Understanding Factors Affecting Behavioral Intention to Use Blended Learning of Business Major Undergraduates in a Public University in Chengdu, China
Article Sidebar
Main Article Content
Abstract
Purpose: Given the advancements in information technology and the implications of COVID-19 on education, the blended learning can enhance accessibility to university education. The study examines the factors influencing business major undergraduates’ behavioral intention towards blended learning. Research design, data, and methodology: Data were gathered quantitatively from a sample of 500 undergraduate students using an organized electronic questionnaire. The researchers employed judgmental sampling and quota sampling. The data analysis method used was structural equation modeling, and confirmatory factor analysis (CFA) was used to verify the validity of the data gathered. Results: The data analysis results fully validated all of the hypotheses, with attitude showing the most direct influence on undergraduate business majors’ behavioral intention in blended learning. Perceived usefulness and perceived ease of use significantly affect attitude. Social influence, self-efficacy and facilitating conditions have a significant effect on behavioral intention. Conclusions: To facilitate the progress of blended learning, university administrators, educators, and students need to consider various elements that influence students’ willingness to use blended learning. Furthermore, according to the study’s findings, efforts should be made to improve undergraduates’ perceptions of the utility and usability of blended learning to improve their favorable attitude towards it, thereby further promoting their intention to adopt it.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data, or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution License (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
References
Abdallah, N., Ahlan, A. R., & Abdullah, O. A. (2019). The Role of Quality Factors on Learning Management Systems Adoption from Instructor’s Perspectives. The Online Journal of Distance Education and E-Learning, 7(2), 133-150.
Abdelwahed, N. A. A., & Soomro, B. A. (2023). Attitudes and Intentions Towards the Adoption of Mobile Learning during COVID-19: Building an Exciting Career through Vocational Education. Education + Training, 65(2), 210-231. https://doi.org/10.1108/et-02-2022-0048
Agarwal, R., & Karahanna, E. (2000). Time Flies When You are Having Fun: Cognitive Absorption and Beliefs about Information Technology Usage. MIS Quarterly, 24(4), 665-694. https://doi.org/10.2307/3250951
Ajzen, I. (1991). The Theory of Planned Behavior, Organizational Behavior and Human Decision Processes. Journal of Leisure Research, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-t
Al-Emran, M., Granić, A., Al-Sharafi, M. A., Ameen, N., & Sarrab, M. (2021). Examining the Roles of Students’ Beliefs and Security Concerns for Using Smartwatches in Higher Education. Journal of Enterprise Information Management, 34(4), 1229-1251. https://doi.org/10.1108/jeim-02-2020-0052
Alharbi, S., & Drew, S. (2014). Using the Technology Acceptance Model in Understanding Academics’ Behavioral Intention to Use Learning Management Systems. International Journal of Advanced Computer Science and Applications, 5(1), 143-155. https://doi.org/10.14569/ijacsa.2014.050120
Ali, M., Raza, S. A., Qazi, W., & Puah, C. H. (2018). Assessing E-learning System in Higher Education Institutes: Evidence from Structural Equation Modelling. Interactive Technology and Smart Education, 15(1), 59-78. https://doi.org/10.1108/itse-02-2017-0012
Al-Mamary, A., Yaser, H., Shamsuddin, A., Aziati, A., & Al-Maamari, M. (2015). Adoption of Management Information Systems in Context of Yemeni Organizations: A Structural Equation Modeling Approach. Journal of Digital Information Management, 13(6), 429-444.
Bagdi, H., Bulsara, H., Sankar, D., & Sharma, L. (2023). The Transition from Traditional to Digital: Factors that Propel Generation Z’s Adoption of Online Learning. International Journal of Educational Management, 37(3), 695-717. https://doi.org/10.1108/ijem-01-2023-0003
Bagozzi, R., & Yi, Y. (1988). On The Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/bf02723327
Bentler, P. M., & Bonett, D. G. (1980). Significance Tests and Goodness of Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588
Buabeng-Andoh, C. (2018). Predicting Students’ Intention to Adopt Mobile Learning: A Combination of Theory of Reasoned Action and Technology Acceptance Model. Journal of Research in Innovative Teaching & Learning, 11(2), 178-191.
