (2020). Perspective of Yemeni students on use of online learning: Extending the information systems success model with transformational leadership and compatibility. Information Technology & People, 33(1), 106-128. doi:https://doi.org/10.1108/itp-02-2018-0095

AlHamad, M., Akour, I., Alshurideh, M., Al-Hamad, A., Kurdi, B., & Alzoubi, H. (2021). Predicting the intention to use google glass: A comparative approach using machine learning models and PLS-SEM. International Journal of Data and Network Science, 5(3), 311-320. doi:https://doi.org/10.5267/j.ijdns.2021.6.002

Alrwashdeh, M., Jahmani, A., Ibrahim, B., & Aljuhmani, H. (2020). Data to model the effects of perceived telecommunication service quality and value on the degree of user satisfaction and e-WOM among telecommunications users in North Cyprus. Data in brief, 28, 104981. doi:https://doi.org/10.1016/j.dib.2019.104981

Alshurideh, M., Salloum, S., Al Kurdi, B., Monem, A., & Shaalan, K. (2019). Understanding the Quality Determinants that Influence the Intention to Use the Mobile Learning Platforms: A Practical Study. International Journal of Interactive Mobile Technologies, 13(11), 157-183. doi:https://doi.org/10.3991/ijim.v13i11.10300

Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3), e13751. https://doi.org/10.1016/j.heliyon.2023.e13751

Alyoussef, I. (2022). Acceptance of a flipped classroom to improve university students’ learning: An empirical study on the TAM model and the unified theory of acceptance and use of technology (UTAUT). Heliyon, 8(12), e12529. doi:https://doi.org/10.1016/j.heliyon.2022.e12529

Ameen, A., Al-Ali, D., Mohammed, F., Isaac, O., Alrajawy, I., & Younis, D. (2021). The moderation effect of innovativeness on the relationship between overall quality and actual usage of smart government. Journal of System and Management Sciences, 11(1), 141-154. doi:https://doi.org/10.33168/jsms.2021.0109

Aparicio, M., Costa, C., & Moises, R. (2021). Gamification and reputation: key determinants of e-commerce usage and repurchase intention. Heliyon, 7(3), e06383. doi:https://doi.org/10.1016/j.heliyon.2021.e06383

Aparicio, M., Oliveira, T., Bacao, F., & Painho, M. (2019). Gamification: A key determinant of massive open online course (MOOC) success. Information & Management, 56(1), 39-54. doi:https://doi.org/10.1016/j.im.2018.06.003

Arfi, W., Nasr, I., Kondrateva, G., & Hikkerova, L. (2021). The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context. Technological Forecasting and Social Change, 167, 120688. doi:https://doi.org/10.1016/j.techfore.2021.120688

Çera, G., Pagria, I., Khan, K., & Muaremi, L. (2020). Mobile banking usage and gamification: the moderating effect of generational cohorts. Journal of Systems and Information Technology, 22(3), 243-263. doi:https://doi.org/10.1108/jsit-01-2020-0005

Cha, S. (2020). Customers’ intention to use robot-serviced restaurants in Korea: relationship of coolness and MCI factors. International Journal of Contemporary Hospitality Management., 32(9), 2947–2968. doi:https://doi.org/10.1108/ijchm-01-2020-0046

Chen, C., & Tsai, J. (2019). Determinants of behavioral intention to use the Personalized Location-based Mobile Tourism Application: An empirical study by integrating TAM with ISSM. Future Generation Computer Systems, 96, 628-638. doi:https://doi.org/10.1016/j.future.2017.02.028

Chin, W. (2009). How to Write Up and Report PLS Analyses. Handbook of Partial Least Squares, 655–690. https://doi.org/10.1007/978-3-540-32827-8_29

Davis, F. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral Dissertation, Massachusetts Institute of Technology.

