Factors Influencing Acceptance to Use M-learning in Learning Arabic Language for Non-native Speakers in Saudi Universities

  • Faihan Dulaym Alotaibi
  • Saeedah Siraj
  • Wail Muil Alhaj Said Ismail
Palabras clave: Structural Equation Modeling. Language Interactivity, System Enjoyment Arabic Language Learning, Saudi Arabia, UTAUT

Resumen

The acceptance of mobile learning apparatus in language learning in the Arab world in general and Saudi Arabia in particular is not widespread as expected, despite the several advantages the m-learning has offered to the rest of the world. Therefore, the present study intended to uncover the factors that significantly predict the intention to use mobile learning for learning Arabic to non-native speakers in Saudi Universities. Relevant model was developed by extending the unified theory of acceptance and use of technology (UTAUT) as well as incorporating three other factors namely; language interactivity (LI), system enjoyment (SE) as well as content quali- ty. Quantitative method based on cross-sectional survey design was emplo- yed for data collection from 460 students of teaching Arabic to non-native speakers’ programs in Saudi Universities. The tool used for analysis in this study was a Partial Least Squares (PLS) which was used to test the model empirically. It was found from the study that language interactivity (LI), system enjoyment (SE), performance expectancy (PE), facilitating condi- tions (FC), and expected effort (EE) are significant in relation (either directly or indirectly) to behavioural intention (BI) to use m-learning. The implication for future research development as well as the limitations of the findings are also discussed the paper.

Biografía del autor/a

Faihan Dulaym Alotaibi
Department of Curriculum and Instruction Faculty of Education, University of Malaya
Saeedah Siraj
Department of Curriculum and Instruction Faculty of Education, University of Malaya
Wail Muil Alhaj Said Ismail
Department of Curriculum and Instruction Faculty of Education, University of Malaya

Citas

Abbad, M. M., Morris, D., & 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 Distance Learning. 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), 82-107.

Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8), 681-691. http://dx.doi.org/10.1016/j.im.2007.09.002 Al-Hujran, O., Al-Lozi, E., & Al-Debei, M. M. (2014). Get ready to mobile learning: Examining factors affecting college students' behavioral intentions to use m-learning in Saudi Arabia. Journal of Business Administration, 10(1), 111-128.

Ali, R. A., & Arshad, M. R. M. (2016). Perspectives of students’ behavior towards mobile learning (m- learning) in Egypt: an extension of the UTAUT model. Engineering, Technology & Applied Science Research, 6(4), 1109- 1114.

Ali, R. A., Rafie, M., & Arshad, M. (2018). Empirical Analysis on Factors Impacting on Intention to Use M-learning in Basic Education in Egypt. Inter- national Review of Research in Open and Distributed Learning, 19(2). https://doi.org/10.19173/irrodl.v19i2.3510

Almaiah, M. A., Jalil, M. A., & Man, M. (2016). Extending the TAM to exami- ne the effects of quality features on mobile learning acceptance. Journal of Computers in Education, 3(4), 453-485.

Alrawashdeh, T. A., Muhairat, M. I., & Alqatawnah, S. M. (2005). Factors affecting acceptance of web-based training system: using extended

UTAUT and structural equation modeling. Review Literature and Arts of the Americas, 1(3), 31–65. https://doi.org/10.1146/annurev.clinpsy.1.102803.144239

Alrawashdeh, T. A., Muhairat, M. I., & Alqatawnah, S. M. (2012). Factors affecting acceptance of webbased training system: Using extended UTAUT and structural equation modeling. Arxiv preprint arXiv: 1205.1904.

Alshalabi, I. A., & Elleithy, K. (2012). Effective m-learning design strategies for computer science and engineering courses. International Journal of Mobile Network Communications & Telematics (IJMNCT), 2(1), 1-11. doi: 10.5121/ijmnct.2012.2101.

Alzahrani, A., Stahl, B. C., & Prior, M. (2012). Developing an instrument for e-public services’ acceptance using confirmatory factor analysis: Middle East context. Journal of Organizational and End User Computing (JOEUC), 24(3), 18-44.

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

Attalla, S. M. E.-S., El-Sherbiny, R., Mokbel, W. A., El-Moursy, R. M., & Abdel-Wahab, A. G. (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.

