FACTOR AFFECTING ICT-BASED LEARNING IN HIGHER EDUCATION IN PHNOM PENH, CAMBODIA

Authors

  • Bunteng Long
  • Kitti Phothikitti
  • Rawin Vongurai

Keywords:

Higher education, ICT-Based leaning, performance expectancy, Effort expectancy, Behavioral intention, Use behavior

Abstract

The purpose of this study was to examine the factors affecting the adoption of ICT- based learning of students in higher education in Phnom Penh, Cambodia. The conceptual framework was developed from previous studies which includes facilitating conditions, self-efficacy, perceived ease of use, performance expectancy, effort expectancy, behavioral intention and use behavior. The quantitative method was applied to distribute a questionnaire to 527 respondents. The multistage sampling technique was conducted in nonprobability sampling, using judgmental sampling to select undergraduate students in three private universities, quota sampling to calculate the sample size of each group, and convenience sampling to distribute a questionnaire online and offline. Before collecting data, Item-Objective Congruence Index (IOC) and Cronbach’s Alpha were employed to validate constructs. Confirmatory Factor Analysis (CFA) was used to verify convergent and discriminant validity, and goodness of fit indices. Structural Equation Model (SEM) was carried out to test the relationship among variables. The findings showed that performance expectancy and effort expectancy significantly affected behavioral intention, and behavioral intention positively affected use behavior. However, the results contradicted that facilitating condition, self-efficacy, and perceived ease of use were not significant on behavioral intention. Government, educators and practitioners are recommended to encourage significant factors to increase ICT-based learning adoption and learning efficiency of students by clearly communicating the benefits of system usage, improving system to be user-friendly and promoting the usage of the system more effectively to increase the level of system adoption among students.

References

Agarwal, R., Sambamurthy, V., & Stair, R. M. (2000). The evolving relationship between general and specific computer selfefficacy: An empirical assessment. Information Systems Research, 11(4), 418-430

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

Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin, 82(2), 261.

Alenezi, A., Abdul Malek, A. K., & Veloo, A. (2010). An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing The students’ intention to use e-learning: A case study from Saudi Arabian government universities. Turkish Online Journal of Educational Technology, 9, 22-34.

Arbuckle, J. J. (1995). AMOS user’s guide. Chicago, IL: SmallWaters.

Arif, M. (2017). Corporate social responsibility and loyalty: Intervening influence of customer satisfaction and trust. Cogent Business & Management, 4(1), 1-10. Retrieved from DOI:10.1080/23311975.2017.1396655

Ariff, M. S. M., Yeow, S. M., Zakuan, N., Jusoh, A., & Bahari, A. Z. (2012). The effects of computer self-efficacy and technology acceptance model on behavioral intention in internet banking systems. Procedia-Social and Behavioral Sciences, 57, 448-452.

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

Bandyopadhyay, K., & Fraccastoro, K. A. (2007). The effect of culture on user acceptance of information technology. Communications of the Association for Information Systems, 19(1), 23.

Blurton, C. (1999). New directions of ICT-use in education. UNESCO. Retrieved from http://www.unesco.org/education/educprog/lwf/dl/edict.pdf

Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303-316.

Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Retrieved fromhttps://doi.org/10.4324/9780203807644

Chang, A. (2012). UTAUT and UTAUT 2: A review and agenda for future research. The Winners, 13(2), 10-114.

Changchit, C. (2014). Students’ perceptions of cloud computing. Issues in Information Systems, 15(1), 312-322.

Chau, P. Y., & Hu, P. J. (2002). Examining a model of information technology acceptance by individual professionals: An exploratory study. Journal of Management Information Systems, 18(4), 191-229.

Chen, H. R., & Tseng, H. F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and Program Planning, 35(3), 398-406.

Chen, J. L. (2011). The effects of education compatibility and technological expectancy on e-learning acceptance. Computers and Education, 57(2), 1501-1511.

Cheok, M. L., & Wong, S. L. (2015). Predictors of e-learning satisfaction in teaching and learning for school teachers: A literature review. International Journal of Instruction, 8(1), 75-90.

Chui, H., Hsieh, Y., Kao, Y., & Lee, M. (2007). The determinants of email receivers’ disseminating behaviors on the internet. Journal of Advertising Research–JAR, 47. Retrieved from https://doi.org/10.2501/S0021849907070547.

Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13(3), 319-339.

Derntl, M., Neumann, S., Griffiths, D., & Oberhuemer, P. (2011). The conceptual structure of IMS learning design does not impede its use for authoring. IEEE Transactions on Learning Technologies, 5(1), 74-86.

Doll, W. J., & Torkzadeh, G. (1988). The measurement of end-user computing satisfaction. MIS Quarterly, 12(2), 259-274.

Dulle, F. W., & Minishi-Majanja, M. K. (2011). The suitability of the Unified theory of acceptance and use of technology (UTAUT) model in open access adoption studies. Information Development, 27(1), 32-45.

Filippini, R., Forza, C., & Vinelli, A. (1998). Trade-off and compatibility between performance: Definitions and empirical evidence. International Journal of Production Research, 36(12), 3379-3406.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

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Published

2022-10-21