Nursing students’ behavioral intention to use online courses: A questionnaire survey
Abstract
Background The development of network communication science and technology has accorded a special benefit to learning. Online courses have also become the most popular and important learning resource among students.Objectives Overall, this research aims to explore what are the important factors making students use online courses.Design The research combines the technology acceptance model and the innovation diffusion theory, and adds four research variables, computer anxiety, computer self-efficacy, perceived financial cost and perceived information quality to propose a new hybrid technology acceptance model to study students' behavioral intention to use online courses.Settings Based on 228 questionnaires collected from nursing students in Taiwan.Methods The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to examine the reliability and validity of the measurement model.Participants The survey began with e-mail and telephone interviews in January 2006. The interviewees were 348 students of Taiwan's universities. Because some of the replying subjects have never taken those courses and some did not complete the questionnaires, there were 228 valid questionnaires from students of Taiwan's universities who have taken online courses. The responding rate was 65.52%.Results This research found that computer anxiety had a negative effect on the behavioral intention to use online courses (gamma=-0.21, P<0.01). Computer self-efficacy had a positive effect on the behavioral intention to use online courses (gamma=0.37, P<0.01). Compatibility had a positive effect on both the behavioral intention to use online courses (gamma=0.18, P<0.01) and perceived usefulness (gamma=0.3, P<0.01). Perceived usefulness had a positive effect on the behavioral intention to use online courses (beta=0.14, P<0.05). Perceived ease of use had a positive effect on perceived usefulness (gamma=0.23, P<0.01), the behavioral intention to use online courses (gamma=0.24, P<0.01). Perceived financial cost had a negative effect on the behavioral intention to use online courses (gamma=-0.16, P<0.01). Perceived information quality had a positive effect on the behavioral intention to use online courses (gamma=0.11, P<0.05). The findings of this research help to develop more user friendly online courses for students.Conclusions (1) Computer anxiety, computer self-efficacy, compatibility, perceived usefulness, perceived ease of use, perceived financial cost, and perceived information quality were the critical factors that impacted on students' behavioral intention to use online courses. (2) Computer anxiety and perceived financial cost had a negative effect on the behavioral intention to use online courses. (3) The present study added four new research constructs (computer anxiety, computer self-efficacy, perceived financial cost, and perceived information quality) to the research model so that it would be more complete; this improved the fit of the whole model. (4) Computer self-efficacy, compatibility, perceived usefulness, perceived ease of use, and perceived information quality had a positive effect on the behavioral intention to use online courses. By explaining students' behavioral intention from a user's perspective, the findings of this research help to provide insight into the best way to promote new e-learning tools for students.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314 · see citing works
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163 · see citing works
(1980) · Medical Entomology and Zoology · Cited by 25,810 · see citing works
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709 · see citing works
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066 · see citing works
EQS : structural equations program manual
Bentler, P. M. (1989) · Medical Entomology and Zoology · Cited by 9,669 · see citing works
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150 · see citing works
Understanding information technology usage: a test of competing models
Taylor, S., & Todd, P. A. (1995) · Information Systems Research · doi:10.1287/isre.6.2.144 · Cited by 8,815 · see citing works
Computer Self-Efficacy: Development of a Measure and Initial Test
Compeau, D. R., & Higgins, C. A. (1995) · MIS Quarterly · doi:10.2307/249688 · Cited by 6,553 · see citing works
A Model of the Antecedents of Perceived Ease of Use: Development and Test
Venkatesh, V., & Davis, F. D. (1996) · Decision Sciences · doi:10.1111/j.1540-5915.1996.tb00860.x · Cited by 3,854 · see citing works
A Model of the Antecedents of Perceived Ease of Use: Development and Test
Venkatesh, V., & Davis, F. D. (1996) · Decision Sciences · doi:10.1111/j.1540-5915.1996.tb01822.x · Cited by 3,802 · see citing works
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999) · MIS Quarterly · doi:10.2307/249751 · Cited by 3,709 · see citing works
Agarwal, R., & Prasad, J. (1998) · Information Systems Research · doi:10.1287/isre.9.2.204 · Cited by 3,575 · see citing works
Kaplan, B., DeGross, J. I., Wood-Harper, A. T., Wastell, D. G., & Truex, D. P., III (2004) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/b115738 · Cited by 3,136 · see citing works
Wu, J.-H., & Wang, S.-C. (2005) · Information & Management · doi:10.1016/j.im.2004.07.001 · Cited by 2,284 · see citing works
Toward an understanding of the behavioral intention to use mobile banking
Luarn, P., & Lin, H. (2004) · Computers in Human Behavior · doi:10.1016/j.chb.2004.03.003 · Cited by 1,997 · see citing works
Exploring the factors associated with Web site success in the context of electronic commerce
Liu, C., & Arnett, K. P. (2000) · Information & Management · doi:10.1016/s0378-7206(00)00049-5 · Cited by 1,526 · see citing works
Enticing online consumers: an extended technology acceptance perspective
Chen, L., Gillenson, M. L., & Sherrell, D. L. (2002) · Information & Management · doi:10.1016/s0378-7206(01)00127-6 · Cited by 1,380 · see citing works
Vijayasarathy, L. R. (2004) · Information & Management · doi:10.1016/j.im.2003.08.011 · Cited by 1,218 · see citing works
Shopping online for freedom, control, and fun.
