Factors Impacting Behavioral Intention to Use Blended Learning for English Courses in Higher Vocational Colleges in China
Main Article Content
Abstract
Purpose: The study investigates the impact of five independent variables (self-efficacy, facilitating conditions, performance expectancy, effort expectancy, and attitude) on the dependent variable (behavioral intention). Besides, it aims to identify significant differences between variables. Research design, data, and methodology: The research employed the Index of Item-Objective Congruence for validity and Cronbach’s Alpha in a pilot test (n=38) for reliability. With the non-probabilistic sampling technique, 495 valid responses from students at Anshun Technical College were analyzed by multiple linear regression to verify the significant relationship between variables. Following this, a 14-week Intervention Design Implementation (IDI)was conducted among 33 students. Afterward, the quantitative results from post-IDI and pre-IDI were analyzed in the paired-sample t-test for comparison. Results: Multiple linear regression revealed that performance expectancy, effort expectancy, and attitude had a significant impact on students’ behavioral intention to use blended learning for English courses, while self-efficacy and facilitating conditions had no significant impact on students’ behavioral intention. Finally, the results from the paired-sample t-test for comparison demonstrated significant differences in Performance Expectancy, Effort Expectancy, Attitudes, and Behavioral Intention between the post-IDI and pre-IDI stages. Conclusions: This research strives to explain the factors impacting students’ behavioral intention to use blended learning to enhance their behavioral intentions and improve the effective implementation of blended learning in higher vocational colleges in China.
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
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-t
Ajzen, I., & Fishbein, M. A. (1975). Belief, attitude, intention, and behavior: An introduction to Theory and research (1st ed.). Addison-Wesley.
Alexander, B., Ashford-Rowe, K., Barajas-Murph, N., Dobbin, G., Knott, J., McCormack, M., Pomerantz, J., Seilhamer, R., & Weber, N. (2019, July 29). Horizon report 2019 higher education edition. EDU19. The Learning and Technology Library. https://www.learntechlib.org/p/208644/
Al-Fraihat, D., Joy, M., & Sinclair, J. (2020). Evaluating E-learning systems success: an empirical study. Computers in Human Behavior, 102, 67-86. https://doi.org/10.1016/j.chb.2019.08.004
Ali, A., Khan, R. M. I., & Alouraini, A. (2023). A Comparative Study on the Impact of Online and Blended Learning. SAGE Open, 13(1), 1-10. https://doi.org/10.1177/21582440231154417
Alleyne, P., & Lavine, M. (2013). Factors influencing accountants' behavioural intentions to use and actual usage of enterprise resource planning systems in a global development agency. Journal of Financial Reporting and Accounting, 11(2), 179-200. https://doi.org/10.1108/JFRA-11-2011-0017
Al-Mamary, Y. H. S., Siddiqui, M. A., Abdalraheem, S. G., Jazim, F., Abdulrab, M., Rashed, R. Q., Alquhaif, A. S., & Aliyu Alhaji, A. (2023). Factors impacting Saudi students’ intention to adopt learning management systems using the TPB and UTAUT integrated model. Journal of Science and Technology Policy Management, 2053-4620. https://doi.org/10.1108/JSTPM-04-2022-0068
Al Maskari, A. (2019). Student engagement in blended learning instructional design: an analytical study. Learning and Teaching in Higher Education: Gulf Perspectives, 15(2), 61-79. https://doi.org/10.18538/lthe.v15.n2.283
Anthony, B. J. (2019). Green information system integration for environmental performance in organizations: an extension of belief–action–outcome framework and natural resource-based view theory. Benchmarking: An International Journal, 26(3), 1033-1062. https://doi.org/10.1108/bij-05-2018-0142
Anthony, J. B., Kamaludin, A., Romli, A., Mat Raffei, A. F. A. L., Eh Phon, D. N., Abdullah, A., Leong Ming, G. A., Shukor, N., Shukri Nordin, M., & Baba, S. (2020). Predictors of blended learning deployment in institutions of higher learning: theory of planned behavior perspective. International Journal of Information and Learning Technology, 37(4), 179-196. https://doi.org/10.1108/IJILT-02-2020-0013
Asare, A., Yun-Fei, S., & Adjei-Budu, K. (2016). Adoption of e-learning in higher education: Expansion of UTAUT model. European Academic Research, 3, 13236-13259.