DeLone, W., & McLean, E. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30. doi:https://doi.org/10.1080/07421222.2003.11045748

Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: defining" gamification". Proceedings of the 15th international academic MindTrek conference: Envisioning future media environments (págs. 9-15). New York, NY: ACM Press. doi:https://doi.org/10.1145/2181037.2181040

Dhahak, K., & Huseynov, F. (2020). The Influence of Gamification on Online Consumers' Attitude and Intention to Purchase Fast Moving Consumer Goods. Business & Economics Research Journal, 11(3), 769-791. doi:https://doi.org/10.20409/berj.2020.281

Gu, W., Xu, Y., & Sun, Z. (2021). Does MOOC quality affect users’ continuance intention? Based on an integrated model. Sustainability, 13(22), 12536. doi:https://doi.org/10.3390/su132212536

Gupta, P., Prashar, S., Vijay, T., & Parsad, C. (2021). Examining the influence of antecedents of continuous intention to use an informational app: the role of perceived usefulness and perceived ease of use. International Journal of Business Information Systems, 36(2), 270-287. doi:https://doi.org/10.1504/ijbis.2021.112829

Hair, J., Hult, G., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd Edition. Thousand Oaks, CA.: Sage Publications Inc.

Hair, J., Sarstedt, M., Ringle, C., & Gudergan, S. (2023). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications, Inc.

Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135. doi:https:// 10.1007/s11747-014-0403-8

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. New Challenges to International Marketing, 277–319. https://doi.org/10.1108/s1474-7979(2009)0000020014

Hubert, M., Blut, M., Brock, C., Backhaus, C., & Eberhardt, T. (2017). Acceptance of smartphone‐based mobile shopping: Mobile benefits, customer characteristics, perceived risks, and the impact of application context. Psychology & Marketing, 34(2), 175-194. doi:https://doi.org/10.1002/mar.20982

Izkair, A., & Lakulu, M. (2023). Model of intention and actual use mobile learning in higher education institutions in Iraq. Indonesian Journal of Electrical Engineering and Computer Science, 30(2), 1250. doi:https://doi.org/10.11591/ijeecs.v30.i2.pp1250-1258

Kanaan, A., AL-Hawamleh, A., Abulfaraj, A., Al-Kaseasbeh, H., & Alorfi, A. (2023). The effect of quality, security and privacy factors on trust and intention to use e-government services. International Journal of Data and Network Science, 7(1), 185-198. doi:https://doi.org/10.5267/j.ijdns.2022.11.004

Lambert, S. (2020). Do MOOCs contribute to student equity and social inclusion? A systematic review 2014–18. Computers & Education, 145, 103693. doi:https://doi.org/10.1016/j.compedu.2019.103693

Mariani, M., Styven, M., & Teulon, F. (2021). Explaining the intention to use digital personal data stores: An empirical study. Technological Forecasting and Social Change, 166, 120657. doi:https://doi.org/10.1016/j.techfore.2021.120657

Martins, J., Branco, F., Gonçalves, R., Au-Yong-Oliveira, M., Oliveira, T., Naranjo-Zolotov, M., & Cruz-Jesus, F. (2019). Assessing the success behind the use of education management information systems in higher education. Telematics and Informatics, 38, 182-193. doi:https://doi.org/10.1016/j.tele.2018.10.001

Martono, S., Nurkhin, A., Mukhibad, H., Anisykurlillah, I., & Wolor, C. (2020). Understanding the employee’s intention to use information system: Technology acceptance model and information system success model approach. The Journal of Asian Finance, Economics and Business, 7(10), 1007-1013. doi:https://doi.org/10.13106/jafeb.2020.vol7.no10.1007

Mesuwini, J., & Mokoena, S. (2024). Exploring Online Teaching and Learning Challenges for the Technical and Vocational Education and Training Lecturer. Journal of Education and e-Learning Research, 11(1), 193-202. https://doi.org/10.20448/jeelr.v11i1.5423

Rakhmawati, H., & Rusydi, M. (2020). Influence of TAM and UTAUT models of the use of e-filing on tax compliance. International Journal of Research in Business and Social Science, 9(1), 106-111. doi:https://doi.org/10.20525/ijrbs.v9i1.576

Rezvani, S., Heidari, S., Roustapisheh, N., & Dokhanian, S. (2022). The effectiveness of system quality, habit, and effort expectation on library application use intention: the mediating role of perceived usefulness, perceived ease of use, and user satisfaction. . International Journal of Business Information Systems, 1(1), 1-18. doi:https://doi.org/10.1504/ijbis.2022.10049515

