Past studies have placed little emphasis on quality factors as the detebile learning application provides me a promptrminants of mobile learning adoption. Thus, this study’s purpose is to integrate the Technology Acceptance Model (TAM) with the updated DeLone and McLean’s model (DL&ML) to examine whether quality factors (including system quality, information quality, and service quality) and individual beliefs (including perceived usefulness and perceived ease of use) are the antecedents to students’ satisfaction and their intention to use, leading to enhancing their actual usage of mobile learning system. A total of 400 questionnaires were distributed. The results showed that quality factors (including system quality, information quality, and service quality) had significant effects on students’ satisfaction and their intention to use mobile learning; besides, perceived usefulness has significantly strong impacts on intention to use mobile learning, and satisfaction and intention to use both have significant effects on actual use of mobile learning. This study opens future work for using the identified quality factors as guidelines for researchers and designers to design and develop mobile learning applications.
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Abachi, H. R., & Muhammad, G. (2014). The impact of m-learning technology on students and educators. Computers in Human Behavior, 30, 491–496.
Abu-Al-Aish, A., & Love, S. (2013). Factors influencing students’ acceptance of m-learning: An investigation in higher education. The International Review of Research in Open and Distributed Learning, 14(5).
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
Ahn, T., Ryu, S., & Han, I. (2007). The impact of web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3), 263–275.
Al-Debei, M. M. (2014). The quality and acceptance of websites: An empirical investigation in the context of higher education. International Journal of Business Information Systems, 15(2), 170–188.
Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior, 56, 93–102.
Almaiah, M. A. (2018). Acceptance and usage of a mobile information system services in University of Jordan. Education and Information Technologies, 1–23.
Almaiah, M. A., & Jalil, A. (2014). Investigating Students' perceptions on Mobile learning services. International Journal of Interactive Mobile Technologies, 8(4).
Almaiah, M. A., & Man, M. (2016). Empirical investigation to explore factors that achieve high quality of mobile learning system based on students’ perspectives. Engineering Science and Technology, an International Journal, 19(3), 1314–1320.
Almaiah, M. A., Jalil, M. A., & Man, M. (2016a). Preliminary study for exploring the major problems and activities of mobile learning system: A case study of Jordan. Journal of Theoretical & Applied Information Technology, 93(2).
Almaiah, M. A., Jalil, M. A., & Man, M. (2016b). Extending the TAM to examine the effects of quality features on mobile learning acceptance. Journal of Computers in Education, 3(4), 453–485.
Almarashdeh, I. A., Sahari, N., Zin, N. A. M., & Alsmadi, M. (2010). The success of learning management system among distance learners in Malasian universities. Journal of Theoretical & Applied Information Technology, 21(2).
Almasri, A. K. M. (2014). The influence on mobile learning based on technology acceptance model (tam), mobile readiness (Mr) and perceived interaction (pi) for higher education students. International Journal of Technical Research and Applications, 2(1), 05–11.
Al-Mushasha, N. F., & Nassuora, A. B. (2012). Factors determining e-learning service quality in Jordanian higher education environment. Journal of Applied Sciences, 12(14), 1474.
Al-Shboul, M., Rababah, O., Al-Sayyed, R., Sweis, G., & Aldreabi, H. (2013). Roadmap to advance e-learning management system at the University of Jordan. Journal of American Science, 9(1), 531–545.
Althunibat, A. (2015). Determining the factors influencing students’ intention to use m-learning in Jordan higher education. Computers in Human Behavior, 52, 65–71.
Ariffin, S. A. (2011). Mobile learning in the institution of higher learning for Malaysia students: Culture perspectives. International Journal on Advanced Science, Engineering and Information Technology, 1(3), 283–288.
Bidin, S., & Ziden, A. A. (2013). Adoption and application of mobile learning in the education industry. Procedia-Social and Behavioral Sciences, 90, 720–729.
Byrne, B. M. (2013). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Hove: Psychology Press
Chang, C. C., Yan, C. F., & Tseng, J. S. (2012). Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students. Australasian Journal of Educational Technology, 28(5), 809–826.
Chen, H. R., & Tseng, H. F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and program planning, 35(3), 398–406.
