Factors Affecting Financial Accounting Students’ Behavioural Intention toward Mobile Learning in Government Science and Technical Colleges in Gombe State

Suleiman Hayatu, Ahmad Aliyu Deba, Babangida Haruna

Abstract


The main objective of the study focuses on determining the factors affecting behavioural intention toward m-learning among financial accounting students of government science and technical colleges (GSTCs) in Gombe State. In achieving this, four hypotheses were raised to guide the study. The studyemploys a descriptive survey design. The study is based on the unified theory of acceptance and use of technology (UTAUT) model. A sample of 175 students was taken out of the total population of 312 financial accounting students of GSTCs using Yamane (1967) the formula for determining sample size. A proportionate random sampling technique was used in drawing the sample from the three GSTCs since they are the only colleges among the GSTCs offering financial accounting. A structured questionnaire with a five-point Likert scale was developed, validated and its reliability ascertained using Cronbach alpha. A reliability coefficient of 0.78 was found. Data collected were analyzed using Pearson product-moment the correlation coefficient, multiple regression and ANOVA statistics. The finding of the study shows that all the four constructs of the UTAUT model significantly affect financial accounting students’ behavioural intention toward m-learning with 52 per cent of the variance. The study recommends that another study needs to be conducted to find out the behavioural intention of both financial accounting teachers and students toward the adoption of m-learning for teaching and learning of financial accounting in GSTCs in Gombe state in particular and Nigeria at large.The main objective of the study focuses on determining the factorsaffecting behavioural intention toward m-learning among financialaccounting students of government science and technical colleges(GSTCs) in Gombe State. In achieving this, four hypotheses wereraised to guide the study. The study employs a descriptive surveydesign. The study is based on the unified theory of acceptance anduse of technology (UTAUT) model. A sample of 175 students wastaken out of the total population of 312 financial accounting studentsof GSTCs using the Yamane (1967) formula for determining sample size.A proportionate random sampling technique was used in drawing thesample from the three GSTCs since they are the only colleges amongthe GSTCs offering financial accounting. A structured questionnairewith a five-point Likert scale was developed, validated and its reliabilityascertained using Cronbach alpha. A reliability coefficient of 0.78 wasfound. Data collected were analyzed using Pearson product-momentthe correlation coefficient, multiple regression and ANOVA statistics. Thefinding of the study shows that all the four constructs of the UTAUTmodel significantly affect financial accounting students’ behaviouralintention toward m-learning with 52 per cent of the variance. The studyrecommends that another study needs to be conducted to find out thebehavioural intention of both financial accounting teachers andstudents toward the adoption of m-learning for teaching and learningof financial accounting in GSTCs in Gombe state in particular andNigeria at large.

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References


Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179-211.

Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 23(4), 665-683

Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An integrated model. Education and Information Technologies. https://doi.org/10.1007/s10639-019-10094-2

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. Jordan Journal of Business Administration, 10 (1).

Chaka, J. G., & Govender, I. (2020). Implementation of mobile learning using a social network platform: Facebook. Problems of Education in the 21st Century, 78(1), 24-47. https://doi.org/10.33225/pec/20.78.24

Chelvarayan, A., Chee, J. E., Yoe, S. F., & Hashim, H. (2020). Students’ perceptions on mobile learning: The influencing factors. International Journal of Education Psychology and Counselling, 5(37), 1-9. https://doi.org/10.35631/ijepc.537001

Crompton, H. (2013). A historical overview of mobile learning: Toward learner-centered education. In Z. L. Berge & L. Y. Muilenburge (Eds.), Handbook of mobile learning, Florence KY: Routledge.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika Journal, 16, 297-334.

Dimitrious, B., Labros, S., Nicholaos, K., Maria, K., & Athanasios, K. (2013). Traditional teaching method vs teaching through the application of information and communication technologies in the accounting field. European Scientific Journal, 9 (28).

Donaldson, R. L. (2011). Student acceptance of mobile learning. Unpublished doctoral dissertation, Florida State University, USA.

El-Hussain, M. O. M., & Cronje, J. C. (2010). Defining mobile learning in the higher education landscape. Educational Technology and Society Journal, 13 (3), 12-21.

Hamzah, W. W., Yusoff, M., Ismail, I., & Yacob, I. (2020). The behavioural intention of secondary school students to use tablet as a mobile learning device. International Journal of Interactive Technologies, 14(13), 161-171. https://do.org/10.3991/ijim.v14i13.13027

Henry, S. F., & James, F. (2015). Mobile learning in the 21st century higher education classroom: Readiness, experiences and challenges. Caribbean Curriculum Journal, 23, 99-120.

