Mobile learning adoption in higher education in guyana

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Information about Mobile learning adoption in higher education in guyana
Education

Published on March 14, 2014

Author: lenandlar

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1 Company Proprietary and Confidential Mobile Learning Adoption in Higher Education in Guyana Troy Thomas Lenandlar Singh Kemuel Gaffar University of Guyana November 4, 2012

2 Company Proprietary and Confidential OUTLINE • Background • Hypotheses • Data and Method • Results • Discussion • Conclusion • Recommendations and Future Work

3 Company Proprietary and Confidential BACKGROUND • E-learning and technology has transformed the educational landscape worldwide giving rise to new pedagogical systems • One area of e-learning that is gaining increasing popularity and attention is mobile learning (MLearning) - a new educational paradigm! • MLearning allows "anywhere", "anytime" teaching and learning! • Constantly evolving with rapid increase of mobile devices and changing lifestyles of people • Ubiquitous and Pervasive

4 Company Proprietary and Confidential BACKGROUND • Research in m-learning still in its infancy stage • Wang et al. (2010) indicates that studies that explore the best practice of m-learning are largely undefined. • Lack of empirical evidence to show that mobile technology engages students and promote learning (Hlodan, 2010) • Need for systematic studies that examine instructors’ and students’ m-learning experience AND factors that affect adoption and acceptance

5 Company Proprietary and Confidential TECHNOLOGY ACCEPTANCE • Most MLearning studies are based on the Technology Acceptance Model - TAM (Davis, 1989) • or the Unified Theory of Acceptance and Use of Technology - UTAUT (Venkatesh et al., 2003) • Objective is to identify factors that influence adoption and relationship among factors

6 Company Proprietary and Confidential THE UTAUT MODEL - Venkatesh et al. (2003)

7 Company Proprietary and Confidential THE UTAUT MODEL • UTAUT model should explain 70% of the variance in BI (Venkatesh et al., 2003) • In the UTAUT model, the interactions are essential to finding significant effects of SF on BI and FC does not affect BI (Venkatesh et al., 2003) • Most MLearning in HE studies are done in Western countries (Schepers and Wetzels, 2007; Traxler, 2007). Research emerging in non-Western context.

8 Company Proprietary and Confidential THE UTAUT MODEL • Do the hypothesized UTAUT relationships hold in non-Western context? • Jairak et al. (2009) (Thailand) finds an effect of FC on BI and no effect of PE on BI (violations of UTAUT) • Nassuora (2012) (Saudi Arabia) find no effect of SF on BI (may be due to omission of interactions.) • Im, Hong and Kang (2011) (US and Korea) confirm the UTAUT relationships (even without interactions)

9 Company Proprietary and Confidential HYPOTHESIS H1 : PE is positively related to BI H2 : EE is positively related to BI H3 : SF is positively related to BI H4 : ATT is positively related to BI H5 : PE is positively related to ATT H6 : EE is positively related to ATT H7 : SF is positively related to ATT H8 : FC is positively related to ATT H9: FC is positively related to BI

10 Company Proprietary and Confidential CONCEPTUAL STRUCTURAL FRAMEWORK

11 Company Proprietary and Confidential DATA AND METHOD • Large scale (online) survey of students • Survey sent to entire student population via email • 322 usable responses collected (43.4% males, 56.5% females)

12 Company Proprietary and Confidential METHOD • Modified UTAUT framework and survey items adopted from Jairak et al. (2009) - used 5-point rating scales • Confirmatory Factor Analysis (CFA) to determine whether the factors are retrieved from the data. • Reliability of factors and validity of loadings evaluated. • Model fit: RMSEA (<0.06) and CFI (>0.95) fit indices used. Chi-square too sensitive for large samples (Chen 2007; Hui & Bentler 1999).