Cheng, Y. M. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research, 22(3), 361–390.
Cho, C., & Lai. (2009). The role of perceived user-interface design in continued usage intention of self-paced e-learning tools. Computers & Education, 53(2), 216–227.
Dahlstrom, E., Walker, J. D., & Dziuban, C. (2013). ECAR study of undergraduate students and information technology. 2013.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319–340.
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95.
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.
Delone, W. H., & Mclean, E. R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce, 9(1), 31–47.
Etezadi-Amoli, J., & Farhoomand, A. F. (1996). A structural model of end user computing satisfaction and user performance. Information & Management, 30(2), 65–73.
Fathema, N., Shannon, D., & Ross, M. (2015). Expanding the technology acceptance model (TAM) to examine faculty use of learning management systems (LMSs) in higher education institutions. Journal of Online Learning & Teaching, 11(2).
Field, A. (2009). Discovering statistics using SPSS. Sage publications.
Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), 7.
Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. The Internet and Higher Education, 19, 18–26.
Glackin, B. C., Rodenhiser, R. W., & Herzog, B. (2014). A library and the disciplines: A collaborative project assessing the impact of eBooks and mobile devices on student learning. The Journal of Academic Librarianship, 40(3), 299–306.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19, 213–236.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Upper Saddle River: Pearson Prentice Hall.
Hassan, M. H., Alhosban, F., & Hourani, M. A. (2016). Using Mobile Technologies for Enhancing Student Academic Experience: University of Jordan Case Study. International Journal of Interactive Mobile Technologies (iJIM), 10(1), 13–18.
Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A model for measuring e-learning systems success in universities. Expert Systems with Applications, 39(12), 10959–10966.
Holsapple, C. W., & Lee-Post, A. (2010). Behavior-based analysis of knowledge dissemination channels in operations management. Omega, 38(3), 167–178.
Hunt, S. D., Sparkman Jr., R. D., & Wilcox, J. B. (1982). The pretest in survey research: Issues and preliminary findings. Journal of Marketing Research, 19, 269–273.
Iqbal, S., & Qureshi, I. A. (2012). M-learning adoption: A perspective from a developing country. The International Review of Research in Open and Distributed Learning, 13(3), 147–164.
Jaradat, M. I. R. M. (2014). Understanding individuals' perceptions, determinants and the moderating effects of age and gender on the adoption of mobile learning: Developing country perspective. International Journal of Mobile Learning and Organisation, 8(3–4), 253–275.
Kanthawongs, P., & Kanthawongs, P. (2013). Individual and social factors affecting student's usage intention in using learning management system. Procedia-Social and Behavioral Sciences, 88, 89–95.
Khan, A. I., Al-Shihi, H., Al-Khanjari, Z. A., & Sarrab, M. (2015). Mobile learning (M-learning) adoption in the Middle East: Lessons learned from the educationally advanced countries. Telematics and Informatics, 32(4), 909–920.
Kim, T. G., Lee, J. H., & Law, R. (2008). An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model. Tourism Management, 29(3), 500–513.
Lee, Y., & Kozar, K. A. (2006). Investigating the effect of website quality on e-business success: An analytic hierarchy process (AHP) approach. Decision Support Systems, 42(3), 1383–1401.
Lee, B. C., Yoon, J. O., & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers & Education, 53(4), 1320–1329.
Lee, Y. C., Li, M. L., Yen, T. M., & Huang, T. H. (2010). Analysis of adopting an integrated decision making trial and evaluation laboratory on a technology acceptance model. Expert Systems with Applications, 37(2), 1745–1754.
Lindsay, R., Jackson, T. W., & Cooke, L. (2011). Adapted technology acceptance model for mobile policing. Journal of Systems and Information Technology, 13(4), 389–407.
Liu, Y., Li, H., & Carlsson, C. (2010). Factors driving the adoption of m-learning: An empirical study. Computers & Education, 55(3), 1211–1219.
Lwoga, E. T. (2014). Critical success factors for adoption of web-based learning management systems in Tanzania. International Journal of Education and Development using Information and Communication Technology, 10(1), 4.
