Evaluating E-learning systems success : an empirical study

E-learning, as a direct result of the integration of technology and education, has emerged as a powerful medium of learning particularly using Internet technologies. The undeniable significance of e-learning in education has led to a massive growth in the number of e-learning courses and systems offering different types of services. Thus, evaluation of e-learning -systems is vital to ensure successful delivery, effective use, and positive impacts on learners. Based on an intensive review of the literature, a comprehensive model has been developed which provides a holistic picture and identifies different levels of success related to a broad range of success determinants. The model has been empirically validated by fitting the model to data collected from 563 students engaged with an e-learning system in one of the UK universities through a quantitative method of Partial Least Squares - Structural Equation Modelling (PLS-SEM). The determinants of e-learning perceived satisfaction are technical system quality, information quality, service quality, support system quality, learner quality, instructor quality, and perceived usefulness, which together explain 71.4% of the variance of perceived satisfaction. The drivers of perceived usefulness are technical system quality, information quality, support system quality, learner quality, and instructor quality, and these explain 54.2% of the variance of perceived usefulness. Four constructs were found to be the determinants of e-learning use, namely educational system quality, support system quality, learner quality, and perceived usefulness, and together they account for 34.1%. Finally, 64.7% of the variance of e-learning benefits was explained by perceived usefulness, perceived satisfaction, and use

The Determinants of the Post-Adoption Satisfaction of Educators with an E-Learning System

This paper examines factors that influence the post-adoption satisfaction of educators with e-learning systems. Based on the expectation-confirmation framework, we propose a research model that demonstrates how post-adoption beliefs affect post-adoption satisfaction. The model was tested at a university by educators (n = 175) who use an e-learning platform to conduct their teaching. The results suggest that post-adoption satisfaction is driven by confirmation, perceived system quality, perceived usefulness, perceived work compatibility and perceived support. These core determinants of satisfaction explained around 83% of the total variance of satisfaction in this study

Adoption of extended UTAUT model on e-learning in UAE higher education institutions

The fast development of e-learning technology has become a crucial aspect of learning in higher institutions of learning. Just as with any other technology, important factors affect users’ behavioural intention to adopt e-learning. Previous studies have explained the factors affecting e-learning adoption using the UTAUT model in western contexts. However, such factors or antecedents of e-learning adoption may be varied in non-western contexts. The propositions of the UTAUT model have been severally tested in the western and developed nations context, but there exist inadequate empirical validations of the propositions of the model in non-western, i.e. in developing nations. Therefore, building on already established antecedents and factors, the study sought to investigate the direct effect of the four determinants of e-learning adoption, including the added variable-service quality on HEI students’ behavioural intention to use e-learning technologies in the UAE. Furthermore, the study also examined the mediating role of perceived satisfaction, behavioural intention and perceived usefulness in the relationship between the five determinants of e-leaning adoption and the actual use of e-learning systems. Using a quantitative approach and a survey research design, data were obtained from a sample of 453 students selected from pioneering universities with e-learning infrastructures in the UAE. Data were analyzed using the partial least squares structural equation modelling (PLS-SEM). The results show that from a total of 16 direct hypotheses, only four hypotheses were rejected. Regarding the mediating analysis, the results show that perceived usefulness and perceived satisfaction significantly mediates the relationship between performance expectancy, effort expectancy, social influence, service quality, facilitating condition and the actual use of e-learning. However, students’ behavioural intention only mediates the relationship between facilitating condition and actual use of e-learning; nonetheless not mediating the relationship between performance expectancy, effort expectancy, social influence, service quality, and e-learning usage. Interestingly, the study showed that service quality plays a crucial role in HEI students’ perceived usefulness and perceived satisfaction regarding using e-learning technologies. This finding shows a novel contribution of the study in introducing a new antecedent of e-learning adoption, i.e. service quality, perceived usefulness and perceived satisfaction to the technology acceptance models in a higher education context. Consequently, future studies can explore service quality as an integral part of the antecedents of e-learning adoption in higher education in a context not covered by the scope of this study. Recommendations to relevant stakeholders in the higher education sectors were proposed

