Mobile Learning Adoption: Using Composite Model Measurement Invariance to Assess Gender Differences

Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179–211

Al-Adwan, A. S., Al-Madadha, A., & Zvirzdinaite, Z. (2018). Modeling students' readiness to adopt mobile learning in higher education: An empirical study. International Review of Research in Open and Distributed Learning, 19 (1), 222-241

Alowayr, A. (2021). Determinants of mobile learning adoption: extending the unified theory of acceptance and use of technology (UTAUT). International Journal of Information and Learning Technology. 39(1), 1-12. https://doi.org/10.1108/IJILT-05-2021-0070

Alrajawy, I., Isaac, O., Ghosh, A., Nusari, M., Al-Shibami, A. H., & Ameen, A. (2018). Determinants of student's intention to use mobile learning in Yemeni public universities: Extending the technology acceptance model (TAM) with anxiety. International Journal of Management and Human Science (IJMHS), 2(2), 1–9.

Amirian, P., & Basiri, A. (2016). Landmark-based pedestrian navigation using augmented reality and machine learning. Progress in Cartography: EuroCarto 2015, 451-465.

Ananto, P., & Ningsih, S. K. (2020). Incorporation of smartphones and social media to promote mobile learning in an Indonesian vocational higher education setting. International Journal of Interactive Mobile Technologies, 14(19), 66–81.

Arkorful, V., & Abaidoo, N. (2015). The role of e-learning, advantages and disadvantages of its adoption in higher education. International journal of instructional technology and distance learning, 12(1), 29-42.

Asabere, N. Y. (2013). Benefits and challenges of mobile learning implementation: Story of developing nations. International Journal of Computer Applications, 73(1), 23-27.

Asabere, N. Y., Acakpovi, A., Torgby, W., Sackey, J. Y. A., & Kwaikyi, S. (2019). Exploiting the adoption and implementation of electronic learning in a technical university in Ghana. International Journal of Online Pedagogy and Course Design (IJOPCD), 9(4), 44-67.

Azizi, S. M., & Khatony, A. (2019). Investigating factors affecting on medical sciences students' intention to adopt mobile learning. BMC Medical Education, 19 (1), 1–10.

Bali, S., & Liu, M. C. (2018, November). Students’ perceptions toward online learning and face-to-face learning courses. In Journal of Physics: Conference Series (110(1), 012094. IOP Publishing.

Bao, Y., Xiong, T., Hu, Z., & Kibelloh, M. (2013). Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption. Journal of Educational Computing Research, 49 (1), 111–132. https://doi.org/10.2190/EC.49.1.e

Binyamin, S. S., Rutter, M. J., & Smith, S. (2020). The moderating effect of gender and age on the students' acceptance of learning management systems in Saudi higher education. Knowledge Management and E-Learning, 12(1), 30–62. https://doi.org/10.34105/j.kmel.2020.12.003

Buabeng-Andoh, C. (2018). Predicting students' intention to adopt mobile learning. Journal of Research in Innovative Teaching & Learning, 11(2), 178–191. https://doi.org/10.1108/jrit-03-2017-0004

Buabeng-Andoh, C. (2021). Exploring University students' intention to use mobile learning: A research model approach. Education and Information Technologies, 26 (1), 241–256. https://doi.org/10.1007/s10639-020-10267-4

Cacciamani, S., Villani, D., Bonanomi, A., Carissoli, C., Olivari, M. G., Morganti, L., Riva, G., & Confalonieri, E. (2018). Factors affecting students' acceptance of tablet PCs: A study in Italian high schools. Journal of Research on Technology in Education, 50(2), 120–133. https://doi.org/10.1080/15391523.2017.1409672

Criollo-C, S., Guerrero-Arias, A., Jaramillo-Alcázar, Á., & Luján-Mora, S. (2021). Mobile learning technologies for education: Benefits and pending issues. Applied Sciences, 11(9), 4111.

Carranza, R., Díaz, E., Martín-Consuegra, D., & Fernández-Ferrín, P. (2020). PLS–SEM in business promotion strategies. A multigroup analysis of mobile coupon users using MICOM, Industrial Management & Data Systems, 120(12), 2349-374.  https://doi.org/10.1108/IMDS-12-2019-0726

Chang, C. C., Liang, C., Yan, C. F., & Tsen, J. S. (2013). The impact of college students' intrinsic and extrinsic motivation on continuance intention to use English mobile learning systems. Asia-Pacific Education Researcher, 22 (2), 181–192. DOI: 10.1007/s40299-012-0011-7

Cheng, Y. M. (2015). Towards an understanding of the factors affecting m-learning acceptance: Roles of technological characteristics and compatibility. Asia Pacific Management Review, 20(3), 109–119. https://doi.org/10.1016/j.apmrv.2014.12.011

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https//www.jstor.org/stable/249008

Gómez-Ramirez, I., Valencia-Arias, A., & Duque, L. (2019). Approach to M-learning acceptance among university students: An integrated model of TPB and TAM. International Review of Research in Open and Distance Learning, 20(3), 141–164. https://doi.org/10.19173/irrodl.v20i4.4061

Hair, J. F. Jr, Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications

Habibi, A., Yaakob, M. F. M., & Al-Adwan, A. S. (2021). m-Learning management system use during Covid-19. Information Development. https://doi.org/10.1177/02666669211035473

Hamidi, H., & Chavoshi, A. (2018). Analysis of the essential factors for the adoption of mobile learning in higher education: A case study of students of the University of Technology. Telematics and Informatics, 35(4), 1053-1070.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International marketing review.

