Abstract
In today’s higher education, the Internet is indispensable in creating, storing, and disseminating information and knowledge. This study examines gender differences among college students in their usage perceptions of the Internet. A multiple-variable logistic model was proposed and tested using data gathered from 805 college students. The results of the study suggest gender differences in usage perceptions of the Internet can be detected among college students. Specifically, the differences are reflected in that male college students have a higher level of perceptions of Internet self-efficacy, experience, and information overload than females. Implications for research in information systems and practice in higher education are discussed.
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Arbaugh, J. B. (2002). Managing the online classroom: a study of technological and behavioral characteristics of Web-based MBA courses. Journal of High Technology Management Research, 13(2), 203–223.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs: Prentice Hall.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351–370.
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511–535.
Chin, W. (1998). The partial least squares approach to structural equation modeling. In G. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah: Lawrence Erlbaum Associate.
Chin, W., Marcolin, B., & Newsted, P. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189–211.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
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.
Eppler, M. J., & Mengis, J. (2004). The concept of information overload: a review of literature from organization science, accounting, marketing, MIS, and related disciplines. The Information Society, 20(5), 325–344.
Fornell, C., & Larcker, V. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Hair, J., Jr., Black, W., Babin, B., Anderson, R., & Tatham, R. (2005). Multivariate data analysis (6th ed.). Upper Saddle River: Prentice Hall.
Hargittai, E., & Shafer, S. (2006). Differences in actual and perceived online skills: the role of gender. Social Science Quarterly, 87(2), 432–448.
Kaifi, B. A., Mujtaba, B. G., & Williams, A. A. (2009). Online college education for computer-savvy students: a study of perceptions and needs. Journal of College Teaching and Learning, 6(6), 1–16.
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213.
Kraemer, K. L., Danziger, J. N., Dunkle, D. E., & King, J. L. (1993). The usefulness of computer-based information to public managers. MIS Quarterly, 17(2), 129–148.
Lenhart, A. (2009, January 14). Pew Internet project data memo. Retrieved from http://www.pewinternet.org/~/media//Files/Reports/2009/PIP_Adult_social_networking_data_memo_FINAL.pdf.pdf
Li, N., & Kirkup, G. (2007). Gender and cultural differences in Internet use: a study of China and the UK. Computers & Education, 48(2), 301–317.
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: the case of information systems continuance. MIS Quarterly, 31(4), 705–737.
Ma, Q., & Liu, L. (2005). The role of Internet self-efficacy in the acceptance of Web-based electronic medical records. Journal of Organizational and End User Computing, 17(1), 38–57.
Marakas, G. M., Johnson, R. D., & Clay, P. F. (2007). The evolving nature of the computer self-efficacy construct: an empirical investigation of measurement construction, validity, reliability and stability over time. Journal of the Association for Information Systems, 8(1), 16–46.
Nunnally, J., & Bernstein, I. (1994). Psychometric theory. New York: McGraw Hill.
Ono, H., & Zavodny, M. (2003). Gender and the internet. Social Science Quarterly, 84(1), 111–121.
Orlikowski, W. J. (1992). The duality of technology: rethinking the concept of technology in organizations. Organization Science, 3(2), 398–427.
Qureshi, S., & Hoppel, C. (1995). Ruling the net. Harvard Business Review, 74(3), 125–133.
Rekabdarkolaei, S. M., & Amuei, F. (2008). Evaluation of ICT literacy differences in trainee student teachers from the view of sexuality. Campus-Wide Information Systems, 25(3), 176–188.
Rosen, L. D., & Maguire, P. D. (1990). Myths and realities in computerphobia: a meta-analysis. Anxiety Research, 3(3), 175–191.
Sherman, R. C., End, C., Kraan, E., Cole, A., Campbell, J., Birchmeier, Z., et al. (2000). The Internet gender gap among college students: forgotten but not gone? CyberPsychology and Behavior, 3(5), 885–894.
Teo, T., & Lim, V. (1997). Usage patterns and perceptions of the Internet: the gender gap. Equal Opportunities International, 16(6–7), 1–8.
van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.
Venkatesh, V., & Morris, M. (2000). Why don’t men ever stop to ask for direction? Gender, social influence, and their role in technology acceptance and usage behaviors. MIS Quarterly, 24(1), 115–139.
Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.
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Appendix. Survey items
Appendix. Survey items
(Note: Except Experience, the anchors for scales: 1 = Strongly Disagree; 5 = Strongly Agree)
Perceived Internet self-efficacy (InternetSE):
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InternetSE1:
I’m proficient at using the Internet
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InternetSE2:
I feel confident that I can use the Internet to achieve my goals.
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InternetSE3:
Using the Internet is probably something that I am good at.
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InternetSE4:
I believe that using the Internet is a skill that I can use easily.
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InternetSE5:
I believe that my skills at using the Internet are quite good.
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InternetSE6:
When it comes to using the Internet, my skills are top-notch.
Perceived Internet experience (Experience):
Experience: How many hours per week do you use the Internet?
Perceived ease of Internet use (EaseUse):
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EaseUse 1:
This web site was easy to use.
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EaseUse 2:
I found it easy to get the web site to do what I wanted it to do.
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EaseUse 3:
It was easy to get the web site to give me the information I was looking for.
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EaseUse 4:
I found it easy to search for the type of job information I wanted.
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EaseUse 5:
The job search functions of the web site were easy to use.
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EaseUse 6:
It was easy to get the job search functions to give me the information I was looking for.
Perceived usefulness of the Internet (Usefulness):
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Usefulness1:
This web site helped me to quickly make a decision about whether I would like to work for the company.
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Usefulness2:
This web site enabled me to effectively get the information I needed.
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Usefulness3:
This web site was useful for deciding whether to pursue employment with this organization.
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Usefulness4:
The search functions enabled me to get the information I wanted.
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Usefulness5:
The search functions helped me get information in the order I was looking for it.
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Usefulness6:
The search functions helped me decide whether I would like to work for this company.
Perceived Internet information overload (InfoLoad):
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InfoLoad1:
This web site overloaded me with information.
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InfoLoad2:
Too much information was provided at one time.
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InfoLoad3:
There was more information than I could interpret right away.
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Hu, T., Zhang, X., Dai, H. et al. An examination of gender differences among college students in their usage perceptions of the internet. Educ Inf Technol 17, 315–330 (2012). https://doi.org/10.1007/s10639-011-9160-1
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DOI: https://doi.org/10.1007/s10639-011-9160-1