Understanding Continued Usage Intention in e-Learning Context

With the latest development of the Internet technologies, it has offered many e-learning systems available for the educators to conduct courses online. The advantage of using such systems in connection with on-site courses is that it increases flexibility through resources that facilitate learning anytime anywhere. However, there is little empirical evidence to suggest what factors underpin educators continued usage of such systems. This study builds a model based on the Unified Theory of Acceptance and Use of Technology to identify the factors. The model is tested among the university educators (n = 175) who use a popular e-learning system, Moodle. The results suggest that continuance intention is driven by perceived usefulness and access. Perceived ease of use, perceived behavioral control, compatibility, and social influence do not have significant impact on continuance intention. These core determinants of continuance intention altogether explained around 70% of the total variance of intention

A cross-cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students

This paper examines the social, organisational and individual factors that may affect students' acceptance of e-learning systems in higher education in a cross-cultural context. A questionnaire was developed based on an extended technology acceptance model (TAM). A total sample of 1173 university students from two private universities in Lebanon and one university in England participated in this study. After performing the satisfactory reliability and validity checks, the hypothesised model was estimated using structural equation modeling. The findings of this study revealed that perceived usefulness (PU), perceived ease of use (PEOU), social norms (SNs), perceived quality of work life (QWL), computer self-efficacy (SE) and facilitating conditions (FC) are significant determinants of behavioural intentions (BIs) and usage of e-learning system for the Lebanese and British students. QWL, the newly added variable, was found the most important construct in explaining the causal process in the model for both samples. Differences were found between Lebanese and British students with regard to PEOU, SN, QWL, FC, SE and actual usage; however, no differences were detected in terms of PU and BI. Overall, the proposed model achieves acceptable fit and explains for 69% of the British sample and 57% of the Lebanese sample of its variance which is higher than that of the original TAM. Our findings suggest that individual, social and organisational factors are important to consider in explaining students' BI and usage of e-learning environments

Extending the Technology Acceptance Model to Understand Students’ Use of Learning Management Systems in Saudi Higher Education

Although learning management systems (LMS) have been widely adopted by higher educational institutions in many countries, they are considered an emerging technology in Saudi Arabia. Furthermore, research has demonstrated that the students’ use of them is not always satisfactory. This quantitative study investigated the factors that affect the students use of LMS in higher education by extending the technology acceptance model (TAM) and adapting eight external variables. Based on the probability multi-stage cluster sampling technique, online surveys were sent by email to 2000 students registered in three public universities in Saudi Arabia. 851 responses were submitted by participants, and 833 responses were used for data analysis. Using Partial Least Squares Structural Equations Modeling (PLS-SEM), the results revealed that perceived ease of use is affected by six factors (content quality, system navigation, ease of access, system interactivity, instructional assessment and system learnability). The findings confirmed that perceived usefulness has five determinants (content quality, learning support, system interactivity, instructional assessment and perceived ease of use). This research is relevant to researchers, decision makers and e-learning systems designers working to enhance students’ use of e-learning systems in higher education, in particular where there is not yet widespread adoption.Keywords: TAM, technology acceptance, usability, e-learning systems, LMS, Blackboard, PLS-SEM

Evaluating the success of e-learning systems : the case of Moodle LMS at the University of Warwick

E-learning is a direct result of the integration of education and technology, and is increasingly considered as a powerful medium for learning. The undeniable significance of e-learning in education has led to a large growth of e-learning courses and systems offering different types of service. Thus, evaluation of e-learning systems is vital in ensuring successful delivery, effective use, and positive impact on learners. In recent studies, the vast majority of universities report having adopted varieties of e-learning systems and platforms to facilitate the students’ learning process. However, while adopting e-learning systems is useful, it is not an end in itself. In reviewing the literature, studies have revealed many problems with these systems, such as meeting users’ requirements and the suitability of these systems for targeted users. In order to improve the current systems to satisfy users’ needs, it is important to understand the different aspects that influence the quality and success of these systems. Hence, a new model for evaluating the success of e-learning systems is introduced in this research. Based on an intensive review of the literature, four approaches were identified and analysed as a theoretical basis for the research: DeLone and McLean’s information systems success model; the Technology Acceptance Model; the User Satisfaction Models; and the E-learning Quality Models. In order to provide a general comprehensive definition of e-learning success measurements, the four approaches found in the literature were considered in developing our model. The proposed model includes eleven constructs: technical system quality; information quality; service quality; educational system quality; support system quality; learner quality; instructor quality; perceived satisfaction; perceived usefulness; system use; and benefits. The model is comprehensive, and not based on the number of constructs, but on the intention to provide a holistic picture and different levels of success related to a broad range of success determinants, rather than focusing on a specific construct. As such, it forms an original contribution to knowledge. To test the model, an empirical study was conducted. First, an instrument was designed to assess the perceptions of students towards e-learning system success. Second, an expert study with 30 e-learning experts was carried out to confirm the measurements and indicators. The model was then tested in the context of the University of Warwick by fitting the model to data collected from 563 students engaged with an e-learning system. Both quantitative and qualitative data were analysed. The results confirm that the model proposed in this study is valid and reliable. Thus, the study contributes to the growing body of knowledge with a valid and reliable model and an instrument to evaluate e-learning systems success (EESS model). Further, the study sheds light on important issues and recommendations that should be taken into consideration to improve the perceptions of satisfaction, usefulness, use, and benefits of the e-learning systems. The study further provides practitioners with several practical contributions

