International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN:2313-626X

Volume 3, Issue 7  (July 2016), Pages:  81-88

Title: Understanding intention to use mobile learning: a perspective of the extended unified theory of acceptance and use of technology

Authors:  Reham Adel Ali *, Muhammad Rafie Mohd Arshad


School of Computer Sciences, Universiti Sains Malaysia 11800 USM, Penang, Malaysia

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The objective of this research paper is to gain a better understanding of the intention of students to take up mobile learning (m-learning) through an examination made on the underlying basis of the unified theory of acceptance and use of technology (UTAUT). There are a number of factors influencing the acceptance of m-learning, such as: technology factors (including effort expectancy and performance expectancy); implementation environment factors (facilitating conditions and social influence); and individual factors (self-regulation and self-efficacy). Ultimately, the findings of the research could enrich the student experience by giving schools a tool to better understand those factors impacting on the students’ ability to effectively utilize m-learning; thereby allowing schools to adapt their programs to enhance learning by way of the usage of m-learning. From the review of the literature and subsequent to the factors identified as mentioned above, a research model has been proposed. The model has the ability to enhance the current level of understanding as to the motivating factors influencing students’ motivation to utilize m-learning. This enhanced level of understanding can assist efforts to encourage and provide support for m-learning. 

© 2016 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (

Keywords: Mobile learning, Intention, Self-regulation, Self-efficacy, UTAUT

Article History: Received 9 June 2016, Received in revised form 27 July 2016, Accepted 27 July 2016

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Ali RA, Arshad MRM (2016). Understanding intention to use mobile learning: a perspective of the extended unified theory of acceptance and use of technology. International Journal of Advanced and Applied Sciences, 3(7): 81-88


Abbad MM, Morris D and De Nahlik C (2009). Looking under the bonnet: Factors affecting student adoption of e-learning systems in Jordan. The International Review of Research in Open and Distributed Learning, 10(2): 1-25.
Abu-Al-Aish A and 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): 82-107.
AbuShanab E and Pearson JM (2007). Internet banking in Jordan: The unified theory of acceptance and use of technology (UTAUT) perspective. Journal of Systems and information Technology, 9(1): 78-97.
Agarwal R, Sambamurthy V and Stair RM (2000). Research report: the evolving relationship between general and specific computer self-efficacy—an empirical assessment. Information Systems Research, 11(4): 418-430.
Al-Hujran O, Al-Lozi E and Al-Debei MM (2014). Get Ready to Mobile Learning: Examining Factors Affecting College Students' Behavioral Intentions to Use M-Learning in Saudi Arabia. Jordan Journal of Business Administration, 10(1): 111-128.
Anderson JE and Schwager PH (2004). SME adoption of wireless LAN technology: applying the UTAUT model. In Proceedings of the 7th annual conference of the southern association for information systems, 7: 39-43.
Attalla SMES, El-Sherbiny R, Mokbel WA, El-Moursy RM and Abdel-Wahab AG (2012). Screening of students' intentions to adopt mobile-learning: A case from Egypt. International Journal of Online Pedagogy and Course Design (IJOPCD), 2(1): 65-82.
Bere A (2014). Exploring determinants for mobile learning user acceptance and use: an application of UTAUT. In Information Technology: New Generations (ITNG), 2014 11th International Conference, IEEE: 84-90
Bidin S and Ziden AA (2013). Adoption and application of mobile learning in the education industry. Procedia-Social and Behavioral Sciences, 90(2013): 720-729.

Carlsson C, Carlsson J, Hyvonen K., Puhakainen J and Walden P (2006). Adoption of mobile devices/services-searching for answers with the UTAUT. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06), IEEE, 6: 1-10.

Chang CC (2013). Library mobile applications in university libraries. Library Hi Tech, 31(3): 478-492.

