Examining on Behavioral Intention and Use Behavior of Students Online Learning Systems: A Case of Vocational Collages in Jiangxi, China
DOI:
https://doi.org/10.14456/shserj.2024.59Keywords:
Online Learning, Social Influence, Behavioral Intentions, Use Behavior, Higher EducationAbstract
Purpose: This research paper aims to examine the factors impacting vocational collages’ students’ behavioral intention and use behavior of the online learning system in Jiangxi, China. The conceptual framework proposed a causal relationship among perceived usefulness, perceived ease of use, attitude, perceived behavioral control, social influence, behavioral intentions, and use behavior. Research design, data, and methodology: The researcher used the quantitative method (n=500) to distribute questionnaires to students. The nonprobability sampling includes judgmental, quota sampling, and convenience sampling in collecting data and distributing surveys by the online survey platform. The Structural Equation Model (SEM) and Confirmatory Factor Analysis (CFA) were used for the data analysis, including model fit, reliability, and validity of the constructs. Results: The results explicated that perceived usefulness, perceived ease of use, attitude, and perceived behavioral control have a significant impact on behavioral intentions. In addition, behavioral intentions significantly impact use behavior. Nevertheless, social influence has no significant impact on behavioral intentions. Conclusions: Six hypotheses were proven to fulfill research objectives. Hence, it is recommended that teaching management departments and educational technology centers provide assessments to measure the level of influence and teaching development plans to enhance the overall level of teaching information in the school.
References
Aaker, J. L., & Maheswaran, D. (1997). The effect of cultural orientation on persuasion. Journal of Consumer Research, 24(3), 315-328. https://doi.org/10.1086/209513
Agarwal, R., & Prasad, J. (1999). Are Individual Differences Germane to the Acceptance of New Information Technologies? Decision Sciences, 30, 361-391. http://dx.doi.org/10.1111/j.1540-5915.1999.tb01614.x
Agyei, D. D., & Voogt, J. M. (2011). Exploring the potential of the will, skill, tool model in Ghana: Predicting prospective and practicing teachers' use of technology. Computer & Education, 56(1), 91-100. https://doi.org/10.1016/j.compedu.2010.08.017
Ajzen, I. (1988). Attitudes, Personality, and Behavior (1st ed.). Dorsey.
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. (2002). Perceived Behavioral Control, Self-Efficacy, Locus of Control, and the Theory of Planned Behavior. Journal of Applied Social Psychology, 32, 665-683. http://dx.doi.org/10.1111/j.1559-1816.2002.tb00236.x
Ajzen, I. (2012). The Theory of Planned Behaviour, In P. A. M. Lange, A. W. Kruglanski & E. T. Higgins (Eds.), Handbook of Theories of Social Psychology (pp. 438-459). Sage. https://doi.org/10.4135/9781446249215.n22
Akturan, U., & Tezcan, N. (2012). Mobile Banking Adoption of the Youth Market: Perceptions and Intentions. Marketing Intelligence & Planning, 30, 444-459. https://doi.org/10.1108/02634501211231928
Alexandersson, M., & Limberg, L. (2012). Changing Conditions for Information Use and Learning in Swedish Schools: A Synthesis of Research. HumanIT, 11(2), 131-154.
Ali, S., Ahmad Ganai, B., Kamili, A. N., & Ali Bhat, A. (2018). Pathogenesis-related proteins and peptides as promising tools for engineering plants with multiple stress tolerance. Microbiological Research, 212, 29-37.
https://doi.org/10.1016/j.micres.2018.04.008
Alkhadim, M., Gidado, K., & Painting, N. (2018). Perceived Crowd Safety in Large Space Buildings: The Confirmatory Factor Analysis of Perceived Risk Variables. Journal of Engineering, Project, and Production Management, 8(1), 22-39. https://doi.org/10.32738/jeppm.201801.0004
Allen, R. C. (2009). The British Industrial Revolution in Global Perspective (1st ed.). Cambridge University Press.
Al-Mamary, Y. H., & Shamsuddin, A. (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.
Al-Omairi, T., & Al Balushi, H. (2015). The Influence of paying attention in classroom on students’ academic achievement in terms of their comprehension and recall ability. Proceedings of INTCESS15- 2nd International Conference on Education and Social Sciences, 684-693.
Amin, M. H. A., Rahaman, M. S., & Azad, M. O. K. (2008). Effect of initial moisture content and different storage container on the quality of grass pea (Lathyrus sativa) seed. Int. J. Sust. Crop Prod., 3(3), 18-24.