The effects of individual-level culture and demographic characteristics on e-learning acceptance in Lebanon and England: A structural equation modeling approach

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityDue to the rapid growth of Internet technology, universities and higher educational institutions around the world are investing heavily in web-based learning systems to support their traditional teaching and to improve their students’ learning experience and performance. However, the success of an e-learning system depends on the understanding of certain antecedent factors that influence the students’ acceptance and usage of such e-learning systems. Previous research indicates that technology acceptance models and theories may not be applicable to all cultures as most of them have been developed in the context of developed countries and particularly in the U.S. So far little research has investigated the important role that social, cultural, organizational and individual factors may play in the use and adoption of the e-learning systems in the context of developing countries and more specifically there is almost absence of this type of research in Lebanon. This study aims to fill this gap by developing and testing an amalgamated conceptual framework based on Technology Acceptance Model (TAM) and other models from social psychology, such as Unified Theory of Acceptance and Use of Technology (UTAUT) and TAM2 that captures the salient factors influencing the user adoption and acceptance of web-based learning systems. This framework has been applied to the study of higher educational institutions in the context of developing as well as developed countries (e.g. Lebanon and UK). Additionally, the framework investigates the moderating effect of Hofstede’s four cultural dimensions at the individual level and a set of individual differences on the key determinants that affect the behavioural intention to use e-learning. A total of 1197 questionnaires were received from students who were using web-based learning systems at higher educational institutions in Lebanon and the UK with opposite scores on cultural dimensions. Confirmatory Factor Analysis (CFA) was used to perform reliability and validity checks, and Structural Equation Modeling (SEM) in conjunction with multi-group analysis method was used to test the hypothesized conceptual model. As hypothesized, the findings of this study revealed that perceived usefulness (PU), perceived ease of use (PEOU), subjective norms (SN), perceived quality of work Life (QWL), self-efficacy (SE) and facilitating conditions (FC) to be significant determinants of behavioural intentions and usage of e-learning system for the Lebanese and British students. QWL; the newly added variable; was found the most important factor in explaining the causal process in the model for both samples. Our findings proved that there are differences between Lebanese and British students in terms of PEOU, SE, SN, QWL, FC and AU; however no differences were detected in terms of PU and BI. The results of the MGA show that cultural dimensions as well as demographic factors had a partially moderated effect on user acceptance of e-learning. Overall, the proposed model achieves acceptable fit and explains for 68% of the British sample and 57% of the Lebanese sample of its variance which is higher than that of the original TAM. Our findings suggest that individual, social, cultural and organisational factors are important to consider in explaining students’ behavioural intention and usage of e-learning environments. The findings of this research contribute to the literature by validating and supporting the applicability of our extended TAM in the Lebanese and British contexts and provide several prominent implications to both theory and practice on the individual, organizational and societal levels.Altajir Trus

Factors influencing students' acceptance of m-learning: An investigation in higher education

M-learning will play an increasingly significant role in the development of teaching and learning methods for higher education. However, the successful implementation of m-learning in higher education will be based on users' acceptance of this technology. Thus, the purpose of this paper is to study the factors that affect university students' intentions to accept m-learning. Based on the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors that influence the acceptance of m-learning in higher education and to investigate if prior experience of mobile devices affects the acceptance of m-learning. A structural equation model was used to analyse the data collected from 174 participants. The results indicate that performance expectancy, effort expectancy, influence of lecturers, quality of service, and personal innovativeness were all significant factors that affect behavioural intention to use m-learning. Prior experience of mobile devices was also found to moderate the effect of these constructs on behavioural intention. The results of this research extend the UTAUT in the context of m-learning acceptance by adding quality of service and personal innovativeness to the structure of UTAUT and provide practitioners and educators with useful guidelines for designing a successful m-learning system