Skip to main content
Log in

Mobile learning adoption: A systematic review

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

Mobile learning adoption is an active area of research. This paper aims to contribute to better understanding of mobile learning adoption by providing a body of knowledge to aid researchers working in this field. The applied method is systematic review of commonly used databases based on the guidelines proposed by Kitchenham (Keele, UK, Keele University, 33(2004), 1–26, 2004). In total 39 publications were retrieved out of which 27 were relevant to our research questions. The results highlighted publication trend, adoption models used and a set of factors that influence mobile learning adoption. Based on the findings recommendations were derived for further research in this field.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Ajzen, I. (1993). Attitude theory and the attitude-behavior relation. In D. Krebs, P. Schmidt (Eds.), New directions in attitude measurement (pp. 41–57). Berlin: Walter de Gruyter.

  • Atkin, D., Chaudhry, A., Chaudry, S., Khandelwal, A. K., & Verhoogen, E. (2017). Organizational barriers to technology adoption: Evidence from soccer-ball producers in Pakistan. The Quarterly Journal of Economics, 132(3), 1101–1164.

    Article  Google Scholar 

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

  • Bakhsh, M., Mahmood, A., & Sangi, N. A. (2015). An assessment of students’ readiness towards mobile learning at AIOU, Pakistan. Paper presented at the Information and Communication Technologies (ICICT), 2015 International Conference On, 1–6.

  • Bere, A. (2014). Exploring determinants for mobile learning user acceptance and use: An application of UTAUT. Paper presented at the Information Technology: New Generations (ITNG), 2014 11th International Conference On, 84–90.

  • Bere, A., & Rambe, P. (2016). An empirical analysis of the determinants of mobile instant messaging appropriation in university learning. Journal of Computing in Higher Education, 28(2), 172–198.

    Article  Google Scholar 

  • Bidin, S., & Ziden, A. A. (2013). Adoption and application of mobile learning in the education industry. Procedia-Social and Behavioral Sciences, 90, 720–729.

    Article  Google Scholar 

  • Chandhok, S., & Babbar, P. (2011). M-learning in distance education libraries: A case scenario of Indira Gandhi national open university. The Electronic Library, 29(5), 637–650.

    Article  Google Scholar 

  • Chong, J., Chong, A. Y., Ooi, K., & Lin, B. (2011). An empirical analysis of the adoption of m-learning in Malaysia. International Journal of Mobile Communications, 9(1), 1–18.

    Article  Google Scholar 

  • Cruz, Y. (2013). Examining the effect of learning styles on mobile learning adoption. Paper presented at the Advanced Learning Technologies (ICALT), 2013 IEEE 13th International Conference On, 510–511.

  • Dyson, L. E., Raban, R., Litchfield, A., & Lawrence, E. (2009). Addressing the cost barriers to mobile learning in higher education. International Journal of Mobile Learning and Organization, 3(4), 381–398.

    Article  Google Scholar 

  • Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley series in social psychology, United States

  • Gan, C., Li, H., & Liu, Y. (2017). Understanding mobile learning adoption in higher education: An empirical investigation in the context of the mobile library. The Electronic Library, (just-accepted), 00.

  • Hao, S., Dennen, V. P., & Mei, L. (2017). Influential factors for mobile learning acceptance among Chinese users. Educational Technology Research and Development, 65(1), 101–123.

    Article  Google Scholar 

  • Ho, C. B., Chou, Y., & O'Neill, P. (2010). Technology adoption of mobile learning: A study of podcasting. International Journal of Mobile Communications, 8(4), 468–485.

    Article  Google Scholar 

  • Hwang, G., & Tsai, C. (2011). Research trends in mobile and ubiquitous learning: A review of publications in selected journals from 2001 to 2010. British Journal of Educational Technology, 42(4).

  • Hwang, G., & Wu, P. (2014). Applications, impacts and trends of mobile technology-enhanced learning: A review of 2008–2012 publications in selected SSCI journals. International Journal of Mobile Learning and Organization, 8(2), 83–95.

    Article  Google Scholar 

  • Hyman, J. A., Moser, M. T., & Segala, L. N. (2014). Electronic reading and digital library technologies: Understanding learner expectation and usage intent for mobile learning. Educational Technology Research and Development, 62(1), 35–52.

    Article  Google Scholar 

  • Isa, Wan Abdul Rahim Wan Mohd, Lokman, A. M., Mustapa, M. N., Sah, I. N. M., Hamdan, A. R., & Luaran, J. E. (2015). Exploring the adoption of blended learning: Case of mobile learning. Paper presented at the 2015 3rd International Conference On Artificial Intelligence, Modeling and Simulation (AIMS), 359–364.

  • Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educational Technology Research and Development, 64(4), 611–630.

    Article  Google Scholar 

  • Karimi, S. (2016). Do learners’ characteristics matter? An exploration of mobile-learning adoption in self-directed learning. Computers in Human Behavior, 63, 769–776.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Kim, Y. J., Chun, J. U., & Song, J. (2009). Investigating the role of attitude in technology acceptance from an attitude strength perspective. International Journal of Information Management, 29(1), 67–77.

    Article  Google Scholar 

  • Kim, H., Lee, J., & Rha, J. (2017). Understanding the role of user resistance on mobile learning usage among university students. Computers & Education, 113, 108–118.

    Article  Google Scholar 

  • Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004), 1–26.