Anckar, B., Walden, P., & Jelassi, T. (2002). Creating customer value in online grocery shopping. International Journal of Retail & Distribution Management, 30(4), 211-220.
Armitage, C. J., & Conner, M. (2001). Efficacy of the Theory of Planned Behaviour: A Meta Analytic Review. British Journal of Social Psychology, 40(4), 471-499. https://doi.org/10.1348/014466601164939
Arpaci, I. (2016). Understanding and predicting students' intention to use mobile cloud storage services. Computers in Human Behavior. 58, 150-157. https://doi.org/10.1016/j.chb.2015.12.067
Awang, Z. (2012). A Handbook on SEM Structural Equation Modelling: SEM Using AMOS Graphic (5th ed.). Universiti Teknologi Mara Kelantan.
Behrend, T., Sharek, D., Meade, A., & Wiebe, E. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods, 43(3), 800-813.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246.
https://doi.org/10.1037/0033-2909.107.2.238
Bidin, S. J., & Jomaa, N. (2019). Variations in the Citation Use and Perceptions in Writing the Literature Review by EFL Postgraduates. Eurasian Journal of Applied Linguistics, 5(3), 441-460. https://doi.org/10.32601/ejal.651398
Bolduc, H., & Kinnally, W. (2018). Examining the Impact of Social Identification with Music-on-Music Streaming Behavior. Journal of Radio & Audio Media, 25(1), 42-61. https://doi.org/10.1080/19376529.2017.1362893
Brown, T. A. (2006). Confirmatory Factor Analysis for Applied Research (1st ed.). The Guilford Press.
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.
https://doi.org/10.1108/JRIT/03-2017-000
Clark, V. L. P., & Ivankova, N. V. (2016). Mixed Methods Research: A Guide to the Field (1st ed.). SAGE Publications.
Commer, P., Sci, S., Sair, S. A., & Danish, R. (2018). Effect of Performance Expectancy and Effort Expectancy on the Mobile Commerce Adoption Intention through Personal Innovativeness among Pakistani Consumers. Pakistan Journal of Commerce and Social Science, 12, 501-520.
Crabbe, M., Standing, C., Standing, S., & Karjaluoto, H. (2009). An adoption model for mobile banking in Ghana. IJMC, 7(5), 515-543. https://doi.org/10.1504/ijmc.2009.024391
Davis, F. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340. https://doi.org/10.2307/249008
Fan, X., Duangekanong, S., & Xu, M. (2021). Factors Affecting College Students’ Intention to Use English U-learning in Sichuan, China. AU-GSB E-JOURNAL, 14(2), 118-129. https://doi.org/10.14456/augsbejr.2021.20
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research (1st ed.). Addison-Wesley.
Gerhardt, T., & Mackenzie, L. (2018). The Challenges and Opportunities of ICT in WIL: A case study among priests exploring the correlation and trajectory between effective WIL and ICT Pervasiveness. Journal of Higher Education, 8(4), 408-421. https://doi.org/10.1108/heswbl-07-2017-0045
Guo, F., Yu, J., Jung, H. J., Abruzzi, K. C., Luo, W., Griffith, L. C., & Rosbash, M. (2016). Circadian neuron feedback controls the Drosophila sleep--activity profile. Nature 536(7616), 292-297. https://doi.org/10.1038/nature19097
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). Pearson.
Ho, Y.-S. (2012). The top-cited research works in the Science Citation Index Expanded. Scientometrics, 94, 1297-1312.
https://doi.org/10.1007/s11192-012-0837-z
Huang, Y.-H. (2016). Beyond Safety Outcomes: An Investigation of the Impact of Safety Climate on Job Satisfaction, Employee Engagement and Turnover Using Social Exchange Theory as the Theoretical Framework. Applied Ergonomics, 55, 248-257. https://doi.org/10.1016/j.apergo.2015.10.007
John, H. (2013). Men in Black (1st ed.). Reaktion Books
Khalifa, M., & Shen, K. (2008). Explaining the adoption of transactional B2C mobile commerce. J. Enterprise Inf. Management, 1(2), 110-124.
Kim, H.-W., & Kwahk, K.-Y. (2007). Comparing the Usage Behavior and the Continuance Intention of Mobile Internet Services. Management of eBusiness, 2007. WCMeB 2007. Eighth World, 1-15. https://doi.org/10.1109/wcmeb.2007.98
Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling (1st ed.). Guilford Press.
