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Modeling Students’ Readiness to Adopt Mobile Learning in Higher Education: An Empirical Study
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, Assistant Professor of Information Systems - Business School at Al-Ahliyya Amman University, Jordan., Jordan ; , Assistant Professor of Business Administration - king Talal School of Business Technology at Princess Sumaya University for Technology. ;

IRRODL Volume 19, Number 1, ISSN 1492-3831 Publisher: Athabasca University Press

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Abstract

Mobile devices are increasingly coming to penetrate people's daily lives. Mobile learning (m-learning) is viewed as key to the coming era of electronic learning (e-learning). In the meantime, the use of mobile devices for learning has made a significant contribution to delivering education among higher education students worldwide. However, while m-learning is being widely adopted in developed countries, the adoption of such an approach in developing countries is still immature and underdeveloped. Developing countries are facing several challenges and lagging behind in terms of adopting m-learning in higher education. Thus, this paper explores the factors that have an impact on students\u2019 intentions and readiness to adopt m-learning in higher education in Jordan. Based on the data collected from the field, we examineJordanian students' requirements and preferences in terms of m-learning design, and we also investigate their concerns about adopting m-learning. This empirical study collected data from students using a paper-based questionnaire. The results reveal that students' intentions to adopt m-learning is influenced by several factors that include the relative advantage, complexity, social influence, perceived enjoyment, and the self-management of learning. By providing a picture of students' willingness to adopt m-learning, this study offers useful and beneficial implications for developers of m-learning applications and for educational providers to guide the design and implementation of comprehensive m-learning systems.

Citation

Al-Adwan, A., Al-Madadha, A. & Zvirzdinaite, Z. (2018). Modeling Students’ Readiness to Adopt Mobile Learning in Higher Education: An Empirical Study. The International Review of Research in Open and Distributed Learning, 19(1),. Athabasca University Press. Retrieved March 25, 2023 from .