13 Company Proprietary and Confidential RESULTS - CFA • Initial CFA did not fit very well (RMSEA= 0.08, CFI=0.98) • Modified one correlation between error terms (modification index = 135.96). FC2 and FC3 are correlated. • Revised model fits well (RMSEA 0.059, CFI=0.98). Change in Chi-square = 156.89 for 1 df. • Factor Loadings - generally greater than 0.7 (validity) • Internal Consistency Reliability (Cronbach alpha greater than 0.7)

14 Company Proprietary and Confidential RESULTS - SEM • Initial CFA did not fit very well (RMSEA= 0.08, CFI=0.98) • Modified one correlation between error terms (modification index = 135.96). FC2 and FC3 are correlated. • Revised model fits well (RMSEA 0.059, CFI=0.98). Change in Chi-square = 156.89 for 1 df. • Factor Loadings - generally greater than 0.7 (validity) • Internal Consistency Reliability (Cronbach alpha greater than 0.7)

15 Company Proprietary and Confidential RESULTS - SEM

16 Company Proprietary and Confidential CONCLUSION • 59% of BI explained (Lower than 70% for UTAUT). Researches should experiment with other variables to explain more variance. • FC affects BI (even without ATT) - contradicts UTAUT and Nassuora 2012. • EE does not affect BI (even without ATT) - contradicts UTAUT and Jairak et al. 2009 • FC affects Attitude - contradicts Jairak et al. 2009 • SF affects BI without interactions - contradicts UTAUT • All the other hypotheses confirmed. UTAUT still valuable. • The exploratory treatment is warranted!

17 Company Proprietary and Confidential CONCLUSION – HE at UG • The usefulness (PE) of the technologies is more important than how easy they are to use (EE). • Attitude and the FC are most important to adoption. The effect of limited resources. • PE, EE, FC predict ATT and SF predicts BI so approach adoption promotion needs to be holistic. All factors are important! • • 55% (R-squared) of the variance in ATT is explained. Opportunity for research on attitude promotion.

18 Company Proprietary and Confidential REFERENCES Al-Gahtani, S. S., Hubona, G. S., and Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8):681–691. Bandyopadhyay, K. and Fraccastoro, K. A. (2007). The Effect of Culture on User Acceptance of Information Technology. Communications of the Association for Information Systems, 19(Article 23):522–543. Cheon, J., Lee, S., Crooks, S. M., and Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3):1054–1064. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3):319–340 . Habboush, A. and Hussein, A.-r. (2011). Acceptance of Mobile Learning by University Students. American Journal of Scientific Research, 22(22):119–122.

19 Company Proprietary and Confidential REFERENCES Im, I., Hong, S., and Kang, M. S. (2011). An international comparison of technology adoption. Information & Management, 48(1):1–8. Jairak, K., Praneetpolgrang, P., and Mekhabunchakij, K. (2009). An Acceptance of Mobile Learning for Higher Education Students in Thailand. Special Issue of the International Journal of the Computer, the Internet and Management, 17(SP3):36.1–36.8. Nassuora, A. B. (2012). Student Acceptance of Mobile Learning for Higher Education. American Academic & Scholarly Research Journal, 4(2):0–5. Schepers, J. and Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1):90–103. Teo, T. (2011). Technology Acceptance in Education. In Teo, T., editor, Technology Acceptance in Education: Research and Issues, pages 1–5. Sense Publishers, Rotterdam.

20 Company Proprietary and Confidential REFERENCES Traxler, J. (2005). Defining mobile learning. In IADIS International Conference Mobile Learning 2005, number September 2004, pages 261– 266. Traxler, J. (2007). Defining, Discussing, and Evaluating Mobile Learning: The moving finger writes and having writ…. International Review of Research in Open and Distance Learning, 8(2):1–12. van Raaij, E. M. and Schepers, J. J. (2008). The acceptance and use of a virtual learning environment in China. Computers & Education, 50(3):838– 852. Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3):425–478. Wang, Y.-S. and Shih, Y.-W. (2009). Why do people use information kiosks? A validation of the Unified Theory of Acceptance and Use of Technology. Government Information Quarterly, 26(1):158–165.

21 Company Proprietary and Confidential END OF PRESENTATION Thank You! Kemuel Gaffar kemuel.gaffar@uog.edu.gy

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