CoChat
Sign Up
Cited by 220Educational Technology in LearningTechnology Adoption and User BehaviourOnline and Blended Learning

The DOI matches its Crossref record; the references it cites are not checked yet.

Examining student decisions to adopt Web 2.0 technologies: theory and empirical tests

Hartshorne, Richard, Ajjan, Haya·2009·Journal of Computing in Higher Education
DOI 10.1007/s12528-009-9023-6
Open this paper in CoChat — free account

Overview

Integrity signals

Registry

Crossref · 10.1007/s12528-009-9023-6

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Citations

The citation lists haven’t been fetched yet

References 44 · Cited by 220

Research works printed but not linked: 32

  1. Ajjan, H., & Hartshorne, R. (2008). Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests. The Internet and Higher Education, 11(2), 71–80. · DOI
  2. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting behavior. Englewood Cliffs, NJ: Prentice Hall.
  3. Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122–147. · DOI · Paper page
  4. Baylor, A., & Ritchie, D. (2002). What factors facilitate teacher skill, teacher morale, and perceived student learning in technology-using classroom? Computer and Education, 39(1), 395–414. · DOI · Paper page
  5. Boulos, N. K., & Wheelert, S. (2007). The emerging Web 2.0 social software: An enabling suite of sociable technologies in health and health care education. Health Information and Libraries Journal, 24(1), 2–23. · DOI
  6. Brown, A. L., & Ferrara, R. A. (1985). Diagnosing zones of proximal development. In J. V. Wertsch (Ed.), Culture, communication, and cognition: Vygotskian perspectives (pp. 273–305). NY: Cambridge University Press.
  7. Bruner, J. (1966). Toward a theory of instruction. Cambridge, MA: Harvard University Press.
  8. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. · DOI · Paper page
  9. Dearstyne, B. W. (2007). Blogs, mashups, and wikis: Oh my!. Information Management Journal, 41(4), 24–33.
  10. Dixon, S., & Black, L. (1996). Vocal point: A collaborative, student run online newspaper. In E. J. Valauskas & M. Ertel (Eds.), The internet for teachers and school library media specialists: Today’s applications tomorrow’s prospects (pp. 147–158). New York: Neal-Schuman Publishers, Inc.
  11. Ferdig, R. (2007). Examining social software in teacher education. Journal of Technology and Teacher Education, 15(1), 5–10.
  12. Franklin, T., & Van Harmelen, M. (2007). Web 2.0 for content for learning and teaching in higher education. London: Joint Information Systems Committee.
  13. Johnson, R. T., & Johnson, D. W. (1986). Action research: Cooperative learning in the science classroom. Science and Children, 24, 31–32.
  14. Klamma, R., Chatti, M. A., Duval, E., Fiedler, S., Hummel, H., Hvannberg, E. T. et al. (2006). Social software for professional learning: Examples and research issues. Proceedings of the ICALT-2006 Conference, The Netherlands, pp 912–914. · DOI
  15. Lenhart, A., & Madden, M. (2007). Social networking websites and teens: An overview (pp. 1–10). Washington, DC: Pew Internet and American Life Project.
  16. Linn, M. C. (1991). The computer as learning partner: Can computer tools teach science? In K. Sheingold, L. G. Roberts, & S. M. Malcolm (Eds.), Technology for teaching and learning. Washington, DC: American Association for the Advancement of Science.
  17. Maloney, E. (2007). What Web 2.0 can teach us about learning? Chronicle of Higher Education, 25(18), B26.
  18. Nunnaly, J. (1978). Psychometric theory. New York: McGraw-Hill.
  19. Pence, H. E. (2007). Preparing for the real web generation. Journal of Educational Technology Systems, 35(3), 347–356. · DOI
  20. Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. · DOI · Paper page
  21. Riley, R. W., & Roberts, L. G. (2000). Putting a world-class education at the fingertips of all children: The national educational technology plan. eLearning. Washington, DC: US Department of Education.
  22. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.
  23. Rollett, H., Lux, M., Strohmaier, M., Gisela, D., & Tochtermann, K. (2007). The Web 2.0 way of learning with technologies. International Journal of Learning Technology, 3(1), 87–107. · DOI
  24. Routman, R. (1991). Invitations: Changing as teachers and learners K-12. Toronto, Canada: Irwin Publishing.
  25. Schofield, J. W., & Davidson, A. L. (2002). Bringing the Internet to school: Lessons from an urban district. San Francisco, CA: Jolley-Bass.
  26. Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325–343. · DOI · Paper page
  27. Simões, L., e Gouveia, L. (2008). Web 2.0 and higher education: Pedagogical implications. Higher Education: New Challenges and Emerging Roles for Human and Social Development. 4th International Barcelona Conference on Higher Education Technical University of Catalonia (UPC).
  28. Sturm, M., Kennel, T., McBride, M., & Kelly, M. (2008). The pedagogical implications of Web 2.0. In M. Thomas (Ed.), Handbook of research on Web 2.0 and second language learning (pp. 367–384). Hershey, PA: IGI Publishing.
  29. Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, 29(1), 28–45. · DOI
  30. Triandis, H. C. (1979). Values, attitudes, and interpersonal behavior. In M. M. Page (Ed.), Nebraska symposium on motivation (Vol. 27, pp. 195–259). Lincoln, NE: University of Nebraska Press.
  31. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.
  32. Wright, S. (1921). Correlation and causation. Journal of Agriculture Research, 20, 557–585.

Metadata

Authors
Hartshorne, R., & Ajjan, H.
Affiliations
University of North Carolina at Charlotte (US)
Corresponding author
Hartshorne, Richard
ORCID
Ajjan, Haya
Venue
Journal of Computing in Higher Education
Publisher
Springer Science and Business Media LLC
Published
2009-08-02
Volume
21
Issue
3
Pages
183-198
ISSN
  • 1042-1726 (ISSN-L)
  • 1867-1233
DOI
10.1007/s12528-009-9023-6
OpenAlex
W1986382881
Cited by
220
References
44
Citations by year
2026: 2 · 2025: 3 · 2024: 10 · 2023: 18 · 2022: 20 · 2021: 21 · 2020: 19 · 2019: 11 · 2018: 14 · 2017: 5 · 2016: 13 · 2015: 15 · 2014: 18 · 2013: 19 · 2012: 12
FWCI
26.43
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
Journal of Computing in Higher Education (publishedVersion)
Topics
  • Social Sciences › Education › Educational Technology in Learning
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Education › Online and Blended Learning
Keywords
Web 2.0 tools, student technology adoption, technology acceptance, decomposed theory of planned behavior, student attitudes, subjective norms, intention to use technology, pedagogical benefits, student satisfaction, student-faculty interaction, higher education

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