Wolfinbarger, M., & Gilly, M. C. (2001) · California Management Review · doi:10.2307/41166074 · Cited by 1,150 · see citing works
Extending the technology acceptance model: the influence of perceived user resources
Mathieson, K., Peacock, E., & Chin, W. W. (2001) · ACM SIGMIS Database: the DATABASE for Advances in Information Systems · doi:10.1145/506724.506730 · Cited by 1,099 · see citing works
Computer anxiety and its correlates: a meta-analysis
Chua, S. L., Chen, D.-T., & Wong, A. F. L. (1999) · Computers in Human Behavior · doi:10.1016/s0747-5632(99)00039-4 · Cited by 477 · see citing works
Gefen, D. (2004) · Journal of Management Information Systems · doi:10.1080/07421222.2004.11045792 · Cited by 363 · see citing works
Web-based teaching and learner control: a research review
Lin, B., & Hsieh, C. (2001) · Computers & Education · doi:10.1016/s0360-1315(01)00060-4 · Cited by 283 · see citing works
Gender, Internet Identification, and Internet Anxiety: Correlates of Internet Use
Joiner, R., Gavin, J., Duffield, J., Brosnan, M., Crook, C. K., Durndell, A., Maras, P., Miller, J. E., Scott, A. J., & Lovatt, P. J. (2005) · CyberPsychology & Behavior · doi:10.1089/cpb.2005.8.371 · Cited by 183 · see citing works
Marakas, G. M., Johnson, R. D., & Palmer, J. W. (2000) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1999.0348 · Cited by 143 · see citing works
Strategies of Effective New Product Team Leaders
Jassawalla, A. R., & Sashittal, H. C. (2000) · California Management Review · doi:10.2307/41166031 · Cited by 108 · see citing works
The effects of Internet-based distance learning in nursing.
Soon, K. H., Sook, K. I., Jung, C. W., et al. (2000) · PubMed · Cited by 71 · see citing works
Measuring users' perceived portal service quality: An empirical study
Kuo, T., Lu, I., Huang, C.-H., et al. (2005) · Total Quality Management & Business Excellence · doi:10.1080/14783360500053824 · Cited by 66 · see citing works
Halter, M. J., Kleiner, C. R., & Hess, R. F. (2005) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2005.03.001 · Cited by 52 · see citing works
Distance Education for Graduate Nursing: One State School's Experience
Ostrow, L., & DiMaria-Ghalili, R. A. (2005) · Journal of Nursing Education · doi:10.3928/01484834-20050101-02 · Cited by 29 · see citing works
Bentley, G. W., Cook, P., Davis, K., et al. (2003) · Nurse Educator · doi:10.1097/00006223-200305000-00005 · Cited by 25 · see citing works
Assessing the Effectiveness of an Online Program
Rosenlund, C. H., & Damask-Bembenek, B. (1999) · Nurse Educator · doi:10.1097/00006223-199901000-00001 · Cited by 14 · see citing works
Use of and satisfaction with a browser-based nurse teaching tool in a surgical intensive care unit.
Sery-Ble, O. R., Taffe, E. R., Clarke, A. W., et al. (2001) · PubMed · Cited by 13 · see citing works
Herrin, D. M. (2001) · JONA The Journal of Nursing Administration · doi:10.1097/00005110-200101000-00002 · Cited by 11 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The Technology Acceptance Model: Its past and its future in health care
Holden, R. J., & Karsh, B.-T. (2010) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.07.002 · Cited by 2,669 · see citing works
Hoque, R., & Sorwar, G. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.02.002 · Cited by 1,004 · see citing works
User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model
Lee, D. Y., & Lehto, M. R. (2013) · Computers & Education · doi:10.1016/j.compedu.2012.10.001 · Cited by 565 · see citing works
Elderly persons’ perception and acceptance of using wireless sensor networks to assist healthcare
Steele, R., Lo, A., Secombe, C., & Wong, Y. K. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2009.08.001 · Cited by 508 · see citing works
Technological literacy in nursing education: A scoping review
Nes, A. A. G., Steindal, S. A., Larsen, M. H., Heer, H. C., Lærum-Onsager, E., & Gjevjon, E. R. (2021) · Journal of Professional Nursing · doi:10.1016/j.profnurs.2021.01.008 · Cited by 182 · see citing works
- Authors
- Tung, F.-C., & Chang, S.-C.
- Affiliations
- Taiwan Shoufu University (TW)
- National Cheng Kung University (TW)
- Corresponding author
- Tung, Feng-Cheng
- ORCID
- Tung, Feng-Cheng
- Venue
- International Journal of Nursing Studies
- Publisher
- Elsevier BV
- Published
- 2008-09
- Volume
- 45
- Issue
- 9
- Pages
- 1299-1309
- ISSN
- 0020-7489 (ISSN-L)
- OpenAlex
- W2081816477
- Cited by
- 109
- References
- 35
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 4 · 2023: 11 · 2022: 4 · 2021: 8 · 2020: 9 · 2019: 6 · 2018: 4 · 2017: 5 · 2016: 8 · 2015: 5 · 2014: 7 · 2013: 10 · 2012: 5
- FWCI
- 6.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Nursing Studies (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Online and Blended Learning
- Social Sciences › Education › Technology-Enhanced Education Studies
- Keywords
- online courses, behavioral intention, nursing students, technology acceptance model, diffusion of innovation theory, computer anxiety, computer self-efficacy, perceived financial cost, perceived information quality, perceived usefulness, perceived ease of use, compatibility, e-learning adoption, Taiwan universities, e-learning in higher education
- MeSH terms
- Humans, Models, Theoretical, Surveys and Questionnaires, Students, Nursing, Taiwan, Education, Distance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review