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. https://doi.org/10.1016/j.evalprogplan.2011.11.007
Chen, J. (2022). On the Cultivation Model of Innovative Talents in Colleges and Universities Based on Blended Teaching. Journal of Education, 1, 87-98.
Cigdem, H., & Ozturk, M. (2016). Factors Affecting Students’ Behavioral Intention to Use LMS at A Turkish Post-Secondary Vocational School. International Review of Research in Open and Distributed Learning, 17(3), 276-295.
Dakduk, S., Santalla-Banderali, Z., & Woude, D. (2018). Acceptance of Blended Learning in Executive Education. SAGE Open, 8(3), 1-16. https://doi:10.1177/2158244018800647
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
Fokides, E. (2017). Greek Pre-Service Teachers’ Intentions to Use Computers as In-Service Teachers. Contemporary Educational Technology, 8(1), 56-75. https://doi.org/10.30935/cedtech/6187
Foon, Y. S., & Fah, B. C. Y. (2011). Internet Banking Adoption in Kuala Lumpur: An Application of UTAUT Model. International Journal of Business and Management, 6(4), 161-167.
Gupta, K. P. (2020). Investigating the Adoption of MOOCs in a Developing Country. Interactive Technology and Smart Education, 17(4), 355-375. https://doi.org/10.1108/itse-06-2019-0033
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.) Prentice-Hall.
Jin, C., & Zhang, M. (2023). Exploration and Practice of IT Ability Training Model for New Business Professionals. Exploration of Higher Education, 01, 51-56.
Jnr, B. A., Kamaludin, A., Romli, A., Raffei, A. F. M., Abdullah, A., Shukor, N. A., Nordin, M. S., & Baba, S. (2020). Predictors of Blended Learning Deployment in Institutions of Higher Learning: Theory of Planned Behavior Perspective. The International Journal of Information and Learning Technology, 37(4), 179-196.
John, S. P. (2015). The Integration of Information Technology in Higher Education: A Study of Faculty’s Attitude Towards IT Adoption in the Teaching Process. Contaduría y Administración, 60, 230–252. https://doi.org/10.1016/j.cya.2015.08.004
Long, N., & Khoi, B. (2020). The Intention to Study Using Zoom During the SARS-CoV-2 Pandemic. International Journal of Emerging Technology in Learning, 15(21), 195-216. https://doi.org/10.3991/ijet.v15i21.16777
Lwoga, E. T., & Komba, M. (2015). Antecedents of Continued Usage Intentions of Web-based Learning Management System in Tanzania. Education + Training, 57(7), 738-756. https://doi.org/10.1108/et-02-2014-0014
Mittal, A., Mantri, A., Tandon, U., & Dwivedi, Y. K. (2021). A Unified Perspective on the Adoption of Online Teaching in Higher Education during the COVID-19 Pandemic. Information Discovery and Delivery, 50(2), 117-132. https://doi.org/10.1108/idd-09-2020-0114
Mueller, S. L., & Thomas, A. S. (2001). Culture and Entrepreneurial Potential: A Nine Country Study of Locus of Control and Innovativeness. Journal of Business Venturing, 16, 51-75. https://doi.org/10.1016/S0883-9026(99)00039-7
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Pedroso, R., Zanetello, L., Guimaraes, L., Pettenon, M., Goncalves, V., Scherer, J., Kessler, F., & Pechansky, F. (2016). Confirmatory Factor Analysis (CFA) of the Crack Use Relapse Scale (CURS). Archives of Clinical Psychiatry, 43(3), 37-40. https://doi.org/10.1590/0101-60830000000081
Pramana, E. (2018). Determinants of the Adoption of Mobile Learning Systems among University Students in Indonesia. Journal of Information Technology Education: Research, 17, 365-398. https://doi.org/10.28945/4119
Raman, A., Thannimalai, R., Rathakrishnan, M., & Ismail, S. N. (2022). Investigating the Influence of Intrinsic Motivation on Behavioral Intention and Actual Use of Technology in Moodle Platforms. International Journal of Instruction, 15(1), 1003-1024. https://doi.org/10.29333/iji.2022.15157a
Ramdhony, D., Mooneeapen, O., Dooshila, M., & Kokil, K. (2021). A Study of University Students’ Attitude towards Integration of Information Technology in Higher Education in Mauritius. Higher Education Quarterly, 75(2), 348-363. https://doi.org/10.1111/hequ.12288
Raza, S. A., Qazi, Z., Qazi, W., & Ahmed, M. (2022). E-learning in Higher Education during COVID-19: Evidence from Blackboard Learning System. Journal of Applied Research in Higher Education, 14(4), 1603-1622. https://doi.org/10.1108/jarhe-02-2021-0054
Riyath, M. I. M., & Rijah, U. L. M. (2022). Adoption of a Learning Management System among Educators of Advanced Technological Institutes in Sri Lanka. Asian Association of Open Universities Journal, 17(2), 161-177.