Maditinos, D., Chatzoudes, D., & Sarigiannidis, L. (2013). An examination of the critical factors affecting consumer acceptance of online banking: A focus on the dimensions of risk. Journal of Systems and Information Technology, 15(1), 97–116.
Mohammadi, H. (2015). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191–207.
Molenet.org (2009). The Mobile learning network (MoLeNET) retrieved APR. 28th, 2016, From http://www.molenet.org.uk/
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38(4), 217–230.
O'bannon, B. W., & Thomas, K. (2014). Teacher perceptions of using mobile phones in the classroom: Age matters! Computers & Education, 74, 15–25.
Ong, C. S., Day, M. Y., & Hsu, W. L. (2009). The measurement of user satisfaction with question answering systems. Information & Management, 46(7), 397–403.
Ozdamli, F., & Cavus, N. (2011). Basic elements and characteristics of mobile learning. Procedia-Social and Behavioral Sciences, 28, 937–942.
Park, N., Roman, R., Lee, S., & Chung, J. E. (2009). User acceptance of a digital library system in developing countries: An application of the technology acceptance model. International Journal of Information Management, 29(3), 196–209.
Park, S. Y., Nam, M. W., & Cha, S. B. (2012). University students' behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43(4), 592–605.
Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236–263.
Pituch, K. A., & Lee, Y. K. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222–244.
Prieto, J. C. S., Migueláñez, S. O., & García-Peñalvo, F. J. (2014). Mobile learning adoption from informal into formal: an extended TAM model to measure mobile acceptance among teachers. In Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality (pp. 595–602). ACM.
Rieh, S. Y. (2002). Judgment of information quality and cognitive authority in the web. Journal of the American Society for Information Science and Technology, 53(2), 145–161.
Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. International Journal of Human-Computer Studies, 64(8), 683–696.
Rocha, Á. (2012). Framework for a global quality evaluation of a website. Online Information Review, 36(3), 374–382.
Sanchez-Franco, M. J. (2009). The moderating effects of involvement on the relationships between satisfaction, trust and commitment in e-banking. Journal of Interactive Marketing, 23(3), 247–258.
Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2016). Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers. Computers in Human Behavior, 55, 519–528.
Sekaran, U. (2009). Bougie. M,“research methods for business: A skill building approach”. UK: John Wiley & sons.
The Jordan Times. (2014). 95% of Jordanians own mobiles; 47% use the Internet. Retrieved 21 April, 2016 from http://jordantimes.com/95-of-jordanians-own-mobiles-47-use-the-internet.
Urbach, N., Smolnik, S., & Riempp, G. (2009). The state of research on information systems success. Business & Information Systems Engineering, 1(4), 315–325.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186–204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425–478.
Viberg, O., & Grönlund, Å. (2013). Cross-cultural analysis of users' attitudes toward the use of mobile devices in second and foreign language learning in higher education: A case from Sweden and China. Computers & Education, 69, 169–180.
Wang, Y. S., & Liao, Y. W. (2008). Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government Information Quarterly, 25(4), 717–733.
Wang, W. T., & Wang, C. C. (2009). An empirical study of instructor adoption of web-based learning systems. Computers & Education, 53(3), 761–774.
Wang, Y. S., Wang, Y. M., Lin, H. H., & Tang, T. I. (2003). Determinants of user acceptance of internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501–519.
Williams, P. W. (2009). Assessing mobile learning effectiveness and acceptance. Doctoral dissertation, The George Washington University.
Yamakawa, P., Delgado, C., Díaz, E., Garayar, E., & Laguna, H. (2013). Factors influencing the use of mobile technologies in a university environment: A case from Latin America. International Journal of Information and Communication Technology Education (IJICTE), 9(2), 24–38.
The authors acknowledges the Deanship of Scientific Research at King Faisal University for the financial support.
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Almaiah, M.A., Alismaiel, O.A. Examination of factors influencing the use of mobile learning system: An empirical study. Educ Inf Technol 24, 885–909 (2019). https://doi.org/10.1007/s10639-018-9810-7
- Mobile learning
- Quality factors
- DeLone and McLean’s model
- TAM model