Ayob, H. H., Daleure, G., Solovieva, N., Minhas, W., & White, T. (2023). The effectiveness of using blended learning teaching and learning strategy to develop students' performance at higher education. Journal of Applied Research in Higher Education, 15(3), 650-662. https://doi.org/10.1108/JARHE-09-2020-0288
Azizi, S. M., Roozbahani, N., & Khatony, A. (2020). Factors affecting the acceptance of blended learning in medical education: application of UTAUT2 model. BMC Medical Education, 20(367), 1-9.
Bagdi, H., & Bulsara, H. P. (2023). Understanding the role of perceived enjoyment, self-efficacy, and system accessibility: digital natives' online learning intentions. Journal of Applied Research in Higher Education, 2050-7003. https://doi.org/10.1108/JARHE-09-2022-0302
Balkaya, S., & Akkucuk, U. (2021). Adoption and use of learning management systems in education: the role of playfulness and self-management. Sustainability, 13(3), 1127. https://doi.org/10.3390/su13031127
Bandura, A. (1997). Self-efficacy: The Exercise of Control (1st ed.). W. H. Freeman and Company.
Batucan, G. B., Gonzales, G. G., Balbuena, M. G., Pasaol, K. R. B., Seno, D. N., & Gonzales, R. R. (2022). An Extended UTAUT Model to Explain Factors Affecting Online Learning System Amidst COVID-19 Pandemic: The Case of a Developing Economy. Frontier in Artificial Intelligence, 5, 768-831. https://doi.org/10.3389/frai.2022.768831
Bervell, B., Umar, I. N., Kumar, J. A., Asante Somuah, B., & Arkorful, V. (2021). Blended Learning Acceptance Scale (BLAS) in Distance Higher Education: Toward an Initial Development and Validation. SAGE Open, 11(3), 215824402110400. https://doi.org/10.1177/21582440211040073
Bessadok, A., & Hersi, M. (2023). A structural equation model analysis of English for specific purposes students' attitudes regarding computer-assisted language learning: UTAUT2 model. Library Hi Tech, 0737-8831. https://doi.org/10.1108/LHT-03-2023-0124
Bornschlegl, M., Townshend, K., & Caltabiano, N. J. (2021). Application of the Theory of Planned Behavior to Identify Variables Related to Academic Help Seeking in Higher Education. Frontier in Education, 6, 738-790. https://doi.org/10.3389/feduc.2021.738790
Chao, C. M., & Yu, T. K. (2019). The moderating effect of technology optimism: How it affects students’ weblog learning. Online Information Review, 43(1), 161-180. https://doi.org/10.1108/OIR-11-2016-0316
Chen, X., Khaskheli, A., Raza, S. A., Hakim, F., & Khan, K. A. (2022). Factors affecting readiness to diffuse blended learning in Pakistani higher education institutions. International Journal of Educational Management, 36(6), 1080-1095. https://doi.org/10.1108/IJEM-10-2021-0406
Creswell, J. W. (2012). Educational research (1st ed.). Pearson.
Cui, Y. (2021). Self-efficacy for self-regulated learning and Chinese students’ intention to use online learning in COVID-19: a moderated mediation model. International Journal of Information and Education Technology, 11(11), 532-537. https://doi.org/10.18178/ijiet.2021.11.11.1561
Dakduk, S., Santalla-Banderali, Z., & van der Woude, D. (2018). Acceptance of Blended Learning in Executive Education. SAGE Open, 8(3), 215824401880064. https://doi.org/10.1177/2158244018800647
Dubey, P., & Sahu, K. K. (2022). Investigating various factors that affect students' adoption intention to technology-enhanced learning. Journal of Research in Innovative Teaching & Learning, 15(1), 110-131. https://doi.org/10.1108/JRIT-07-2021-0049
Fisher, R., Perényi, Á., & Birdthistle, N. (2021). The positive relationship between flipped and blended learning and student engagement, performance, and satisfaction. Active Learning in Higher Education, 22(2), 97-113.
https://doi.org/10.1177/1469787418801702
Fleischmann, K. (2021). Hands-on versus virtual: Reshaping the design classroom with blended learning. Arts and Humanities in Higher Education, 20(1), 87-112. https://doi.org/10.1177/1474022220906393
Fulcher, G. (2013). Practical Language Testing (1st ed.). Taylor & Francis.