Lin, H.-F. (2007). Knowledge Sharing and Firm Innovation Capability: An Empirical Study. International Journal of Manpower, 28, 315-332. https://doi.org/10.1108/0143772071075527
Linnenbrink, E. A. (2007). The role of affect in student learning: A multi-dimensional approach to considering the interaction of affect, motivation, and engagement. In P. A. Schutz & R. Pekrun (Eds.), Emotion in education (pp. 107-124). Elsevier Academic Press. https://doi.org/10.1016/B978-012372545-5/50008-3
Littlejohn, A., Hood, N., Milligan, C., & Mustain, P. (2015). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. The Internet and Higher Education, 29(4), 40-48. https://doi.org/10.1016/j.iheduc.2015.12.003
Liu, C., & Forsythe, S. (2010). Sustaining Online Shopping: Moderating Role of Online Shopping Motives. Journal of Internet Commerce, 9(2), 83-103. https://doi.org/10.1080/15332861.2010.503848
Liu, W., Mumford, E., & Taylor, B. (2018). The Relationship Between Parents’ Intimate Partner Victimization and Youths’ Adolescent Relationship Abuse. Journal of Youth and Adolescence, 47(2), 321-333. https://doi.org/10.1007/s10964-017-0733-1
Liyanagunawardena, T., Williams, S., & Adams, A. (2013). The impact and reach of MOOCs: a developing countries’ perspective. eLearning Papers, 1(33), 1-8.
Lu, J. (2014). Are Personal Innovativeness and Social Influence Critical to Continue with Mobile Commerce? Internet Research, 24(2), 134-159. https://doi.org/10.1108/intr-05-2012-0100
Madhurima, D., & Ewuuk, L.-D. (2014). An empirical examination of customers' adoption of m-banking in India. Marketing Intelligence & Planning, 32(4), 475-494.
Maio, G., Haddock, G., & Verplanken, B. (2019). The psychology of attitudes & attitude change (1st ed.). Sage Publications.
Mallat, N., Rossi, M., Tuunainen, V., & Öörni, A. (2009). The Impact of use Context on Mobile Services Acceptance: The Case of Mobile Ticketing. Information & Management, 46(3), 190-195. https://doi.org/10.1016/j.im.2008.11.008
Mathwick, C., Malhotra, N., & Rigdon, E. (2001). Experiential Value: Conceptualization, Measurement and Application in the Catalog and Internet Shopping Environment. Journal of Retailing, 77, 39-56.
https://doi.org/10.1016/S0022-4359(00)00045-2
Mohammadi, H. (2015). A Study of Mobile Banking Usage in Iran. International Journal of Bank Marketing, 33, 733-759.
https://doi.org/10.1108/IJBM-08-2014-0114
Moorthy, M., Ling, C., Fatt, Y., Yee, C., Yin, E., Yee, K., & Wei, L. (2017). Barriers of Mobile Commerce Adoption Intention: Perceptions of Generation X in Malaysia. Journal of theoretical and applied electronic commerce research, 12(2), 37-53. https://doi.org/10.4067/s0718-18762017000200004
Nassoura, A. B. (2012). Students’ acceptance of mobile learning for higher education in Saudi Arabia. American Academic & Scholarly Research Journal, 4(2), 1-10.
Nysveen, H., Pedersen, P., & Thorbjørnsen, H. (2005). Intentions to Use Model Services: Antecedents and Cross-Service Comparisons. Journal of the Academy of Marketing Science, 33(3), 330-346. https://doi.org/10.1177/0092070305276149
Oertzen, A.-S., & Schröder, G.-O. (2019). Achieving continued usage in online banking: A post-adoption study. International Journal of Bank Marketing, 37(6), 1394-1418. https://doi.org/10.1108/ijbm-09-2018-0239
Oliveira, H. C., Garcia, R., Almeida, V. V. S., Oliveira, A. C., Pires, A. J. V., Nascimento, C. S., Veloso, C. M., Silva, R. R., & Oliveira, U. L. C. (2016). Feeding behavior of lambs fed castor meal. Semin. Cienc. Agrar., 37(3), 1451-1460. https://doi.org/10.5433/1679-0359.2016v37n3p1451
Park, Y. K., Song, J. H., Yoon, S. W., & Kim, J. (2014). Learning Organization and Innovative Behavior: The Mediating Effect of Work Engagement. European Journal of Training and Development, 38, 75-94. https://doi.org/10.1108/EJTD-04-2013-0040
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
Perkowitz, M., & Etzioni, O. (1999). Towards adaptive Web sites: Conceptual framework and case study. Artificial Intelligence 118(1-2), 245-275.
