2 research outputs found
Recommended from our members
A conceptual framework highlighting e-learning implementation barriers
Purpose– E-learning has gained much focus from educators and researchers, with many extolling e-learning over traditional learning. Despite this focus, implementation of e-learning systems often fails. Literature considers a range of barriers, impacting the success of e-learning implementations, yet to the best of our knowledge no conceptual framework is able to consolidate existing research.
Design/methodology/approach– This paper undertook an in-depth review of literature concerning e-learning implementation barriers. Papers were extracted from established journals and open sources. Articles not related to e-learning implementation barriers were discarded. A total of 259 papers were identified, published between 1990 and 2016. Hermeneutics and data-driven qualitative content analysis was used to define 68 unique barriers.
Findings– The 68 unique barriers were thematically grouped into four conceptual categories, i.e. Technology (T), Individual (I), Pedagogy (P) and Enabling Conditions (EC). These 4 categories led to the conceptualization of ‘TIPEC’ Framework, which highlights the key concepts hindering e-learning implementation and delivery. Results show that most articles only consider a narrow range of success barriers.
Practical implications – The proposed TIPEC framework acts as a guide for education practitioners, system developers, policy makers and researchers. It provides stakeholders with a summary of e-learning barriers.
Originality/Value – This paper fulfils an identified need for a conceptual framework that consolidates all current research related to E-learning implementation barriers
Recommended from our members
E-learning implementation barriers: impact of student’s individual cultural orientation on e-learning device acceptance
E-learning has been emerging for more than a decade, and institutions are increasingly adopting it
to provide a better learning experience to their students. E-learning is the use of electronic means
to deliver and receive education. E-learning offers a wide range of benefits (flexibility of time and
space, cost effectiveness etc.), it also overcomes the shortcomings of traditional learning which has
resulted in its vast adoption by the institutes. Despite its vast growth i.e. 17% per annum, the
failures of e-learning are still at large. Whilst reviewing the literature concerning e-learning
failures, it was identified that numerous barriers, which are hindering the promised benefits of elearning,
are openly discussed in the literature. To understand these factors, the TIPEC framework,
which structures e-learning barriers, was developed; to consolidate literature from the past 26 years
(1990-2016). 259 papers concerning e-learning barriers, was included in the framework, to better
understand the barriers that hinder e-learning implementation. TIPEC framework comprises of 68
unique e-learning implementation barriers, which were grouped into 4 main categories, i.e.,
Technology, Individual, Pedagogy and Enabling Conditions. This thesis focuses on understanding
the impact of the e-learning student’s individual culture orientation on technology related barriers
within the Individual Category. The TIPEC framework highlighted e-learning failures and
motivated this thesis to provide explanations and recommendations to support more successful elearning
implementation and technology adoption, i.e. by accommodating student’s individual
preferences. The objective of this thesis is to identify the role of individual cultural orientation in
determining student’s expectation of services being offered in an e-learning setup and his/her
preference and acceptance of technological component concerning which device he/she prefers to
receive specific e-learning services. For that reason, data was captured from 560 higher education
students of Pakistan; where there have been a lot of initiatives taken up by the government of
Pakistan in past years to improve the state of education in the country.
A study was carried out using a mono method approach and quantitative methodology, using
structured questionnaire, to answer three research questions. Research question 1 explains the role
of education as a service and assessment of students’ perception about the quality of higher
education on the basis of services being offered by the institutions. After a detail review of
literature, 8 Higher Education Service (HES) quality indicators (i.e. Course content, Lecturer’s
Concern for Students, Facilities, Assessment, Social Activities, Communication with University, Counselling Services and People), proposed by Kwan and Ng (1999), were selected to serve as the
basis of my research experiment for question 1. These higher education services are checked for
students’ preference, i.e. whether they prefer to receive these services through traditional/face to
face education or via one of the six identified e-learning devices i.e. TV, Radio, Desktop, Laptop,
Mobile and Tablet. Overall preference results showed that for 5 out of 8 higher education service
indicators, students preferred two devices i.e. Laptop or Mobile. This suggests that students may
be willing, for some services, to use e-learning devices instead of traditional face-to-face
interaction.
Literature suggested that attitudes towards adoption and preference of technological devices are
influenced by cultural orientation. After the review of different concepts of culture i.e. national,
organisation and individual culture, the phenomena of technology preference and acceptance was
explored with reference to the culture at the individual level. This led to the development of second
research question, i.e. does culture at the individual level play a significant role in device
preference? An experiment was performed to analyse technology preference of students against
the HES quality indicators proposed by Kwan and Ng, based on the cultural setting of the
respondents at an individual level. Culture at the individual level was investigated by applying the
Cultural Value Scale (CVSCALE), which is based on the Hofstede’s five cultural dimensions
(Power Distance, Uncertainty Avoidance, Masculinity/Femininity, Individualism/Collectivism and
Long term/Short term Orientation) enhanced for measurement at the individual level. Three
significant clusters of culture at the individual level were found. Cluster 1 was highest in Power
Distance and highest in Masculinity, and they preferred face to face learning. Cluster 2 is the
highest in Uncertainty Avoidance and lowest in Power Distance preferred Mobile for learning
activities. Cluster 3 students were lowest in Uncertainty Avoidance, highest in both Collectivism
and Long-term Orientation, they preferred Laptop for most of the higher education service quality
indicators. This answered the second research question i.e. to improve student satisfaction with his
university experience, we have to keep in view their culture orientation, as their preference varies
across the multiple HES quality indicators and the devices available to receive them. If we do not
accommodate their individual cultural preferences, we risk reducing the student satisfaction
towards the e-learning experience. Second research question led to the formulation of third research question which investigates the
role of culture at the individual level in determining the factors predicting technology acceptance.
The extended model of Unified Theory of Acceptance and Use of Technology (UTAUT2) was
developed by Venkatesh, Thong and Xu (2012) using 8 previous technology acceptance models.
This model was adapted for this study. Based on individual culture based cluster segmentation,
acceptance of Laptop and mobile (the two preferred devices) for 3 significant clusters were
checked. Results showed that acceptance for Laptop and Mobile significantly varied across the
three cluster segments. For Cluster 2 and Cluster 3, which preferred Mobile and Laptop
respectively, different combinations of variables were found to be statistically significant
determinants of the student’s behavioral intention towards the use of their preferred device.
Conclusion is drawn on the basis of results of three research questions and future recommendations
and limitations are then mentioned in detail