Skip to main content
Log in

Exploring the relationship between African American adult learners’ computer, Internet, and academic self-efficacy, and attitude variables in technology-supported environments

  • Published:
Journal of Computing in Higher Education Aims and scope Submit manuscript

Abstract

This study was conducted to investigate the relationship between African American adult students’ computer, Internet, and academic self-efficacy, and their attitudes toward computers, in technology-supported environments. The study examined whether computer and Internet self-efficacy differed between students with high and low levels of user attitude and computer anxiety. Correlations between academic self-efficacy and computer and Internet self-efficacy were also explored. Participants included adult students who were enrolled in face-to-face and online courses at a university in the southern United States. Quantitative approaches (i.e., MANOVA, correlation, and regression) were used to analyze the collected data. Results indicated that adult students showed a higher level of confidence in performing basic computer or software skills and Internet browsing actions in comparison to advanced computer skills or Internet tasks (e.g., tasks related to encrypting/decrypting and system manipulation). Computer and Internet self-efficacy significantly differed between learners with high and low levels of attitudes toward computers. Positive correlations were found between computer self-efficacy, Internet self-efficacy, and academic self-efficacy. Both computer self-efficacy and Internet self-efficacy were significant predictors of academic self-efficacy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Austin, B., & Royster, J. (2017). Exploring the use of skype technology for teaching food, nutrition and health to African American elders in Seattle, Washington: A Pilot Program. Journal of the Academy of Nutrition & Dietetics, 116, 80. https://doi.org/10.1016/j.jand.2016.06.281.

    Article  Google Scholar 

  • Baker, M. M. (2015). The relationship of technology use with academic self-efficacy and academic achievement in urban middle school students. Retrieved from ProQuest (3689105).

  • Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1016/0146-6402(78)90002-4.

    Article  Google Scholar 

  • Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122–147. https://doi.org/10.1037/0003-066X.37.2.122.

    Article  Google Scholar 

  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Bandura, A., & Schunk, E. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41(3), 586–598.

    Article  Google Scholar 

  • Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: Testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20, 1–15. https://doi.org/10.1016/S0747-5632(03)00049-9.

    Article  Google Scholar 

  • Bozionelos, N. (2001). Computer anxiety: relationship with computer experience and prevalence. Computers in Human Behavior, 17, 213–224. https://doi.org/10.1016/S0747-5632(00)00039-X.

    Article  Google Scholar 

  • Bozionelos, N. (2004). Socio-economic background and computer use: The role of computer anxiety and computer experience in their relationship. International Journal of Human–Computer Studies, 61, 725–746. https://doi.org/10.1016/j.ijhcs.2004.07.001.

    Article  Google Scholar 

  • Buche, M. W., Davis, L. R., & Vician, C. (2007). A longitudinal investigation of the effects of computer anxiety on performance in a computing-intensive environment. Journal of Information Systems Education, 18(4), 415–423.

    Google Scholar 

  • Chang, S. L., Shieh, R. S., Liu, Z. F., & Yu, P. T. (2012). Factors influencing women’s attitudes towards computers in a computer literacy training program. The Turkish Online Journal of Educational Technology, 11(4), 177–187.

    Google Scholar 

  • Chua, S. L., Chen, D., & Wong, A. F. L. (1999). Computer anxiety and its correlates: A meta-analysis. Computers in Human Behavior, 15, 609–623. https://doi.org/10.1016/S0747-5632(99)00039-4.

    Article  Google Scholar 

  • Clark, K. (2003). Impact of technology on the academic self-efficacy and career selection of African American Students. Information Technology in Childhood Education Annual, 1, 79–89.

    Google Scholar 

  • Clark, K. (2017). Practical applications of technology as a key to reducing the digital divide among African–American youth. Journal of Children and Media, 11(2), 252–255. https://doi.org/10.1080/17482798.2017.1306369.

    Article  Google Scholar 

  • Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688.

    Article  Google Scholar 

  • Compeau, D. R., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145–158.

    Article  Google Scholar 

  • Durndell, A., & Haag, Z. (2002). Computer self-efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. Computers in Human Behavior, 18, 521–535. https://doi.org/10.1016/S0747-5632(02)00006-7.

    Article  Google Scholar 

  • Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Retrieved from http://jcmc.indiana.edu/vol6/issue1/eastin.html.

  • Garland, K. J., & Noyes, J. M. (2004). Computer experience: a poor predictor of computer attitude. Computers in Human Behavior, 20, 823–840.