Hoi, V. N. (2020). Understanding higher education learner acceptance and use of mobile devices for language learning: A Rasch-based path modelling approach. Computers and Education, 146. https://do.org/10.1016/j.compedu.2019.103761

Jackman, G. (2014). Investigating the factors influencing students’ acceptance of mobile learning: The Cave Hill campus experience. Caribbean Educational Research Journal, 2 (2), 14-32.

Jairak, K., Praneetpolgrang, P., & Mekhabunchakij, K. (2009). An acceptance of mobile learning for higher education students in Thailand. The International Journal of the Computer, the Internet and Management, 17(SP3), 36.1–36.8.

Kutluk, F. A., Donmez, A., Gulmez, M., & Terzioglu, M. (2015). A re-research about usage of mobile devices in accounting lessons. World Conference on Educational Sciences (WCES), Novotel Athens Convention Centre, Athens, Greece.

Longe, O. R., & Kazeem, R. A. (2012). Essential financial accounting for senior secondary schools. Tonad.

Mtebe, J. S. & Raisamo, R. (2014). Investigating students’ behavioral intention to adopt and use mobile learning in higher education in East Africa. International Journal of Education and Development using Information and Communication Technology (IJEDICT), 10 (3), 4-20.

Osang, F. B., & Ngole, J. (2014). M-learning implementation: Readiness of the National Open University of Nigeria. International Journal of Emerging Technology & Advanced Engineering, 4 (11).

Osang, F. B., Ngole, J., & Tsuma, C. (2013). Prospects and challenges of mobile learning implementation in Nigeria: A case study of national Open University of Nigeria. International Conference on ICT for Africa.

Shorfuzzaman, M. & Alhussein, M. (2016). Modelling learners’ readiness to adopt mobile learning: A perspective from a GCC higher education institution. Mobile Information Systems Journal. http//dx.doi.org/10.1155/2016/698224

Staples, J., Collum, T., & McFry, K. (2016). Mobile device in the accounting classroom. Journal of Accounting Educators.

Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.

Tagoe, M., & Abakah, E. (2014). Determining distance education students’ readiness for mobile learning at university of Ghana using the theory of planned behavior. International Journal of Education and Development using Information and Communication Technology, 10 (1), 91-106.

Thomas, T. D., Singh, L., & Gaffar, K. (2013). The utility of the UTAUT model in explaining mobile learning adoption in higher education in Guyana. International Journal of Education and Development using Information and Communication Technology, 9(3), 71-85.

Titus, A. U. & Okeke, A. U. (2012). M- Learning in Nigerian universities: Challenges and possibilities. Global Awareness Society International Conference. New York.

Traxler, J., & Koole, M. (2014). The theory paper: What is the future of mobile learning? 10th International Conference on Mobile Learning, 289-293.

Ugur, N. G., Koc, T., & Koc, M. (2016). An analysis of mobile learning acceptance by college students. Journal of Education and Instructional Studies in the World, 6 (2).

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425–478.

Wang, S., & Michael, H. (2006). Limitations of mobile phone learning. The JALT CALL Journal, 2 (1).

Wei-Han Tan, G., Sim, J., Keng-Boon, O., & Phusavat, K. (2012). Determinants of mobile learning adoption: An empirical analysis. Journal of Computer Information Systems, 52 (3), 82-91.

Welch, R., Alade, T., & Nichol, L. (2020). Mobile learning adoption at a science museum. In Arai, K., Kapoor, S., Bhatia, R. (Eds.), Intelligent Computing SAI 2020. Advances in Intelligent Systems and Computing, Vol 1228, Springer, Cham. https://do.org/10.1007/978-3-030-52249-0_49

Wu, X., Tam, C. M., & Fang, S. (2020). Users’ behavioural intention toward m-learning in Tourism English education: A case study of Macao. In Lee, L. K., U, L. H., Wang, F. L. Cheung, S. K. S., Au, O., Li, K. S. (Eds.), Technology in Education. Innovations for Online Teaching and Learning ICTE 2020. Communications in Computer and Information Science, Vol 1362. Springer, Singapore. https://do.org/10.1007/978-981-33-4594-2_26

Yamane, T. (1967). Statistics, an introductory analysis (2nd ed.). Harper and Row.


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