Chau PY and Hu PJ (2002). Examining a model of information technology acceptance by individual professionals: An exploratory study. Journal of Management Information Systems, 18(4): 191-229.
Cheng YM (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.
Chung HH, Chen SC and Kuo MH (2015). A study of EFL college students' acceptance of mobile learning. Procedia-Social and Behavioral Sciences, 176(2015), 333-339.
Dadayan L and Ferro E (2005). When technology meets the mind: A comparative study of the technology acceptance model. In International Conference on Electronic Government. Springer Berlin Heidelberg: 137-144.
Davis FD, Bagozzi RP and Warshaw PR (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8): 982-1003.
Grandon EE, Alshare K and Kwun O (2005). Factors influencing student intention to adopt online classes: A cross-cultural study. Journal of Computing Sciences in Colleges, 20(4): 46-56.
Hu PJ, Chau PY, Sheng ORL and Tam KY (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2): 91-112.
Hussein R, Aditiawarman U and Mohamed N (2007). E-Learning acceptance in a developing country: A case of the Indonesian Open University. In German e-Science conference, Baden-Baden, Germany.
Iqbal S and Qureshi IA (2012). M-learning adoption: A perspective from a developing country. The International Review of Research in Open and Distributed Learning, 13(3): 147-164.
Jairak K, Praneetpolgrang P and Mekhabunchakij K (2009). An acceptance of mobile learning for higher education students in Thailand. In Sixth International Conference on eLearning for Knowledge-Based Society, Thailand, 17(18): 361-368.
Jambulingam M (2013). Behavioural intention to adopt mobile technology among tertiary students. World Applied Sciences Journal, 22(9): 1262-1271.
Johnson RD, Hornik S and Salas E (2008). An empirical examination of factors contributing to the creation of successful e-learning environments. International Journal of Human-Computer Studies, 66(5): 356-369.
King FB, Harner M and Brown SW (2000). Self-regulatory behavior influences in distance learning. International Journal of Instructional Media, 27(2): 147-156.
Lee Y, Kozar KA and Larsen KR (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12(1): 752-780.
Liaw SS, Huang HM and Hsing KT (2014). Understanding uses' Attitudes toward Mobile learning Environments. In International Conference on Social, Education and Management Engineering, Macao, China.
Liu Y (2011). Solving the puzzle of mobile learning adoption. PhD Dissertation, Åbo Akademi University, Turku, Finland.
Lowenthal JN (2010). Using mobile learning: Determinates impacting behavioral intention. The Amer. Jrnl. of Distance Education, 24(4): 195-206.
Lu J, Yu CS, Liu C and Yao JE (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3): 206-222.
Marchewka JT and Kostiwa K (2014). An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA, 7(2): 93-104.

Mardikyan S, Besiroglu B and Uzmaya G (2012). Behavioral intention towards the use of 3G technology. Communications of the IBIMA, 2012(2012): Article ID 622123, 10 pages.

Marshall B, Mills R and Olsen D (2011). The role of end-user training in technology acceptance. Review of Business Information Systems (RBIS), 12(2): 1-8.
Miller MD, Ranier RK and Corley JK (2003). Predictors of engagement and participation in an on-line course. Online Journal of Distance Learning Administration, 6(1): 1-13.
Mohammadi H (2015). Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49: 191-207.
Motiwalla LF (2007). Mobile learning: A framework and evaluation. Computers and Education, 49(3): 581-596.
Nanayakkara C (2007). A model of user acceptance of learning management systems: a study within tertiary institutions in New Zealand. The International Journal of Learning, 13(12): 223-232.
Nassuora AB (2012). Students acceptance of mobile learning for higher education in Saudi Arabia. American Academic and Scholarly Research Journal, 4(2): 24-30.
Paechter M, Maier B and Macher D (2010). Students' expectations of and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computers and Education, 54(1): 222-229.
Park SY, Nam MW and Cha SB (2012). University students' behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43(4): 592-605.
Pynoo B, Devolder P, Tondeur J, Van Braak J, Duyck W and Duyck P (2011). Predicting secondary school teachers' acceptance and use of a digital learning environment: A cross-sectional study. Computers in Human Behavior, 27(1): 568-575.
Sekaran U and Bougie R (2010). Research methods for business: A skill building approach. John Wiley and Sons, New Jersey, USA.
Selfe CL (1999). Technology and literacy in the 21st century: The importance of paying attention. Southern Illinois University Press, Illinois, USA.
Straub ET (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of Educational Research, 79(2): 625-649.
Venkatesh V, Morris MG, Davis GB and Davis FD (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3): 425-478.
Virvou M and Alepis E (2005). Mobile educational features in authoring tools for personalised tutoring. Computers and Education, 44(1): 53-68.
Wang YS, Wu MC and Wang HY (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1): 92-118.
Watts N (1997). A Learner-based approach to computer mediated language learning. System, 25(1): 1-8.
Wong WT and Huang NTN (2015). The effects of e-learning system service quality and users' acceptance on organizational learning. International Journal of Business and Information, 6(2): 205-225.
Wu WH, Wu YCJ, Chen CY, Kao HY, Lin CH and Huang, SH (2012). Review of trends from mobile learning studies: A meta-analysis. Computers and Education, 59(2): 817-827.
Yang KC (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22(3): 257-277.
Zhou T (2012). Understanding users' initial trust in mobile banking: An elaboration likelihood perspective. Computers in Human Behavior, 28(4): 1518-1525.
Zimmerman BJ (1995). Self-efficacy and educational development. Self-efficacy in Changing Societies, 202-231, Cambridge University Press, New York, USA.