Badwelan, A., Drew, S., &Bahaddad, A. A. (2016). Towards acceptance m-learning approach in higher education in Saudi Arabia. International Journal of Business and Management, 11(8), 12.

Bere, A. (2014). Exploring determinants for mobile learning user acceptance and use: an application of UTAUT. Paper presented at the ITNG 2014, 11th International Conference on Information Technology: New Generations, Las Vegas, Nevada, USA: IEEE Computer Society.

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

Chatzoglou P.D., Sarigiannidis L. Vraimaki, E., and Diamantidis E., (2009) Investigating Greek employees‟ intention to use web-based training, Compu- ters & Education, vol. 5, PP. 877–889,.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.): New York: Academic Press

Coursaris, C., & Hassanein, K. (2002). Understanding m-commerce: a consumer-centric model. Quarterly Journal of Electronic Commerce, 3, 247- 272.

Curtis, L., Edwards, C., Fraser, K. L., Gudelsky, S., Holmquist, J., Thornton, K. (2010). Adoption of social media for public relations by non-profit organi- zations. Public Relations Review, 36(1), 90-92.

Davis, F. Bagozzi R. and Warshaw P. (1992) Extrinsic and Intrinsic Motivation to Use Computer in the Workplace.” Journal of Applied Social Psychology, Vol. 22, PP. 1111-1132, July.

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

Dyson, L. E., Litchfield, A., Raban, R., & Tyler, J. (2009). Interactive classro- om mLearning and the experiential transactions between students and lecturer. Paper presented at the Proceedings of Ascilite, Auckland.

Fornell, C., & Cha, J. (1994). Partial least squares. In R. P. Bagozzi (Ed.), Advanced methods of marketing research (pp. 52–78). Cambridge, MA: Blac- kwell.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 13, 39-50.

Gupta, B., Dasgupta, S. and Gupta, A. (2008). Adoption of ICT in a govern- ment organization in a developing country: An empirical study. Journal of Strategic Information Systems, 17(2), 140-154.

Hair Jr., J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.

Hwang, G. J., & Tsai, C. 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), E65-E70.

Ibrahim, R., & Jaafar, A. (2011). User acceptance of educational games: A revised unified theory of acceptance and use of technology (UTAUT). World Academy of Science, Engineering and Technology, 77, 557-563.

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610.

Kuo, Y.-C., Walker, A. E., Schroder, K. E., & Belland, B. R. (2014). Interac- tion, internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35-50.

Lawrence, B. A. M. (2016). IPad Acceptance by English Learners in Saudi Arabia. English Language Teaching, 9(12), 34. https://doi.org/10.5539/elt.v9n12p34

Liaw, S.-S., Hatala, M., & Huang, H.-M. (2010). Investigating acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach. Computers & Education, 54(2), 446-454. Marchewka J., Liu C. and Kostiwa K.. (2007) An Application of the UTAUT

Model for Understanding Student Perceptions Using Course Management Software.” Communications of the IIMA, vol. 7, PP. 93-104,.

Martin, F., & Ertzberger, J. (2013). Here and now mobile learning: An experi- mental study on the use of mobile technology. Computers & Education, 68, 76-85.

Nassuora, A. B. (2012). Students acceptance of mobile learning for higher education in Saudi Arabia. American Academic & Scholarly Research Journal, 4(2), 24-30.

Nassuora, A. B. (2013). Students’ acceptance of mobile learning for higher education in Saudi Arabia. International Journal of Learning Management Systems, 1(1), 1. http://dx.doi.org/10.12785/ijlms/010101

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 accep- tance of information technology: Toward a unified view. MIS Quarterly, 27(3), 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 T.S. and Jong D. (2009) Students acceptance of web based learning system,” international symposium on web information system and application (WISA „09), Nanchang, China.

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.

Publicado
2019-08-03
Cómo citar
Dulaym Alotaibi, F., Siraj, S., & Said Ismail, W. M. A. (2019). Factors Influencing Acceptance to Use M-learning in Learning Arabic Language for Non-native Speakers in Saudi Universities. Opción, 35, 152-171. Recuperado a partir de https://produccioncientificaluz.org/index.php/opcion/article/view/27597