Integrated Model towards Computer Assisted Language Learning Acceptance: Empirical Case Study of Saudi Universities

Abdul Fattah Soomro


Maximum utilization of technology in all fields of life including language education by a country has become inevitable to survive in the competitive world. Saudi government has already invested a lot of efforts and public finance to adopt modern teaching practices using Information Communication Technology (ICT) to supplement English Language Teaching (ELT) in Saudi Arabia. The present study applies Technology Acceptance Model (TAM) as a theoretical model to explore the effects of different factors on the attitudes of teachers towards using Computer-Assisted Language Learning (CALL) in the language learning contexts of Saudi Arabia. The current study investigates the effect of perceived usefulness and perceived ease of use on the attitude and intended usage behavior of Saudi English as a Foreign Language (EFL) teachers towards using CALL. In addition to these two factors borrowed from TAM, three other variables: social influence, facilitating conditions and management support are added into the model. To test the hypothesized model, this study applied a quantitative questionnaire survey approach with participants chosen randomly from 10 different universities in Kingdom of Saudi Arabia. A total of 421 valid responses received through online questionnaire from the teachers were used for the analysis to achieve research objectives and hypotheses testing. Structural Equation Modeling Analysis was employed to analyze the data. The findings of this study are found very encouraging and provide sufficient support to the proposed model of the study, which was consisting of TAM as the foundation theory. According to TAM, postulation perceived usefulness and perceived ease of use both are two significant elements that determine attitude and intended usage behavior. These hypotheses were found significant, thus provided external validity to the TAM postulations. In addition, the findings suggested that social influence, management support, and facilitating conditions are important factors that influence individuals’ intended behavior towards CALL usage.


Computer-assisted Language Learning (CALL), Technology Acceptance Model (TAM), Second Language Acquisition (SLA)

Full Text:



AlKahtani, S. (2007). CALL integration: A proposal for in-service CALL training program for EFL faculty at Saudi Arabian Universities. College of Language & Translation Research Center, 42, 1-16.

Alrafi, A. (2009).Technology Acceptance Model. In: A. Alrafi (Ed.) Information Systems Adoption: A study of the technology acceptance model (pp.1-12). Manchester: VDM Verlag.

Al-Rojaie, Y. I. (2011, Nov). Saudi EFL Reading Teachers' Pedagogical Beliefs and Practices: A Qualitative Case Study. Journal of Arabic and Human Sciences, 5(1), 1-19.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.

Amaratunga, D., Haigh, R., Sarshar, M., & Baldry, D. (2002). Assessment of facilities management process capability: A NHS facilities case study. International Journal of Health, 15(6), 277-288.

Bertea, P. (2009). Measuring students' attitudes towards e-learning: A case study. Paper presented at the 5th international science Conference eLearning and Software for Education, Bucharest, Romania.

Byrne, M. M. (2001). Linking philosophy, methodology, and methods in qualitative research. AORN journal, 73(1), 207-210.

Bryman, A., & Bell, E. (2011). Business Research Methods (3rd ed.). USA: Oxford University Press.

Creswell, J. W., & PlanoClark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). London: Sage.

Chandio, F., Irani, Z., Abbasi, M. S., & Nizamani, H. A. (2013). Acceptance of online banking information systems: an empirical case in a developing economy. Behaviour & Information Technology, 32(7), 668-680.

Chen, Y., Chen, C., Lin, Y. & Yeh, R. (2007). Predicting College Student' Use of E-Learning Systems: An attempt to extend technology acceptance model. Retrieved [April January, 2018] from

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.

Clements, J. A. & Bush, A. A. (2011, March 25-26). Habitual is use and continuance. Proceedings of the Southern Association for Information Systems Conference, Atlanta, GA, US.

Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions, and behavioural impacts. International Journal of Man- Machine Studies, 38(3), 475-487.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

Dillon, A., & Morris, M. G. (1996). User acceptance of information technology: Theories and models. Annual Review of Information Science and Technology, 31, 3-32.

Easterby-Smith, M., Thorpe, R., & Lowe, L. (2003). Management Research: An Introduction. London: Sage.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18 (1), 39‐50.

Fullan, M. G. (1991). The meaning of educational change. In M. G. Fullan, The new meaning of educational change (pp. 30-46). New York: Teachers College Press.

