Enhancing Social Networking Technologies Adoption through Perceived Usefulness: The setting of Ugandan Institutions of Higher Learning
Keywords:
Key Words, Social Networking Technologies, Perceived Usefulness, Technology Acceptance Model, User Generated Content, SNT AdoptionAbstract
Social Networking Technologies (SNTs) play a major role in education by improving student academic performance through informal learning. The purpose of this study was to examine the influence of Perceived Usefulness on the adoption of Social Networking Technologies in institutions of higher learning in Uganda. A cross sectional survey methodology was employed to gather data from 146 institutions of higher learning on the variables captured by the modified Perceived Usefulness construct of the Technology Acceptance Model. Results of correlation and regression analysis indicated that a positive and significant relationship exists between Perceived Usefulness and SNTs adoption. These findings have theoretical implications for models of SNTs adoption and practical interventions designed at increasing use of SNTs. The findings of this study suggests that managers of higher institutions of learning should advice users on the usefulness of SNTs adoption in learning so as to improve on their academic job performance, increase productivity and enhance effectiveness in teaching and learning in institutions of higher learning in Uganda.
References
Agarwal, R & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences 1999;30(2):361–91.
Amin, M. (2005). Social science research conception, methodology and analysis. Kampala: ICT University Printery.
Ayman, B, N. (2013): Understanding factors affecting the adoption of M-Commerce by consumers: Journal of Applied Sciences 13(6): 913 – 918
Azam, S & Mohammed, Q (2009): Adoption of e-Commerce by the SMEs in Bangladesh: The Effects of Innovation Characteristics and Perceived Risk: ANZMAC 2009
Bagozzi, R. (2007). ‘The legacy of the technology acceptance model and proposal for paradigm shift. Journal of the Association for Information Systems, 8 (4), 244-254.
Buabeng-Andoh, C. (2012). Factors influencing teachers’ adoption and integration of information and communication technology into teaching: A review of the literature. International Journal of Education and Development using Information and Communication Technology (IJEDICT), 2012, Vol. 8, Issue 1, pp. 136-155.
Chung, J, E., Park, N., Wang, H., Fulk, J., & McLaughlin, M (2010): Age differences in perceptions of online community participation among non-users: An extension of the Technology Acceptance Model: Computers in Human Behavior 26 (2010) 1674–1684
Davis, F. (1989). User acceptance of computer technology: a comparison of two theoretical models’. Management Science, 37 (8), 982-1002.
Freedom on the Net. (2014, May 2014). Retrieved July 2, 2015, from Freedom on the Net: http://www.freedomhouse.org/report/freedom-net/freedom-net-2014#.VbVMI-ZjTMs
Greenhow, C., & Burton, L. (2011). Help from my “friends:†social capital in the social network sites of low-income high school students. Journal of Educational Computing Research, 45(2), 223–245.
Grover, A., & Stewart, D. W. (2010). Defining interactive social media in an educational context. In C. Wankel & M. Marovich & J. Stanaityte (Eds.), Cutting edge social media approaches to business education: Teaching with LinkedIn, Facebook, Twitter, Second Life and Blogs. Charlotte: Information Age Publishing.
Gulbahar, Y., & Guven, I. (2008). A Survey on ICT Usage and the Perceptions of Social Studies Teachers in Turkey. Educational Technology & Society, 11 (3), 37-51.
Henderson, R., and Megan J. Divett (2003). Perceived usefulness, ease of use and electronic supermarket use. International Journal of Human-Computer Studies, 59, 383-395.
Hoffman, E. (2009). Social media and learning environments: Shifting perspective on the locus of control in education. Special Issue Technology & Social Media, 2 (15).
Huo, Y., Zhang, P., Ma, L., & Zhang B(2011) :The influencing factors of Chinese farmers adopt m-commerce services: social network perspective: International Journal of Innovative Computing, Information and Control: Volume 7, Number 6, June 2011: 3559 – 3570
Hussain, I., Gulrez, N., & Tahirkheli, S. (2012). Academic Use of Social Media: Practices and Problems of University Students. International Conference on Education and Management Innovation (pp. 1-6). IACSIT Press, Singapore.
Junco, R. (2012). The relationship between frequency of Facebook use, participation in Facebook activities, and student engagement. Computers & Education, Vol.58, pp.162–171.
Junco, R., Elavsky, C. M., & Heiberger, G. (2012). Putting Twitter to the test: assessing outcomes for student collaboration, engagement and success. British Journal of Educational Technology, 44(2), 273–287.
Kaasinen, E (2005): User acceptance of mobile services– value, ease of use, trust and ease of adoption: Thesis for the degree of Doctor of Technology to be presented with due permission for the public examination and criticism in Tietotalo Building, Auditorium TB104 at Tampere University of Technology, on the 22nd of June 2005 at 12 o´clock noon
Khayati, S (2013): Perceived Usefulness and Use of Information Technology: the Moderating Influences of the Dependence of a Subcontractor towards His Contractor: Journal of Knowledge Management, Economics and Information Technology: Vol. III, Issue 6 December 2013
Kingsly, A., Kofi, A., & Yeboah, C. (2013). A conceptual Framework of Social Networking Technologies adoption in Teaching- A case of Ghana. Elsevier, 561-592.