    Article  Google Scholar 

  • Glass, C., & Knight, L. (1988). Cognitive factors in computer anxiety. Cognitive Therapy and Research, 12, 351–366.

    Article  Google Scholar 

  • Graham, R., & Choi, K. S. (2016). Explaining African–American cell phone usage through the social shaping of technology approach. Journal of African American Studies, 20(1), 19–34. https://doi.org/10.1007/s12111-015-9317-x.

    Article  Google Scholar 

  • Hause, R., Paul, R., & Bradley, J. (2012). Computer self-efficacy, anxiety, and learning in online versus face to face medium. Journal of Information Technology Education: Research, 11, 141–154.

    Article  Google Scholar 

  • Hodges, C. B. (2008). Self-efficacy in the context of online learning environments: A review of the literature and directions for research. Performance Improvement Quarterly, 20(3/4), 7–25.

    Article  Google Scholar 

  • Hong, K. S., Chai, M. L., Tan, K. W., Hasbee, U., & Ting, L. N. (2014). ESL teachers’ computer self-efficacy, attitudes toward computer and classroom computer use. Social Sciences & Humanities, 22(2), 369–385.

    Google Scholar 

  • Huang, K., Cotten, S. R., & Rikard, R. V. (2017). Access is not enough: the impact of emotional costs and self-efficacy on the changes in African–American students’ ICT use patterns. Information, Communication & Society, 20(4), 637–650. https://doi.org/10.1080/1369118X.2016.1203456.

    Article  Google Scholar 

  • Joo, Y. J., Bong, M., & Choi, H. J. (2000). Self-efficacy for self-regulated learning, academic self-efficacy and Internet self-efficacy in web-based instruction. Educational Technology Research and Development, 48(2), 5–17.

    Article  Google Scholar 

  • Korobili, S., Togia, A., & Malliari, A. (2010). Computer anxiety and attitudes Among undergraduate students in Greece. Computers in Human Behavior, 26(3), 399–405. https://doi.org/10.1016/j.chb.2009.11.011.

    Article  Google Scholar 

  • Kuo, Y. C., & Belland, B. R. (2016). An exploratory study of adult learners’ perceptions of online learning: Minority students in continuing education. Educational Technology Research and Development, 64(4), 661–680. https://doi.org/10.1007/s11423-016-9442-9.

    Article  Google Scholar 

  • Kuo, Y. C., Walker, A., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35–50. https://doi.org/10.1016/j.iheduc.2013.10.001.

    Article  Google Scholar 

  • Lee, C. L., & Huang, M. K. (2014). The influence of computer literacy and computer anxiety on computer self-efficacy: The moderating effect of gender. Cyperpsychology, Behavior, and Social Networking, 17(3), 172–180.

    Article  Google Scholar 

  • Liang, J. C., & Wu, S. H. (2010). Nurses’ motivations for web-based learning and the role of Internet self-efficacy. Innovations in Education and Teaching International, 47(1), 226–237.

    Article  Google Scholar 

  • Lim, C. K. (2001). Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners. American Journal of Distance Education, 15(2), 41–51.

    Article  Google Scholar 

  • Loyd, B. H., & Gressard, C. (1984). Reliability and factorial validity of computer attitude scales. Educational and Psychological Measurement, 44(2), 501–505. https://doi.org/10.1177/0013164484442033.

    Article  Google Scholar 

  • Maricutoiu, L. P. (2014). A meta-analysis on the antecedents and consequences of computer anxiety. Procedia - Social and Behavioral Sciences, 127, 311–315. https://doi.org/10.1016/j.sbspro.2014.03.262.

    Article  Google Scholar 

  • Mueller, J., & Wood, E. (2012). Patterns of beliefs, attitudes, and characteristics of teachers that influence computer integration. Education Research International, 2012, 1–13. https://doi.org/10.1155/2012/697357.

    Article  Google Scholar 

  • Murphy, C. A., Coover, D., & Owen, S. V. (1989). Development and validation of the computer self-efficacy scale. Educational and Psychological Measurement, 49(4), 893–899. https://doi.org/10.1177/001316448904900412.

    Article  Google Scholar 

  • Nahm, E. S., & Resnick, B. (2008). Development and testing of the web-based learning self-efficacy scales for older adults. Ageing International, 32(1), 3–14.

    Article  Google Scholar 

  • Osborn, V. (2001). Identifying at-risk students in videoconferencing and web-based distance education. The American Journal of Distance Education, 15(1), 41–54.