Gunasinghe, A., Abd Hamid, J., Khatibi, A., & Azam, S. F. (2020). The adequacy of UTAUT-3 in interpreting academician’s adoption to E-learning in higher education environments. Interactive Technology and Smart Education, 17(1), 86-106. https://doi.org/10.1108/itse-05-2019-0020
Gupta, S., Mathur, N., & Narang, D. (2022). E-leadership and virtual communication adoption by educators: an UTAUT3 model perspective. Global Knowledge, Memory and Communication, 3(2), 30-78. https://doi.org/10.1108/GKMC-01-2022-0001
Hamid, S., Ali, R., Phd, S., Jameel, S., Azhar, M., & Siddiqui, S. (2023). Understanding Behavioural Intention of Experiencing Virtual Tourism During Covid-19: An Extension Of Theory Of Planned Behaviour. Tourism and hospitality management, 3(29), 423-437. https://doi.org/10.20867/thm.29.3.10
Ilyas, A., & Zaman, M. K. (2020). An evaluation of online students’ persistence intentions. Asian Association of Open Universities Journal, 15(2), 207-222. https://doi.org/10.1108/AAOUJ-11-2019-0053
Islam, M. K., Sarker, M. F. H., & Islam, M. S. (2022). Promoting student-centred blended learning in higher education: A model. E-Learning and Digital Media, 19(1), 36-54. https://doi.org/10.1177/20427530211027721
Mielikäinen, M., Viippola, E., & Tepsa, T. (2023). Experiences of a project-based blended learning approach in a community of inquiry from information and communication technology engineering students at Lapland university of applied sciences in Finland. E-Learning and Digital Media, 2(3), 204275302311640. https://doi.org/10.1177/20427530231164053
Minhas, W., White, T., Daleure, G., Solovieva, N., & Hanfy, H. (2021). Establishing an Effective Blended Learning Model: Teacher Perceptions from the United Arab Emirates. SAGE Open, 11(4), 215824402110615. https://doi.org/10.1177/21582440211061538
Ministry of Education. (2021, May 16). Ten-year development plan for education informatization (2011-2020) [EB/OL]. http://www.gov.cn/ gzdt/2012-03/31/content_2104056.htm
Ohanu, I. B., Shodipe, T. O., Ohanu, C. M.-G., & Anene-Okeakwa, J. E. (2022). Quality blended learning systems for improving undergraduate students’ skills. Quality Assurance in Education, 30(2), 169-183.
Onofrei, G., & Ferry, P. (2020). Reusable learning objects: a blended learning tool in teaching computer-aided design to engineering undergraduates. International Journal of Educational Management, 34(10), 1559-1575. https://doi.org/10.1108/IJEM-12-2019-0418
Palys, T. (2008). Purposive sampling. The Sage Encyclopedia of Qualitative Research Methods, 2(1), 697-698.
Pardamean, B., & Susanto, M. (2012). Assessing user acceptance toward blog technology using the UTAUT model. International Journal of Mathematics and Computer in Simulation, 6, 203-212.
Pham, L. T., & Dau, T. K. T. (2022). Online learning readiness and online learning system success in Vietnamese higher education. International Journal of Information and Learning Technology, 39(2), 147-165. https://doi.org/10.1108/IJILT-03-2021-0044
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
Reyes-Mercado, P., Barajas-Portas, K., Kasuma, J., Almonacid-Duran, M., & Zamacona-Aboumrad, G. A. (2023). Adoption of digital learning environments during the COVID-19 pandemic: merging technology readiness index and UTAUT model. Journal of International Education in Business, 16(1), 91-114. https://doi.org/10.1108/JIEB-10-2021-0097
Rogers, E. (1995). Diffusion of Innovations (1st ed.). Free Press.