Gall, M. D., Gall, J. P., & Borg, W. R. (2003). Educational Research: An introduction (7th ed.). Boston, MA: Allyn and Bacon.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: the better approach to structural equation modeling? Long Range Planning 45 (6), 312-319He, G., & Ma, L. (2007). On the Shifting Orientation of CALL towards Post-modernity. Foreign Language Education, 1(1).

Jones, C., & Cross, S. (2009). Is there a net generation coming to university? In: ALT-C 2009 “In Dreams Begins Responsibility”: Choice, Evidence and Change, 8-10 September 2009, Manchester, UK.

Khan, I. A. (2011). Learning difficulties in English: Diagnosis and pedagogy in Saudi Arabia. Educational Research, 2(7), 1248-1257.

Lambropoulos, Christopoulou, & Vlachos. (2006). Culture-Based Language Learning Objects: A CALL Approach for a Ubiquitous World. In P. Zaphiris, & G. Zacharia, User-Centered Computer Aided Language Learning (pp. 22-40).Hershey,PA Idea Group.

Lee, J. S., Cho, H., Gay, G., Davidson, B. & Ingraffea, A. (2003). Technology acceptance and social networking in distance learning. Educational Technology & Society, 6(2), 50-61.

Li, Y. & Huang, J. (2009). Applying theory of perceived risk and technology acceptance model in the online shopping channel. World Academy of Science, Engineering and Technology, 53(1), 919-925.Levy, M. (1997). Computer assisted language learning: Context and conceptualization. Oxford: Clarendon Press.

Lucas, H. C. (1997). Technology acceptance and performance: A field study of Broker workstations. Center for digital economy research, Stern School Business, working paper.

Mahdi, H. S. (2013). Issues of Computer Assisted Language Learning Normalization in EFL Contexts. International Journal of Linguistics, 5(1), 191-203.

Masrom, M. (2007, May 21-24). Technology acceptance model and e-learning. Paper presented at the 12th International Conference on Education, Sultan Hassanal Bolkiah Institute of Education, Universiti Brunei Darussalam.

Neuman, W. L. (2011). Social Research Methods: Qualitative and Quantitative Approaches. USA: Allyn and Bacon.

Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Educational Technology & Society, vol. 12, No. 3, 150–162

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879.

Price, L., & Kirkwood, A. (2008). Technology in the United Kingdom's higher education context. In S. Scott, & K. Dixon (Eds.), The 21st Century, Globalised University: Trends and Development in Teaching and Learning (pp. 83–113). Perth: Black Swan.

Proffitt, L.N. (2008). A study of the influence of learner readiness on academic success and student perceptions of online learning. A dissertation presented in partial fulfilment of the requirements for the degree Doctor of Philosophy, Capella University.

Ramayah, T. & Ignatius, J. (2005). Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. Journal of Systems Management, vol. 3, No. 3, 36-51.

Shen, D., Laffey, J., Lin, Y. & Huang, X. (2006). Social influence for perceived usefulness and ease-of-use of course delivery systems. Journal of Interactive Online Learning, vol. 5, No. 3, Winter. Retrieved [May 12, 2017] from

Soomro, A. F., & Almalki, M. S. (2017). Language Practitioners’ Reflections on Method-Based and Post-Method Pedagogies. English Language Teaching, 10(5), 234-242.

Sumak, B., Hericko, M., Pusnik, M. & Polancic,G. (2011). Factors affecting acceptance and use of Moodle: An empirical study based on TAM. Informatica, vol. 35, 91–100.

Tashakkori, A., & Teddlie, C. (2003). Handbook of mixed methods in social and behavioral research. London: Sage.

Tatweer. (2008). Retrieved Feb 12, 2014, from King Abdullah Project for General Education Development:

Yee, H. T. K., Luan, W. S., Ayub, A. F. & Mahmud, R. (2009). A review of the literature: determinants of online learning among students. European Journal of Social Sciences, 8(2), 246-252.



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

2013-2023 (CC-BY) Australian International Academic Centre PTY.LTD.

International Journal of Education and Literacy Studies  

You may require to add the '' domain to your e-mail 'safe list’ If you do not receive e-mail in your 'inbox'. Otherwise, you may check your 'Spam mail' or 'junk mail' folders.