Ringle, Christian, M., Wende, Sven, & Becker, J.-M. (2024). SmartPLS 4. Bönningstedt: SmartPLS. Obtenido de https://www.smartpls.com

Rosa-Castillo, A., García-Pañella, O., Maestre-Gonzalez, E., Pulpón-Segura, A., Roselló-Novella, A., & Solà-Pola, M. (2022). Gamification on Instagram: Nursing students' degree of satisfaction with and perception of learning in an educational game. Nurse Education Today, 118, 105533. doi:https://doi.org/10.1016/j.nedt.2022.105533

Salloum, S., Alhamad, A., Al-Emran, M., Monem, A., & Shaalan, K. (2019). Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access, 7, 128445–128462. doi:https://doi.org/10.1109/access.2019.2939467

Sarabadani, J., Jafarzadeh, H., & ShamiZanjani, M. (2017). Towards understanding the determinants of employees' E-learning adoption in workplace: a unified theory of acceptance and use of technology (UTAUT) View. International Journal of Enterprise Information Systems (IJEIS), 13(1), 38-49. doi:https://doi.org/10.4018/ijeis.2017010103

Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce . International Journal of Information Management, 286-301. doi:https://doi.org/10.1016/j.ijinfomgt.2019.08.008

Sarstedt, M., Hair Jr, J., Cheah, J., Becker, J., & Ringle, C. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal, 27(3), 197-211. doi:https://doi.org/10.1016/j.ausmj.2019.05.003

Schettino, G., & Capone, V. (2022). Learning design strategies in MOOCs for physicians’ training: a scoping review. International journal of environmental research and public health, 19(21), 14247. doi:https://doi.org/10.3390/ijerph192114247

SEP. (2024). Principales cifras del sistema educativo nacional 2023-2024. https://www.planeacion.sep.gob.mx/Doc/estadistica_e_indicadores/principales_cifras/principales_cifras_2023_2024_bolsillo.pdf

Shahzad, K., Zhang, Q., & Khan, M. (2024). Blockchain technology adoption in supply chain management: an investigation from UTAUT and information system success model. International Journal of Shipping and Transport Logistics, 18(2), 165-190. doi:https://doi.org/10.1504/ijstl.2024.137893

Silic, M., & Ruf, C. (2018). The effects of the elaboration likelihood model on initial trust formation in financial advisory services. International Journal of Bank Marketing, 36(3), 572–590. doi:https://doi.org/10.1108/IJBM-02-2017-0038.

To, A., & Trinh, T. (2021). Understanding behavioral intention to use mobile wallets in vietnam: Extending the tam model with trust and enjoyment. Cogent Business & Management, 8(1), 1-14. doi:https://doi.org/10.1080/23311975.2021.1891661

Ucha, C. (2023). Role of course relevance and course content quality in MOOCs acceptance and use. Computers and Education Open, 5, 100147. doi:https://doi.org/10.1016/j.caeo.2023.100147

Usman, H., Mulia, D., Chairy, C., & Widowati, N. (2022). Integrating trust, religiosity and image into technology acceptance model: the case of the Islamic philanthropy in Indonesia. Journal of Islamic Marketing, 13(2), 381-409. doi:https://doi.org/10.1108/jima-01-2020-0020

Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. doi:https://doi.org/10.2307/41410412

Xu, F., & Du, J. (2018). Factors influencing users’ satisfaction and loyalty to digital libraries in Chinese universities. Computers in Human Behavior, 83, 64-72. doi:https://doi.org/10.1016/j.chb.2018.01.029

Yang, Q., & Lee, Y. (2021). The critical factors of student performance in MOOCs for sustainable education: a case of Chinese universities. Sustainability, 13(14), 8089. doi:https://doi.org/10.3390/su13148089

Zheng, H., Qian, Y., Wang, Z., & Wu, Y. (2023). Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA. Sustainability, 15(6), 5557. doi:https://doi.org/10.3390/su15065557

Zhu, M., Sari, A., & Lee, M. (2018). A systematic review of research methods and topics of the empirical MOOC literature (2014–2016). The Internet and Higher Education, 37, 31-39. doi:https://doi.org/10.1016/j.iheduc.2018.01.002

Published

2025-09-30