    Article  Google Scholar 

  • Ozerbas, M. A., & Erdogan, B. H. (2016). The effect of the digital classroom on academic success and online technologies self-efficacy. Educational Technology & Society, 19(4), 203–212.

    Google Scholar 

  • Paraskeva, F., Bouta, H., & Papagianni, A. (2008). Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice. Computers & Education, 50, 1084–1091.

    Article  Google Scholar 

  • Pintrich, P. R., Smith, D. A., Garcia, T., & McKeachie, W. J. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educational and Psychological Measurement, 53(3), 801–813.

    Article  Google Scholar 

  • Puzziferro, M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. American Journal of Distance Education, 22(2), 72–89.

    Article  Google Scholar 

  • Sam, K., Othman, A., & Nordin, Z. (2005). Computer self-efficacy, computer anxiety, and attitudes toward the Internet: A study among undergraduates in Unimas. Educational Technology & Society, 8(4), 205–219.

    Google Scholar 

  • Sanders, D., & Morrison-Shetlar, A. I. (2001). Student attitudes toward web-enhanced instruction in an introductory biology course. Journal of Research on Computing in Education, 33(3), 1–13.

    Article  Google Scholar 

  • Santoso, H. B., Lawanto, O., Becker, K., Fang, N., & Reeve, E. M. (2014). High and low computer self-efficacy groups and their learning behavior from self-regulated learning perspective while engaged in interactive learning modules. Journal of Pre-College Engineering Education Research, 4(2), 11–28. https://doi.org/10.7771/2157-9288.1093.

    Article  Google Scholar 

  • Shank, D. B., & Cotten, S. R. (2014). Does technology empower urban youth? The relationship of technology use to self-efficacy. Computers & Education, 70, 184–193. https://doi.org/10.1016/j.compedu.2013.08.018.

    Article  Google Scholar 

  • Shi, J., Chen, Z., & Tian, M. (2011). Internet self-efficacy, the need for cognition, and sensation seeking as predictors of problematic use of the Internet. Cyberpsychology, Behavior, and Social Networking, 14(4), 231–234.

    Article  Google Scholar 

  • Simsek, A. (2011). The relationship between computer anxiety and computer self-efficacy. Contemporary Educational Technology, 2(3), 177–187.

    Google Scholar 

  • Smith, A. (2014). African Americans and technology use. Retrieved from http://www.pewinternet.org/2014/01/06/african-americans-and-technology-use/.

  • Torkzadeh, G., Chang, C. J., & Demirhan, D. (2006). A contingency model of computer and internet self-efficacy. Information & Management, 43(4), 541–550. https://doi.org/10.1016/S0747-5632(02)00010-9.

    Article  Google Scholar 

  • Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of computer self-efficacy scales and the impact of computer training. Educational and Psychological Measurement, 54(3), 813–821.

    Article  Google Scholar 

  • Torkzadeh, G., Pflughoeft, K., & Hall, L. (1999). Computer self-efficacy, training effectiveness and user attitudes: An empirical study. Behaviour & Information Technology, 18(4), 299–309.

    Article  Google Scholar 

  • Torkzadeh, G., & Van Dyke, T. P. (2002). Effects of training on Internet self-efficacy and computer user attitudes. Computers in Human Behavior, 18(5), 479–494. https://doi.org/10.1016/S0747-5632(02)00010-9.

    Article  Google Scholar 

  • Tsai, C. C. (2012). The development of epistemic relativism versus social relativism via online peer assessment, and their relations with epistemological beliefs and Internet self-efficacy. Educational Technology & Society, 15(2), 309–316.

    Google Scholar 

  • Warren, J. R., Hecht, M. L., Jung, E., Kvasny, L., & Henderson, M. G. (2010). African American ethnic and class-based identities on the World Wide Web: Moderating the effects of self-perceived information seeking/finding and web self-efficacy. Communication Research, 37(5), 674–702. https://doi.org/10.1177/0093650210374005.

    Article  Google Scholar 

  • Wu, Y. T., & Tsai, C. C. (2006). University students’ Internet attitudes and Internet self-efficacy: A study at three universities in Taiwan. CyberPsychology & Behavior, 9, 441–450. https://doi.org/10.1089/cpb.2006.9.441.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yu-Chun Kuo.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kuo, YC., Belland, B.R. Exploring the relationship between African American adult learners’ computer, Internet, and academic self-efficacy, and attitude variables in technology-supported environments. J Comput High Educ 31, 626–642 (2019). https://doi.org/10.1007/s12528-019-09212-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12528-019-09212-3

Keywords

Navigation