Abstract
The specific features of the Internet have created an ideal place for teaching and learning. There has been a lot of attention on how and why students adopt and use an Internet-based learning medium. In recent years, we witnessed a significant amount of studies on the impact of contextual factors (such as gender difference) on technology usage. These studies have shown that male and female users seem to use technology in a very different way. In view of this, we attempt to explore the gender differences in student acceptance of an Internet-based learning medium (ILM). Specifically, we examine the gender differences in the relative impact of both extrinsic and intrinsic motivations, as well as the social influence on student acceptance of an ILM. A total of 504 students participated in this study. Attitude has the strongest direct effect on behavioral intention for both male and female students. Perceived usefulness influences attitude and behavioral intention to use an ILM more strongly for male students than it influences female students, whilst subjective norm is a more important factor determining female students’ intention to use an ILM than it is for male students. We conclude the paper by discussing its theoretical and practical implications.
Keywords
- Gender Difference
- Partial Little Square
- Subjective Norm
- Female Student
- Intrinsic Motivation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Buying options
Preview
Unable to display preview. Download preview PDF.
REFERENCES
Ahuja, M. K., & Thatcher, J. B. (2005). Moving beyond intentions and toward the theory of trying: Effects of work environment and gender on post-adoption information technology use. MIS Quarterly, 29(3), 427–459.
Bagozzi, R. P., & Lee, K. H. (2002). Multiple routes for social influence: The role of compliance, internalization,and social identity. Social Psychology Quarterly, 65(3), 226–247.
Bem, S. L. (1981). Bsri and gender schema theory: A reply to Spence and Helmreich. Psychological Review, 88, 369–371.
Chau, P. Y. K. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185–204.
Cheung, C. M. K., & Lee, M. K. O. (2010). A theoretical model of intentional social action in online social networks. Decision Support Systems, 49(1), 24–30.
Chin, W. W. (1998). The partial least squares: Approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah, NJ: Lawrence Erlbaum Associates.
Chong, J. (1998). Crime indicators for alcohol and drug abuse. Criminal Justice and Behavior, 25(3), 283–305.
Davis, F. D. (1993). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–339.
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.
Davis, F. D., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22, 1111–1132.
Debrand, C. C. (2008). Gender differences in email and instant messaging: A study of undergraduate business information systems students. Journal of Computer Information Systems, 48(3), 20–30.
Deci, E. L., & Rayan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum Press.
Deci, E. L., & Rayan, R. M. (1991). A motivaiton approach to self: Integration in personality. Lincoln, NE: University of Nebraska Press.
Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Frankel, K. A. (1990). Women and computing. Communications of ACM, 33(11), 34–45.
Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of email: An extension to the Technology Acceptance Model. MIS Quarterly, 21(4), 389–400.
Hair, J. F., Black, W. C., Babin B. J., Anderson R. E., & Tatham R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson Education Inc.
Hussong, A. M., Curran, P. J., & Chassin, L. (1998). Pathways of risk for accelerated heavy alcohol use among adolescent children of alcoholic parents. Journal of Abnormal Child Psychology, 26(6), 453–466.
Igbaria, M., Schiffman, S. J., & Wieckowshi, T. J. (1994). The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology. Behaviour and Information Technology, 13(6), 349–361.
Jones, S. (2002). The Internet goes to college: How students are living in the future with today’s technology. Pew Internet & American Life Project. Washington, DC.
Kelman, H. C. (1958). Compliance, identification, and internalization: Three processes of attitude change. Journal of Conflict Resolution, 2(1), 51–60.
Lee, Y. C. (2006). An empirical investigation into factors influencing the adoption of an e-learning system. Online Information Review, 30(5), 517–541.
Lee, M. K. O., Cheung, C. M. K., & Chen, Z. H. (2005). Acceptance of internet-based learning medium: The role of extrinsic and intrinsic motivation. Information & Management, 42(8), 1095–1104.
Lightdale, J. R., & Prentice, D. A. (1994). Rethinking sex differences in aggression: Aggressive behavior in the absence of social roles. Personality and Social Psychology Bulletin, 20, 34–44.
Meyers, R. A., Brashers, D. E., Winston, L. & Grob, L. (1997). Sex differences and group argument: A theoretical framework and empirical investigation. Communication Studies, 48, 19–41.
Ngai, E. W. T., Poon, J. K. L., & Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers & Education, 48(2), 250–267.
Odell, P. M. (2000). Internet use among female and male college students. CyberPsychology & Behavior, 3(5), 855–862.
Quatman, T., & Watson, C. M. (2001). Differences in adolescent self-esteem: An exploration of domains. The Journal of Genetic Psychology, 162(1), 93–117.
Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education, 49(2), 396–413.
Shen, A. X. L., Lee, K. O. M., & Cheung, M. K. C. (2010). Gender differences in intentional social action: We-Intention to engage in social network-facilitated team collaboration. Journal of Information Technology, 25(2), 152–169.
Shi, N., Lee, K. O. M., Cheung, M. K. C., & Chen, H. P. (2010). The continuance of online social networks: How to keep people using facebook. Hawaii International Conference on System Sciences, Kauai, Hawaii, USA.
Straub, D. W., Keil, M., & Brenner, W. H. (1997). Testing the Technology Acceptance Model across cultures: A three country study. Information Management, 33(1), 1–11.
Studlar, D. T., McAllister, I., & Hayes, B. C. (1998). Explaining the gender gap in voting: A crossnational analysis. Social Science Quarterly, 79(4), 779–798.
Taylor, S. T., (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.
Teo, T. S. H. (2001). Demographic and motivation variables associated with Internet usage activities. Internet Research, 11(2), 125–137.
Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation. MIS Quarterly, 23(2), 239–260.
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(1), 115–139.
Venkatesh, V., (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204.
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.
Walker, K. (1994). I’m no friends the way she’s friends: Ideological and behavioral constructions of masculinity in men’s friendships. Masculinities, 2, 38–55.
Weiser, E. B. (2000). Gender differences in Internet use patterns and Internet application preferences: A two-sample comparison. CyberPsychology & Behavior, 3(2), 167–178.
Wellman, B. (1992). Men in networks: Private communities, domestic friendships. London: Sage.
Wilson, M. (2004). A conceptual framework for studying gender in information systems research. Journal of Information Technology, 19, 81–92.
Wolfe, C. R. (2001). Learning and teaching on the World Wide Web. San Diego, CA: Academic Press.
Zhang, K. K. Z., Lee, K. O. M., Cheung, M. K. C., & Chen, H. P. (2009). Understanding the role of gender in bloggers’ switching behavior. Decision Support Systems, 47(4), 540–546.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Sense Publishers
About this chapter
Cite this chapter
Cheung, C.M., Lee, M.K. (2011). Exploring the Gender Differences in Student Acceptence of an Internet-Based Learning Medium. In: Teo, T. (eds) Technology Acceptance in Education. SensePublishers. https://doi.org/10.1007/978-94-6091-487-4_10
Download citation
DOI: https://doi.org/10.1007/978-94-6091-487-4_10
Publisher Name: SensePublishers
Online ISBN: 978-94-6091-487-4
eBook Packages: Humanities, Social Sciences and LawEducation (R0)
-
Published in cooperation with
https://www.sensepublishers.com/
