Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 328

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Perceived Ease of Use and Perceived Usefulness of Social Media for e-Learning in Libyan Higher Education: A Structural Equation Modeling Analysis

Open access
Murdoch University, Australia, Elkaseh, Ali Mohamed, Wong, Kok Wai, Murdoch University, Australia, Fung, Chun Che, Murdoch University, Australia·2016·International Journal of Information and Education Technology

Abstract

Social networking media are becoming popular among students and teachers in higher education.Researchers have also started to explore the use of social networking media for teaching and learning in higher education.Social networking media have offered new opportunities for sharing, creating and interacting between students and teachers.However, to implement and adopt such technology, there is a need to investigate the factors that influence the acceptance of the students and the teachers using such technologies as a tool for learning and teaching.In this paper, a study based on the Technology Acceptance Model (TAM), which emphasizes on Perceived Ease of Use and Perceived Usefulness together with Behavior Intention to use new technologies, is used to test the factors of using social networking media for e-learning in Libyan higher education.A quantitative research method was employed utilizing survey method.Research data was collected from a sample of teachers and students from four universities in the Libyan higher educational sector.Structural Equation Modeling was carried out to examine the predictive behaviour of the proposed factors of the research model.It was discovered from the study that the Perceived Ease of Use and Perceived Usefulness are important factors for predicting a student's and teachers' behavioral intention to use social networking media for e-learning in Libyan higher education.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.7763/ijiet.2016.v6.683

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Research works printed but not linked: 38

  1. [1] N. H. Jabr, "Social networking as a tool for extending academic learning and communication," International Journal of Business and Social Science, vol. 2, pp. 93-102, 2011.
  2. [2] W. M. Al-rahmi, M. S. Othman, and M. A. Musa, "The improvement of students' academic performance by using social media through collaborative learning in Malaysian higher education," Asian Social Science, vol. 10, 2014.
  3. [4] E. Dahlstrom, ECAR National Study of Undergraduate Students and Information Technology, 2011: EDUCAUSE Center for Applied Research, 2011.
  4. 10.3102/0013189X09336671 · DOI · Paper page
  5. [6] C. Redecker, K. Ala-Mutka, M. Bacigalupo, A. Ferrari, and Y. Punie, "Learning 2.0: The impact of Web 2.0 innovations on education and training in Europe," Final Report: European Commission-Joint Research Center-Institute for Porspective Technological Studies, Seville, 2009.
  6. 10.1207/s15327809jls1403_3 · DOI
  7. [10] A. Elkaseh, K. W. Wong, and C. C. Fung, "The impact of teaching and learning styles on behavioural intention to use e-learning in Libyan higher education," International Review of Contemporary Learning Research, pp. 25-34, 2014.
  8. [11] A. Rhema and I. Miliszewska, "Towards e-learning in higher education in Libya," Issues in Informing Science and Information Technology, vol. 7, pp. 423-7, 2010. · DOI
  9. 10.1002/bltj.20298 · DOI
  10. 10.1145/1104966.1104968 · DOI · Paper page
  11. [14] L. Jonnavithula and A. Tretiakov, "A model for the effects of online social networks on learning," presented at Ascilite Conference, 2012.
  12. [15] A. Kamenetz, "Gates foundation bets on facebook app to help kids graduate," Fast Company, vol. 14, 2011.
  13. [16] R. Harrison and M. Thomas, "Identity in online communities: Social networking sites and language learning," International Journal of Emerging Technologies and Society, vol. 7, pp. 109-124, 2009.
  14. 10.1016/j.compedu.2009.07.008 · DOI
  15. [19] A. Schroeder, S. Minocha, and C. Schneider, "Social software in higher education: The diversity of applications and their contributions to students' learning experiences," Communications of the Association for Information Systems, vol. 26, pp. 547-564, 2010. · DOI
  16. [20] A. Schroeder, S. Minocha, and C. Schneider, "Social software in higher education: The diversity of applications and their contributions to students' learning experiences," Communications of the Association for Information Systems, vol. 26, p. 25, 2010. · DOI
  17. [22] W. Rifkin, N. Longnecker, J. Leach, L. Davis, and L. Orthia, "Motivate students by having them publish in new media: An invitation to science lecturers to share and test," presented at the Australian Conference on Science and Mathematics Education, 2012.
  18. 10.1087/20110306 · DOI · Paper page
  19. 10.1287/mnsc.35.8.982 · DOI · Paper page
  20. [26] F. Wahid, "Using the technology adoption model to analyze Internet adoption and use among men and women in Indonesia," The Electronic Journal of Information Systems in Developing Countries, vol. 32, 2007.
  21. 10.1016/j.im.2004.08.001 · DOI
  22. 10.1016/j.compedu.2008.11.002 · DOI · Paper page
  23. 10.1111/j.1467-8535.2004.00426.x · DOI
  24. 10.1016/S0378-7206(98)00028-7 · DOI · Paper page
  25. [36] M. H. Seif, M. R. Sarmadi, I. Ebrahimzadeh, and H. Zare, "A model for predicting intention to use e-learning based on epistemological beliefs," Life Science Journal, vol. 9, pp. 926-929, 2012.
  26. 10.1016/0360-1315(90)90036-7 · DOI
  27. [40] Y. Zhao and F. L. Bryant, "Can teacher technology integration training alone lead to high levels of technology integration? A qualitative look at teachers' technology integration after state mandated technology training," Electronic Journal for the Integration of Technology in Education, vol. 5, pp. 53-62, 2006.
  28. 10.2307/249029 · DOI
  29. [44] F. J. Fowler, Survey Research Methods, vol. 1, Sage, 2009.
  30. 10.2307/3151312 · DOI · Paper page
  31. [48] J. F. Hair, R. L. Tatham, R. E. Anderson, and W. Black, Multivariate Data Analysis, Upper Saddle River, NJ: Pearson Prentice Hall, vol. 6, 2006.
  32. 10.2307/2786945 · DOI
  33. [50] J. Hair, Multivariate Data Analysis, vol. 6, 2006.
  34. [51] C. Fornell and D. F. Larcker, "Evaluating structural equation models with unobservable variables and measurement error," Journal of Marketing Research (JMR), vol. 18, 1981.
  35. [54] J. F. Hair, R. E. Anderson, R. L. Tatham, and W. Black, Multivariate Data Analysis, Upper Saddle River, 1998.
  36. [55] R. L. Tatham and W. C. Black, Multivariate Data Analysis, vol. 1, pp. 1-19, New Jersey: Prcentice Hall, 1998.
  37. [56] Y. K. Dwivedi, M. D. Williams, B. Ramdani, S. Niranjan, and V. Weerakkody, "Understanding factors for successful adoption of web 2.0 applications," ECIS, 2011.
  38. [57] R. G. Martin, "Factors affecting the usefulness of social networking in e-learning at German University of Technology in Oman," International Journal of e-Education, e-Business, e-Management and e-Learning, vol. 2, 2012.

Cited by

Metadata

Authors
Murdoch University, A., Elkaseh, A. M., Wong, K. W., Murdoch University, A., Fung, C. C., & Murdoch University, A.
Venue
International Journal of Information and Education Technology
Published
2016
Volume
6
Issue
3
Pages
192-199
ISSN
2010-3689 (ISSN-L)
OpenAlex
W2329871087
Cited by
328
References
4
FWCI
28.30
Type
journal article
Language
en
Open access
diamond

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

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.