    Google Scholar 

  • Kukulska-Hulme, A., Sharples, M., Milrad, M., Arnedillo-Snchez, I., & Vavoula, G. (2009). Innovation in mobile learning: A European perspective. International Journal of Mobile and Blended Learning (IJMBL), 1(1), 13–35.

    Article  Google Scholar 

  • Lee, D., Park, J., & Ahn, J. H. (2001). On the explanation of factors affecting e-commerce adoption. ICIS 2001 Proceedings, 14.

  • Lee, M. J., & Chan, A. (2007). Pervasive, lifestyle-integrated mobile learning for distance learners: An analysis and unexpected results from a podcasting study. Open Learning, 22(3), 201–218.

    Article  Google Scholar 

  • Leung, R., McGrenere, J., & Graf, P. (2008). The learnability of mobile application interfaces needs improvement. In Proc. of British HCI Workshop on HCI and the Older Population.

  • Liu, Y., Han, S., & Li, H. (2010). Understanding the factors driving m-learning adoption: A literature review. Campus-Wide Information Systems, 27(4), 210–226.

    Article  Google Scholar 

  • Mazhar, F., Rizwan, M., Fiaz, U., Ishrat, S., Razzaq, M. S., & Khan, T. N. (2014). An investigation of factors affecting usage and adoption of internet & mobile banking in Pakistan. International Journal of Accounting and Financial Reporting, 4(2), 478–500.

    Article  Google Scholar 

  • Osakwe, J., Dlodlo, N., & Jere, N. (2017). Where learners’ and teachers’ perceptions on mobile learning meet: A case of Namibian secondary schools in the Khomas region. Technology in Society, 49, 16–30.

    Article  Google Scholar 

  • Pappas, I. O., Cetusic, L., Giannakos, M. N., & Jaccheri, L. (2017). Mobile learning adoption through the lens of complexity theory and fsQCA. Paper presented at the Global Engineering Education Conference (EDUCON), 2017 IEEE, 536–541.

  • Prieto, J. C. S., Miguelez, S. O., & Garca-Pealvo, F. J. (2014). Mobile learning adoption from informal into formal: An extended TAM model to measure mobile acceptance among teachers. Paper presented at the Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality, 595–602.

  • Prieto, J. C. S., Miguelez, S. O., & Garca-Pealvo, F. J. (2015). Mobile acceptance among pre-service teachers: A descriptive study using a TAM-based model. Paper presented at the Proceedings of the 3rd International Conference on Technological Ecosystems for Enhancing Multiculturality, 131–137.

  • Reychav, I., & McHaney, R. (2017). The relationship between gender and mobile technology use in collaborative learning settings: An empirical investigation. Computers & Education, 113, 61–74.

    Article  Google Scholar 

  • Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.

  • Sabah, N. M. (2016). Exploring students’ awareness and perceptions: Influencing factors and individual differences driving m-learning adoption. Computers in Human Behavior, 65, 522–533.

    Article  Google Scholar 

  • Schardt, C., Adams, M. B., Owens, T., Keitz, S., & Fontelo, P. (2007). Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Medical Informatics and Decision Making, 7(1), 16.

    Article  Google Scholar 

  • Seol, S., Sharp, A., & Kim, P. (2012). Use of a mobile application to promote scientific discovery learning: Students' perceptions towards and practical adoption of a mobile application. In Proceedings of the 13th annual conference on information technology education (pp. 121–126). ACM.

  • So, H., Choi, H., & Yoon, H. (2015). Understanding users’ perceived needs and concerns toward mobile application integration in primary science education in Korea. International Journal of Mobile Learning and Organization, 9(4), 315–333.

    Article  Google Scholar 

  • Talukder, M. (2012). Factors affecting the adoption of technological innovation by individual employees: An Australian study. Procedia-Social and Behavioral Sciences, 40, 52–57.

    Article  Google Scholar 

  • Tan, G. W., Ooi, K., Sim, J. J., & Phusavat, K. (2012). Determinants of mobile learning adoption: An empirical analysis. Journal of Computer Information Systems, 52(3), 82–91.

    Google Scholar 

  • Traxler, J. (2009). Learning in a mobile age. International Journal of Mobile and Blended Learning (IJMBL), 1(1), 1–12.

    Article  MathSciNet  Google Scholar 

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.

    Article  Google Scholar 

  • Yadegaridehkordi, E., Iahad, N. A., & Baloch, H. Z. (2013). Success factors influencing the adoption of M-learning. International Journal of Continuing Engineering Education and Life Long Learning, 23(2), 167–178.

    Article  Google Scholar 

  • Yeap, J. A., Ramayah, T., & Soto-Acosta, P. (2016). Factors propelling the adoption of m-learning among students in higher education. Electronic Markets, 26(4), 323–338.

    Article  Google Scholar 

  • Taherdoost, H. (2018). A review of technology acceptance and adoption models and theories. Procedia Manufacturing, 22, 960–967.

    Article  Google Scholar 

  • Weinberg, B. A. (2004). Experience and technology adoption.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bimal Aklesh Kumar.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1

Table 4 Selected primary studies

Appendix 2

Table 5 Grouping of factors

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, B.A., Chand, S.S. Mobile learning adoption: A systematic review. Educ Inf Technol 24, 471–487 (2019). https://doi.org/10.1007/s10639-018-9783-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-018-9783-6

Keywords

Navigation