Perry, A., Orly, R., Peled-Avron, L., & Shamay-Tsoory, S. (2013). Don't stand so close to me: A behavioral and ERP study of preferred interpersonal distance. NeuroImage, 83(1), 761-769. https://doi.org/10.1016/j.neuroimage.2013.07.042
Pipitwanichakarn, T., & Wongtada, N. (2020). The role online review on mobile commerce adoption: an inclusive growth context. Journal of Asia Business Studies, 14(5), 759-778. https://doi.org/10.1108/jabs-02-2019-0060
Prieto, I., & Pérez-Santana, M. (2014). Managing innovative work behavior: The role of human resource practices. Personnel Review, 43(2), 1-10.
Rhema, A., & Miliszewska, I. (2014). Analysis of Student Attitudes towards E-learning: The Case of Engineering Students in Libya. Issues in Informing Science and Information Technology, 11, 169-190. https://doi.org/10.28945/1987
Riquelme, H. E., & Rios, R. E. (2010). The Moderating Effect of Gender in the Adoption of Mobile Banking. The International Journal of Bank Marketing, 28, 328-341. http://dx.doi.org/10.1108/02652321011064872
Rogers, E. M. (1962). Diffusion of Innovations (1st ed.). Free Press.
Samuel, A., Susan, M., & Biniecki, Y. (2017). Using concept mapping as a tool for conducting research: An analysis of three approaches. Cogent Social Sciences, 3(1), 1404753. https://doi.org/10.1080/23311886.2017.1404753
Sarmento, R., & Costa, V. (2016). Comparative Approaches to Using R and Python for Statistical Data Analysis (1st ed.). IGI Global Press.
Sharma, S., Pradhan, K., Satya, S., & Vasudevan, P. (2005). Potentiality of earthworms for waste management and in other uses- a review. The J. Am. Sci., 1(1), 4-16
Shiau, W. L., & Chau, P. Y. (2016). Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach. Information & Management, 53, 355-365. https://doi.org/10.1016/j.im.2015.10.004
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.
Stark, J. S., & Lattuca, L. R. (1997). Shaping the College Curriculum: Academic Plans in Action (1st ed.). Evaluative.
Tarhini, A., Masa'deh, R., Al-Busaidi, K. A., Bany Mohammed, A., & 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
Taylor, D. G., & Strutton, D. (2010). Has e-marketing come of age? Modeling historical influences on post-adoption era Internet consumer behaviors. Journal of Business Research, 63(9-10), 950-956. https://doi.org/10.1016/j.jbusres.2009.01.018
Tenorio, M. L., Dekker, M., & Verkerk, R. (2017). Evaluating the effect of storage conditions on the shelf life of cape gooseberry. LWT, 80, 523-530. https://doi.org/10.1016/j.lwt.2017.03.027
Thakur, R., & Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk, and usage intention across customer groups for mobile payment services in India. Internet Research: Electronic Networking Applications and Policy, 24(3), 369-392. https://doi.org/10.1108/intr-12-2012-0244
Van Manen, M. (1997). Researching Lived Experience: Human Science for an Action Sensitive Pedagogy (2nd ed.). Althouse Press.
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46, 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., & Morris, M. G. (2000). Why Don’t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior. MIS Quarterly, 24, 115-139. https://doi.org/10.2307/3250981
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Towards a Unified View. MIS Quarterly, 27, 425-478.
Wang, Z., Guo, D., & Wang, X. (2016). Determinants of Residents’ E-Waste Recycling Behaviour Intentions: Evidence from China. Journal of Cleaner Production, 137, 850-860. https://doi.org/10.1016/j.jclepro.2016.07.155
Wu, J. H., & Wang, Y. M. (2006). Measuring KMS Success: A Respecification of the DeLone and McLean’s Model. Journal of Information & Management, 43(6), 728-739. http://dx.doi.org/10.1016/j.im.2006.05.002
Zeithaml, V. A., Parasuraman, A., & Malhotra, A. (2002). Service Quality Delivery through Web Sites: A Critical Review of Extant Knowledge. Journal of the Academy of Marketing Science, 30, 362-375. https://doi.org/10.1177/009207002236911
Zhou, T. (2011). Understanding mobile internet continuance usage from the perspectives of UTAUT and flow. Information Development, 27(3), 207-218. https://doi.org/10.1177/0266666911414596
Downloads
Published
How to Cite
Issue
Section
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.