Rudhumbu, N. (2022). Applying the UTAUT2 to Predict the Acceptance of Blended Learning by University Students. Asian Association of Open Universities Journal, 17(1), 15-36. https://doi.org/10.1108/aaouj-08-2021-0084
Salloum, S. A., Maqableh, W., Mhamdi, C., Kurdi, B. A., & Shaalan, K. (2018). Studying the Social Media Adoption by University Students in the United Arab Emirates. International Journal of Information Technology and Language Studies, 2(3), 83-95.
Sica, C., & Ghisi, M. (2007). The Italian Versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric Properties and Discriminant Power. In M. A. Lange (Ed.). Leading — Edge Psychological Tests and Testing Research (pp. 27-50). Nova Science Publishers.
Singh, R., & Tewari, A. (2021). Modeling Factors Affecting Online Learning Adoption: Mediating Role of Attitude. International Journal of Educational Management, 35(7), 1405-1420. https://doi.org/10.1108/ijem-05-2021-0198
Tagoe, M. A., & 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.
Tan, P. J. B. (2013). Applying the UTAUT to Understand Factors Affecting the Use of English E-learning Websites in Taiwan. SAGE Open, 3(4), 1-12. https://doi.org/10.1177/2158244013503837
Tarhini, A. (2013). The Effects of Individual-Level Culture and Demographic Characteristics on E-Learning Acceptance in Lebanon and England: A Structural Equation Modelling Approach [Doctoral Dissertation, Brunel University].
Tarhini, A., Masa’deh, R. E., Al-Busaidi, K. A., Mohammed, A. B., & Maqableh, M. (2017). Factors Influencing Students’ Adoption of E-learning: A Structural Equation Modeling Approach. Journal of International Education in Business, 10(2), 164-182. https://doi.org/10.1108/jieb-09-2016-0032
Valtonen, T., Kukkonen, J., Kontkanen, S., Sormunen, K., Dillon, P., & Sointu, E. (2015). The Impact of Authentic Learning Experiences with ICT on Pre-service Teachers’ Intentions to Use ICT for Teaching and Learning. Computers & Education, 81, 49-58. https://doi.org/10.1016/j.compedu.2014.09.008
Venkatesh, V., & Davis, F. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 12(1), 157-178. https://doi.org/10.2307/41410412
Wang, G., & Fu, S. (2018). Construction of Learner Profile Model and Development of Scale in the Network Environment. Journal of Distance Education, 3, 64-74.
Wang, L. Y. K., Lew, S. L., Lau, S. H., & Leow, M. C. (2019). Usability Factors Predicting Continuance of Intention to Use Cloud E-learning Application. Heliyon, 5(6), 1-12. https://doi: 10.1016/j.heliyon.2019.e01788.
Wang, Y. S., Wang, Y. M., Lin, H. H., & Tang, I. (2003). Determinants of User Acceptance of Internet Banking: An Empirical Study. International Journal of Service Industry Management, 14(5), 501-519. https://doi.org/10.1108/09564230310500192
Wolf, E., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety. Educational and Psychological Measurement, 73(6), 913-934.
Yang, X., Zhou, H., & Zheng, X. (2021). Characteristics and Implications of Online Teaching Implementation in Universities during the Epidemic: An Analysis of Online Teaching Quality Report and Online Teaching Cases. Electrochemical Education Research, 10, 53 -62.
Yu, X. (2023). Development and Future Prospects of Digital Teaching in Higher Education. Higher Education in China, 1, 4-7.
Zhang, Y., Fang, Y., Wei, K. K., & Wang, Z. (2012). Promoting the Intention of Students to Continue Their Participation in E‐learning Systems. Information Technology & People, 25(4), 356-375. https://doi.org/10.1108/09593841211278776