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View References & Citations Map
  1. Abbasi, M., Tarhini, A., & Hassouna, M. (2015). Social, organizational, demography and individuals’ technology acceptance behaviour: a conceptual model. European Scientific Journal, 11(9), 48-76.
  2. Al-Adwan, A. (2015). Exploring physicians’ behavioural intention toward the adoption of electronic health
  3. Al Adwan, A. (2017). Case study and grounded theory: a happy marriage? An exemplary application from healthcare informatics adoption research. International Journal of Electronic Healthcare, 9(4), 294-318.
  4. Al-Adwan, A., Al-Adwan, A., & Smedley, J. (2013). Exploring students’ acceptance of e-learning using
  5. Al-Adwan, A., & Smedley, J. (2012). Implementing e-learning in the Jordanian higher educationsystems:
  6. Ali, R., & Arshad, M. (2016). Perspectives of students’ behavior towards mobile learning (M-learning) in
  7. AlKailani, M. (2016). Factors affecting the adoption of internet banking in Jordan: An extended TAM model. Journal of Marketing Development and Competitiveness, 10(1), 39-52
  8. Almarabeh, T., & Mohammad, H. (2013). E-learning in the Jordanian higher education system: Strengths, weakness, opportunities and threats. Journal of American Science, 9(3), 281-287.
  9. Almasri, A. (2015). Readiness and mobile learning process for higher education students in Jordanian universities. International Journal of Multidisplinary Research, 5(1), 85-96.
  10. Arpaci, I. (2014). A comparative study of the effects of cultural differences on the adoption of mobile learning. British Journal of Educational Technology, 46(4), 699-712.
  11. Aypay, A., Celik, H., & Aypay, A. (2012). Technology acceptance in education: A study of pre-service teachers in turkey. The Turkish Online of Educational Technology, 11(4), 264-272.
  12. Callum, K. (2010). Attitudes of educators to the introduction of mobile technology. Retrieved from www.citrenz.ac.nz/conferences/2010/papers10/139.pdf
  13. Callum, K., & Jeffrey, L. (2013). The influence of students’ ICT skills and their adoption of mobile learning. Australasian Journal of Educational Technology, 29(3), 303-314.
  14. Callum, K., Jeffrey, L., & Kinshuk, I. (2014). Factors impacting teachers’ adoption of mobile learning. Journal of Information Technology Education: Research, 13(1), 141-162.
  15. Carte, T., & Russell, C. (2003). In pursuit of moderation: nine common errors and their solutions. MIS Quarterly, 27(3), 479-501.
  16. Celik, H. (2016). Customer online shopping anxiety the unified theory of acceptance and use technology (UTAUT) framework. AsiaPacific Journal of Marketing and Logistics, 28(2), 278-307.
  17. Cheng, Y. (2014). Exploring the intention to use mobile learning: the moderating role of personal innovativeness. Journal of Systems and Information Technology, 16(1), 40-61.
  18. Concannon, F., Flynn, A., & Compbell, M. (2005). What campus-based students think about the quality and benefits of e-learning. British Journal of Educational Technology, 36(3), 501-512.
  19. Davis, F. (1989). Perceived usefulness, perceived ease of use acceptance of information technology. MIS Quarterly, 13(3), 139-339.
  20. Davis, F., Bagozzi, R., & Warshaw, P. (1992). Extrinsic and intrinsic motivation to use computers in workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
  21. Deb, S. (2011). Effective distance learning in developing countries using mobile and multimedia technology. International of Multimedia and Ubiquitous Engineering, 6(2), 33-40
  22. Farley, H., Murphy, A., & Rees, S. (2013, December). Revisiting the definition of Mobile Learning. In
  23. Hadi, F., & Kishik, A. (2014). Acceptance of mobile learning among university students in Malysia. Journal of Computing and organizational Dynamics, 1(1), 1-14.
  24. Hair, F., Hult, G., & Ringle, M. (2013). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage.
  25. Hair, J., Sarstedt, M., & Ringle, C. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433.
  26. Hassan, U., Nawaz, M., Syed, T., Arfeen, M., Naseem, A., & Noor, S. (2015). Investigating students’
  27. Hossain, M., & El Saddik, A. (2008). A biologically inspired multimedia content repurposing system in heterogenous environments. Multimedia Systems, 14(3), 135-143.
  28. Huang, R. (2014). Exploring the moderating role of self-management of learning in mobile English learning. Educational Technology& Society, 17(4), 255-267.
  29. Iqbal, S., & Qureshi, I. (2012). M-learning adoption: A perspective from a developing country. The International Review of Research in Open and Distributed Learning, 13(3), 148-164.
  30. Jambulingam, M. (2013). Behavioural intention to adopt mobile technology among tertiary students. World Applied Sciences Journal, 22(9), 1262-1271.
  31. Joo, Y., Lim, K., & Lim, E. (2014). Investigating the structural relationship among perceived innovation
  32. Jung, H. (2014). Ubiquitous learning: determinants impacting learners’ satisfaction and performance with smartphones. Language learning& Technology, 18(3), 97-119.
  33. Koufteros, A. (1999). Testing a model of pull production: A paradigm for manufacturing research using structural equation modelling. Journal of operations Management, 17(1), 467-488.
  34. Liaw, S., Hatala, M., & Huang, H. (2010). Investigating acceptance toward mobile learning to assist
  35. Liew, B.T., Kang, M., Yoo, E., & You, J. (2013). Investigating the determinants of mobile learning acceptance in Korea. In J. Herrington, A. Couros, & V. Irvine (Eds.), Proceedings of EdMedia: World Conference on Educational Media and Technology 2013 (pp. 1424-1430). Association for
  36. Liu, Y. (2008). An adoption model for mobile learning. In Proceeding for the IADIS international Conference e-Commerce. Amsterdam, The Netherlands.
  37. Liu, Y., Han, S., & Li, H. (2010). Understanding the factors driving m-learning adoption: a literature review. Campus-Wide Information Systems, 27(4), 210-116.
  38. Lu, J., Chun-Chun-Sheng, Y., & Chang, L. (2005). Facilitating conditions, wireless trust and adoption intention. Journal of Computer Information Systems, 46(1), 17-24.
  39. Martin, F., & Ertzberger, J. (2013). Here and now mobile learning: An experimental study on the use of mobile technology. Computer& Education, 68(1), 76-85.
  40. Nassuora, A. (2013). Students’ acceptance of mobile learning for higher education in Saudi Arabia. International Journal of Learning Management Systems, 1(1), 1-9.
  41. Osman, M., El-Hussein, M., & Cronje, J. (2010). Defining mobile learning in the higher education landscape. Educational Technology& Society, 13(3), 12-21.
  42. Poong, Y., Yamaguchi, S., & Takada, J. (2016). Investigating the drivers of mobile learning acceptance
  43. Prajapati, M., & Patel, J. (2014). The factors influencing in mobile learning adoption: A literature review. International Journal of Application or Innovation in Engineering and Management, 3(9), 133138.
  44. Rogers, E. (2005). Diffusion of innovation. New York: Free Press.
  45. Sahin, I. (2006). Detailed review of Rogers’ diffusion of diffusion of innovations theory and educational
  46. Sarrab, M., Al Shibli, I., & Badursha, N. (2016). An empirical study of factors driving the adoption of
  47. Sarstedt, M., Henseler, J., & Ringle, C. (2011). Multi-group analysis in partial least squares (PLS) path modeling: alternative methods and empirical results. In M. Sarstedt, M. Schwaiger, & C.R.
  48. Shaukat, M., & Zafar, J. (2010). Impact of sociological and organisational factors on information
  49. Shorfuzzaman, M., & Alhussein, M. (2016). Modeling learners’ readiness to adopt mobile learning: A perspective from a GCC higher education institution. Mobile Information Systems, 1(1), 1-10.
  50. Tabor, S. (2016). Making mobile learning work: Student perceptions and implementation factors. Journal of Information Technology Education: Innovations in Practice. 15(1), 75-98
  51. Telecommunication Regulatory Commission. (2016). Telecom markets statistics and surveys. Retrieved from http://www.trc.gov.jo/Pages/viewpage.aspx?pageID=1006
  52. Thomas, T., Singh, L., & Gaffar, K. (2013). The utility of the UTAUT model in explaining mobile learning
  53. Traxler, J. (2007). Defining, discussing and evaluating mobile learning: The moving finger writes and having writ. The International Review of Research in Open and Distrusted Learning, 8(2), 129138.
  54. Ugur, N., Koc, T., & Koc, M. (2016). An analysis of mobile learning acceptance by college students. Journal of Educational and Instructional Studies, 6(2), 2146-7463.
  55. Venkatesh, V. (1999). Creation of favorable user perceptions: exploring the role of intrinsic motivation. MIS quarterly, 23(2), 239-260.
  56. Venkatesh, V., Morris, M., Davies, G., & Davis, F. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478.
  57. Wang, S., Wu, C., & Wang, 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.
  58. Wong, K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.
  59. Yang, S. (2013). Understanding undergraduate students’ adoption of mobile learning model: a perspective of extended UTAUT2. Journal of Convergence Information Technology, 8(10), 969-979.
  60. Zou, X., & Zhang, X. (2013). Effect of different score reports of web-based formative test on students’ selfregulated learning. Computers& Education, 66(1), 54-63.

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