Define mobile learningFormalInformalUbiquitous and pervasive
Explain modelUTAUT model has been used in various contexts; one is mobile learning for example Jairak et al. (2009)Added age and gender (exogenenous) demographic factors.Jairak et al. (2009) did not find significance between PE to BI and FC to ATB (not predictors)
This should focus on determining whether the scales are distinct of whether they overlap.This would enable the use of confirmatory factor analysis which facilitate better examination of the measurement models. Both metric and scalar invariance can be tested so that we are in a better position to evaluate how well the scales are working in the population. This would also allow the use of LISREL (Structural Equation) models to test the relationships between the factors of the UTAUT model
This may help to bridge the gap between lecturers and students in terms the capability of the mobile devices especially phones.
_mobile learning lecturers versus students on usage and perception using the utaut model
Mobile Learning: Lecturers versus Students on Usage and
Perception using the UTAUT Model
Department of Computer Science, University of Guyana
Department of Computer Science, University of Guyana
Department of Mathematics, Physics and Statistics, University of Guyana
• Review of Literature
• Research Questions
• Recommendations and Future Work
• E-learning has transformed the educational landscape worldwide
• Technology is fundamentally changing the way we teach and learn
• New pedagogical models, curriculum delivery methods and
• One area of e-learning that is gaining increasing popularity and
attention is mobile learning (m-learning)
• M-learning has essentially extended the reach of e-learning and
distance education systems by allowing educators and students to
teach and learn anywhere, anytime and on the move
Background & Context
• Despite increased use of mobile devices, Guyana is faced with several
o Bandwidth issues
o Cost of equipment /service
o Lack of competition (only 2 mobile providers)
• With these in mind, m-learning at the University of Guyana appears far-
o Lack of policy
o Inadequate infrastructure
o Cost of hardware and software systems
• M-learning is an opportunity for the University of Guyana and similar
o What opportunities exist?
o Lack of experimentation and perception!
• Research in m-learning still in its infancy stage
• Experimentation mostly in developed countries with affordable mobile
technology and fast-paced developments
• Wang et al. (2010) claims that studies that explore the best practice of m-
learning are largely undefined.
• Need for systematic studies that examine instructors’ and students’ m-
• Lack of empirical evidence to show that mobile technology engages
students and promote learning (Hlodan, 2010)
• Jairak et al. (2009) found positive effects of various factors on attitude to
technology and behavioural intention.
(i) To investigate the extent of ownership and usage of
mobile devices by staff and students at the University of
(ii) To investigate the relationships among the elements of
the UTAUT model with specific focus on how they
influence attitude towards and intentions to use M-
(iii) To assess the relative propensity for adoption of M-
learning between students and lecturers.
Large scale (online) survey of students and lecturers
• Approximately 10% response rate from student population (508
• Approximately 20% response rate from lecturers after supplementary
paper survey (63 responses)
• Attitudinal items adopted from Jairak et al. (2009)
• UTAUT (Unified Theory of Acceptance and Use of Technology) Model
by Vanketesh et al. (2003)
• Factor analysis: Principal Component Analysis (PCA). Factor scores
generated by regression method and saved.
• Evaluation of internal consistency (Cronbach Alpha).
• Path analysis based on the factor scores.
• Comparisions of mean scale levels: Students vs. Lecturers.
The Research Model Used (Adopted from Jairak et al. (2009) with
Mean Scale Levels
Lect 95% CI
PE 381 56 16.22 2.966 2.838 15.20 15.922 16.518
EE 390 56 12.56 2.219 2.084 10.95 12.34 12.78
SF 394 55 9.98 2.693 2.213 9.75 9.714 10.246
FC 359 54 17.19 3.895 4.120 13.69 16.787 17.593
ATT 396 56 12.79 2.111 1.678 12.14 12.582 12.998
BI 386 54 11.78 2.546 2.540 9.76 11.526 12.034
• Further research on scale development.
• Further research with larger sample size for
• To influence the use of mobile learning among
lecturers (if desired) the facilitating conditions
inclusive of support mechanisms, and
infrastructure should be addressed since this
seems to have a substantial impact on
• The university can also seek to form relationships
with technology providers so that devices and
services (e.g. mobile phones) can be make
available at reasonable prices.
• Further experimental studies should be conducted
on the effects of the use of mobile learning on the
quality of student experience and on the effects on
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