Huang, J. H., Lin, Y. R., & Chuang, S. T. (2007). Elucidating user behavior of mobile learning: A perspective of the extended technology acceptance model, Electronic Library, 25 (5), 585–598. DOI: 10.1108/02640470710829569

Iqbal, S., & Ahmed, B. Z. (2015). An investigation of university student readiness towards m-learning using technology acceptance model. International Review of Research in Open and Distributed Learning, 16(4), 83-103.

Iskander, M. (2008). Innovative techniques in instruction technology, e-learning, e-assessment and education, Springer Netherlands

Jaradat, M. I. R. M., & Faqih, K. M. (2014). Investigating the moderating effects of gender and self-efficacy in the context of mobile payment adoption: A developing country perspective. International Journal of Business and Management, 9(11), 147.

Joo, Y. J., Joung, S., Shin, E. K., Lim, E., & Choi, M. (2014). Factors influencing actual use of mobile learning connected with e-learning. Computer Science & Information Technology, 4(11), 169-176.

Kankam, P. K. (2020). Mobile information behavior of sandwich students towards mobile learning integration at the University of Ghana. Cogent Education, 7(1), 1796202

Kanwal, F., Rehman, M., & Malik, M. A. (2020). E-Learning adoption and acceptance in Pakistan: Moderating effect of gender and experience. Mehran University Research Journal of Engineering and Technology, 39(2), 324–341. https://doi.org/10.22581/muet1982.2002.09

Kemp, S. (2022, July 22). Digital in Ghana: All the Statistics You Need in 2021.  DataReportal. https://datareportal.com/reports/digital-2021-ghana

Kumar, J. A., Bervell, B., Annamalai, N., & Osman, S. (2020). Behavioral intention to use mobile learning: Evaluating the role of self-efficacy, subjective norm, and Whatsapp use habit. IEEE Access, 8, 208058–208074. https://doi.org/10.1109/ACCESS.2020.3037925

Kuadey, N. A., Bensah, L., Ankora, C., Mahama, F., Agbesi, V. K., & Newman, N. K. (2020). Adoption of mobile technology application at a technical university in Ghana. International Journal of Computer Applications, 175 (31), 7–13. https://doi.org/10.5120/ijca2020920871

Li, P. C., Kong, W. J., & Zhou, W. L. (2020). Research on the mobile learning adoption of college students based on TTF and UTAUT. In Proceedings of the 5^th International Conference on Distance Education and Learning. Pervasive Computing Technologies for Healthcare.

Lingga, I. S., Eddy, E. P. S., Dewi, N. L., & Saputra, C. A. R. (2021). Analysis of Using e-Filing with the Implementation of Theory of Planned Behavior. KINERJA, 25(2), 192-204.

Oluwajana, D., & Adeshola, I. (2021). Does the student's perspective on multimodal literacy influence their behavioral intention to use collaborative computer-based learning?. Education and information technologies, 26(5), 5613-5635

Madlala, M., Civilcharran, S., & Singh, U. G. (2020). Understanding students' usage of smartphone applications for learning purposes: A case study. In Proceedings of the 2020 International Conference on Advances in Computing and Communication Engineering, ICACCE 2020. https://doi.org/10.1109/ICACCE49060.2020.9154920

Maldonado, U. P. T., Khan, G. F., Moon, J., & Rho, J. J. (2011). E-learning motivation and educational portal acceptance in developing countries. Online Information Review, 35(1), 66–85. https://doi.org/10.1108/14684521111113597/FULL/HTML

Mehdi, K. D. B. A. (2020). Handbook of research on modern educational technologies, applications, and management, IGI Global

Mpungose, C. B. (2020). Emergent transition from face-to-face to online learning in a South African University in the context of the Coronavirus pandemic. Humanities and Social Sciences Communications, 7(1), 1-9.

Pagani, M. (2008). Encyclopedia of Multimedia Technology and Networking, (2nd Ed), Information Science Reference

Saroia, A. I., & Gao, S. (2019). Investigating university students' intention to use mobile learning management systems in Sweden. Innovations in Education and Teaching International, 56(5), 569–580. https://doi.org/10.1080/14703297.2018.1557068

Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. John wiley & sons.

Sultana, J. (2020). Determining the factors that affect the uses of mobile cloud learning (MCL) platform Blackboard- a modification of the UTAUT model. Education and Information Technologies, 25(1), 223–238. https://doi.org/10.1007/s10639-019-09969-1

Tagoe, M., & Abakah, E. (2014). Determining distance education students' readiness for mobile learning at the University of Ghana using the Theory of Planned Behavior. International Journal of Education and Development Using Information and Communication Technology, 10 (1), 91–106.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540‑5915.2008.00192.x

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly: Management Information Systems, 24(1), 115–136. https://doi.org/10.2307/3250981

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Wai, I. S. H., Ng, S. S. Y., Chiu, D. K., Ho, K. K., & Lo, P. (2018). Exploring undergraduate students' usage pattern of mobile apps for education. Journal of Librarianship and Information Science, 50(1), 34–47. DOI: 10.1177/0961000616662699

Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92–118. https://doi.org/10.1111/j.1467-8535.2007.00809.x

Zaidi, S. F. H., Osmanaj, V., Ali, O., & Zaidi, S. A. H. (2021). Adoption of mobile technology for mobile learning by university students during COVID-19. International Journal of Information and Learning Technology, 38 (4), 329–343.