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
Samsudeen, S. N., & Mohamed, R. (2019). University students’ intention to use e-learning systems: A study of higher educational institutions in Sri Lanka. Interactive Technology and Smart Education, 16(3), 219-238. https://doi.org/10.1108/ITSE-11-2018-0092
Sharma, L., & Srivastava, M. (2020). Teachers’ motivation to adopt technology in higher education. Journal of Applied Research in Higher Education, 12(4), 673-692. https://doi.org/10.1108/JARHE-07-2018-0156
Singh, J., Steele, K., & Singh, L. (2021). Combining the Best of Online and Face-to-Face Learning: Hybrid and Blended Learning Approach for COVID-19, Post Vaccine, & Post-Pandemic World. Journal of Educational Technology Systems, 50(2), 140-171. https://doi.org/10.1177/00472395211047865
Sitar-Taut, D.-A., & Mican, D. (2021). Mobile learning acceptance and use in higher education during social distancing circumstances: an expansion and customization of UTAUT2. Online Information Review, 45(5), 1000-1019. https://doi.org/10.1108/OIR-01-2021-0017
Taamneh, A., Alsaad, A., Elrehail, H., Al-Okaily, M., Lutfi, A., & Sergio, R. P. (2023). University lecturers’ acceptance of moodle platform in the context of the COVID-19 pandemic. Global Knowledge, Memory and Communication, 72(6/7), 666-684. https://doi.org/10.1108/GKMC-05-2021-0087
Tewari, A., Singh, R., Mathur, S., & Pande, S. (2023). A modified UTAUT framework to predict students' intention to adopt online learning: moderating role of openness to change. International Journal of Information and Learning Technology, 40(2), 130-147. https://doi.org/10.1108/IJILT-04-2022-0093
Twum, K. K., Ofori, D., Keney, G., & Korang-Yeboah, B. (2022). Using the UTAUT, personal innovativeness and perceived financial cost to examine student’s intention to use E-learning. Journal of Science and Technology Policy Management, 13(3), 713-737. https://doi.org/10.1108/JSTPM-12-2020-0168
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478.
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.
Waite, A., & White, B. (2019). Collaborative learning approaches in higher education. Journal of Educational Research, 112(4), 345-360.
Wang, J. (2019). Application of blending learning based on network learning space in teaching design of digital art. International Journal of Educational Technology, 14(9), 177-189. https://doi.org/10.3991/ijet.v14i03.10107
Wang, K., van Hemmen, S. F., & Criado, J. R. (2022). The behavioural intention to use MOOCs by undergraduate students: incorporating TAM with TPB. International Journal of Educational Management, 36(7), 1321-1342. https://doi.org/10.1108/IJEM-11-2021-0446
Wei, Y. T., Shi, Y. H., Yang, H. H., & Liu, J. Q. (2017). Blended learning versus traditional learning: A study on students’ learning achievements and academic press. In F. L. Wang, O. Au, K. K. Ng, J. J. Shang, & R. Kwan (Eds.), Proceedings of 2017 International Symposium on Educational Technology [Symposium] (pp. 219-223). IEEE Computer Society. https://doi.org/10.1109/ISET.2017.57
Wut, T. M., & Lee, S. W. (2022). Factors affecting students’ online behavioral intention in using discussion forum. Interactive Technology and Smart Education, 19(3), 300-318. https://doi.org/10.1108/ITSE-02-2021-0034
Yashwant, A. V., Arayambath, B., Murugaboopathy, V., Kommi, P. B., Prashad, K. V., & Rajasekaran, U. B. (2020). Comparative Evaluation of the Effectiveness of Blended Learning Versus Traditional Learning in Cephalometrics for Undergraduates. Journal of Indian Orthodontic Society, 54(1), 24-30. https://doi.org/10.1177/0301574219883873
Ye, L., Kuang, M., & Liu, S. (2022). ICT Self-Efficacy, Organizational Support, Attitudes, and the Use of Blended Learning: An Exploratory Study Based on English Teachers in Basic Education. Frontier in Psychology, 13(94), 15-35. https://doi.org/10.3389/fpsyg.2022.941535
Zhang, X., King, A., & Prior, H. (2021). Exploring the Factors Influencing Chinese Music Teachers’ Perceptions and Behavioural Intentions in Using Technology in Higher Education: A Pilot Study. Music & Science, 4(2), 40-67. https://doi.org/10.1177/20592043211044819