Ko, C., Yen, J., Chen, C. S., Chen, C. C., & Yen, C. (2008). Psychiatric comorbidity of Internet addiction in college students: An interview study. CNS Spectra., 13(2), 147-153.
Lee, D., Park, J., & Ahn, J. (2000): On the explanation of factors affecting e-commerce adoption. Working Paper Last Revised 2000.
Masoodul, H., Rehana, K., Syed, S, A., & Muhammad, A(2014): Consumer Attitudes and Intentions to Adopt Smartphone Apps: Case of Business Students: Pakistan Journal of Commerce and Social Sciences 2014, Vol. 8 (3), 763-779
Meng, X. (2013): Proceedings of the 30th International Conference on Machine Learning, Atlanta, Georgia, USA, 2013. JMLR: W&CP volume 28.
Mortimer, Gary (2015): Determining the drivers of m-banking adoption: A cross cultural study. In AM2015 Academy of Marketing Conference: The Magic in Marketing, 7 - 9 July 2015, Limerick, Ireland
Munguatosha, G. M., Muyinda, P. B., & Lubega, J. T. (2011). A social networked learning adoption model for higher education institutions in developing countries. On the Horizon, 307-320.
Ndekwa, A, G (2014): Factors Influencing Adoption of Information and Communication Technology (ICT) among Small and Medium Enterprises (SMEs) in Tanzania: IRACST- International Journal of Research in Management & Technology (IJRMT), ISSN: 2249-9563 Vol. 4, No.5, October 2014
Nicolaou, A, I., & McKnight, D, H. (2006). Perceived Information Quality in Data Exchanges Information Systems Research 17(4), pp. 332–351.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory. Sydney, Australia: McGraw Hill.
Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning. Educational Technology & Society, 12 (3), 150–162.
Reuben, R. (2012). The Use of Social Media in Higher Education for Marketing and Communications: A Guide for Professionals in Higher Education. Elsevier
Rose, J., and Fogarty, G. J., (2006). Determinants of perceived usefulness and perceived ease of use in the technology acceptance model: senior consumers’ adoption of self-service banking Technologies. Marketing and Management Development, Vol.2, No.10, pp. 122-129.
Rouis, S. (2012). Impact of Cognitive Absorption on Facebook on Students’ Achievement. Cyber psychology, Behavior, And Social Networking, Vol.15 (6), 2012, pp. 296-303.
Sakarkar, G., Deshpande, S. P., & Thakare, V. M. (2014). An online social networking architecture using context data for effective e-learning systems. In Proceedings of the 2nd Int. Conf. on Emerging Research in Computing, Information, Communication and Applications (pp. 33–39).
Shen, J., Li, L., Dietterich, T. G., and Herlocker, J. L. “A hybrid learning system for recognizing user tasks from desktop activities and email messages.†Proceedings of the 11th International Conference on Intelligent User Interfaces, 2006.
Shroff, R. H., Deneen, C. C., & Eugenia, M. W. (2011). Analysis of the technology acceptance model in examining students’ behavioural intention to use an e-portfolio system. Australasian Journal of Information Technology, 600-618.
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, ( ), 273-315.
Venkatesh, V., & Davis, F. (2012). The Technology Acceptance Model Extension for Information Management Systems. Journal of Computer and Information Technology, 50-73.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science.
Venkatesh, V., Morris, M. G., Davis, F. D., & Davis, G. B. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478.
Wang C, Runsheng F , Kyungsoo P, Yuqiang F, Zhenhua L, Yonghao C (2012): Perceived Usefulness, Perceived Security and Adoption of Mobile Government: An Empirical Research. Advances in information Sciences and Service Sciences (AISS), Volume4, Issue 6.
Wang, C., Runsheng, F., Kyungsoo, P., Yuqiang, F., Zhenhua, L., Yonghao, C. (2012). Perceived Usefulness, Perceived Security and Adoption of Mobile Government: An Empirical Research. Advances in information Sciences and Service Sciences (AISS), Volume4, Issue 6.
Yamane, T. (1967). Statistics, An Introductory Analysis (2nd ed.). New York: Harper and Row.
Yang, H. D., & Yoo, Y. (2004). It’s all about attitude: Revisiting the technology acceptance. Decision Support System, 38, 19-31.
Zanamwe, N., Rupere, T., & Kufandirimbwa, O. (2013). Use of Social Networking Technologies in Higher Education in Zimbabwe: A learners’ perspective. International Journal of Computer and Information Technology, 2 (1), 8-18.
Downloads
Published
Issue
Section
License
- Papers must be submitted on the understanding that they have not been published elsewhere (except in the form of an abstract or as part of a published lecture, review, or thesis) and are not currently under consideration by another journal published by any other publisher.
- It is also the authors responsibility to ensure that the articles emanating from a particular source are submitted with the necessary approval.
- The authors warrant that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required.
- The authors ensure that all the references carefully and they are accurate in the text as well as in the list of references (and vice versa).
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-NonCommercial 4.0 International that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.