E-Learning and gender

This study is to examine gender differences and the adoption of technology in tertial education students. We have used TAM model to measure the acceptance and use of elearning of the respondents. ANOVA and Partial Least Squares (PLS) was used, specifically, the PLS multi-group analysis, to compare differences between groups. In summary, results show that students’ behavior of acceptance of e-learning technology do not manifest statistically significant differences between women and men

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

The Effect of Self Identity and Social Identity on Technology Acceptance

While the effect of social factors on information technology (IT) acceptance behavior has been recognized as an important issue, only a few studies examined this topic in the context of the technology acceptance model. In this study, we incorporate two social factors, self identity and social identity, in the model and address their impacts on IT acceptance decision. An empirical study investigating the impact these social factors have on the acceptance of a web-based class support system is in progress. Upon completion of this study, we expect to provide further understanding on the role of social influence on individual technology acceptance decisions

User acceptance of open enterprise solution: the OSS-ERP case

Organizations implement Enterprise Resource Planning (ERP) systems with the objective of reaching operational efficiency and the incorporation to new markets through the information flow control on time of the entire organization. However, ERP systems are complex tools, mainly for the small and medium size enterprises (SMEs). For these reason, new ERP configurations have arisen for SMEs such as Open Source Software-ERP (OSS-ERP). OSS-ERP is a research topic barely analyzed by the literature. Specifically, this paper’s aim is to focus on the OSS-ERP users’ acceptance and use. The authors have developed a research model based on the Technology Acceptance Model (TAM) for testing the users’ behavior toward OSS-ERP.Las organizaciones implantan Sistemas Integrados de Gestión (ERP, acrónimo de Enterprise Resource Planning) con el objetivo de alcanzar eficiencias operativas y la incorporación a nuevos mercados mediante un mayor control del flujo de información de toda la empresa a tiempo real. Sin embargo, los sistemas ERP son herramientas complejas, principalmente la pequeña y mediana empresa (PYME). Por esta razón, están surgiendo nuevas configuraciones de sistemas ERP para PYME como los sistemas ERP de código abierto (OSS-ERP). OSS-ERP es un tópico de investigación escasamente analizado en la literatura. Concretamente, este artículo se centra en el y aceptación de los usuarios a los sistemas OSS-ERP. Los autores han desarrollado un modelo de investigación basado en Metamodelo de Aceptación de la Tecnología (TAM) para testar el comportamiento de los usuarios hacia los sistemas OSS-ERP

Students' decisions to use an eLearning system: a structural equation modelling analysis

This research investigates and identifies some of the major factors affecting studentsâ?? adoption of an e-learning system at Arab Open University in Jordan. E-learning adoption is approached from the information systems acceptance point of view. An extended version of the Technology Acceptance Model (TAM) was developed to investigate the underlying factors that influence studentsâ?? decisions to use an e-learning system. The proposed model uses the actual use of an e-learning system. It is different from most of the prior TAM studies, which only used a single dependent variable (intention to use). The model was estimated using Structural Equation Modelling (SEM). The final models derived from this study indicated that beliefs of usefulness and ease of use partially mediate the relationship between external factors and intention to use and actual use of e-learning systems

Conceptualizing task-technology fit and the effect on adoption – A case study of a digital textbook service

Although information technology has revolutionized virtually every aspect of how we interact with products and services, it has changed learning to a surprisingly small degree. In a study of a digital textbook service, we provide a new conceptual definition and measurement of technology fit. We conceptualize task-technology fit as how well a technology is integrated with a set of interrelated tasks included in achieving the goal of the behavior where the technology is used. Whereas research on technology adoption typically explains around 40 percent of the variance in motivation to adopt, our model explains as much as 76 percent.acceptedVersio

Looking under the bonnet:factors affecting student adoption of e-learning systems in Jordan

The primary questions addressed in this paper are the following: what are the factors that affect students’ adoption of an e-learning system and what are the relationships among these factors? This paper investigates and identifies some of the major factors affecting students’ adoption of an e-learning system in a university in Jordan. E-learning adoption is approached from the information systems acceptance point of view. This suggests that a prior condition for learning effectively using e-learning systems is that students must actually use them. Thus, a greater knowledge of the factors that affect IT adoption and their interrelationships is a pre-cursor to a better understanding of student acceptance of e-learning systems. In turn, this will help and guide those who develop, implement, and deliver e-learning systems. In this study, an extended version of the Technology Acceptance Model (TAM) was developed to investigate the underlying factors that influence students’ decisions to use an e-learning system. The TAM was populated using data gathered from a survey of 486 undergraduate students using the Moodle based e-learning system at the Arab Open University. The model was estimated using Structural Equation Modelling (SEM). A path model was developed to analyze the relationships between the factors to explain students’ adoption of the e-learning system. Whilst findings support existing literature about prior experience affecting perceptions, they also point to surprising group effects, which may merit future exploration

Gender influence in perception and adoption of e-learning platforms

The main objective of this study is to examine gender differences and the adoption of technology in higher education students. TAM model is the tool used to measure the acceptance and use of e-learning of the respondents. We used Partial Least Squares (PLS), specifically, the PLS multi-group analysis was used to compare differences between groups. In summary, results show that students’ behavior of acceptance of elearning technology do not manifest statistically significant differences between women and men

Extending The Technology Acceptance Model Using Perceived User Resources In Higher Education Web-based Online Learning Courses

The purpose of this research was to examine students\u27 acceptance of the World Wide Web Course Tools (WebCT) online learning system. The Perceived Resources and Technology Acceptance Model (PRATAM) was created based on previous research to address the factors of perceived resources, perceived usefulness, perceived ease of use, attitude toward using, behavioral intention to use and actual system use. The aim for this research was to investigate the critical determinants and provide the causal relationships regarding students\u27 acceptance behaviors when using WebCT. While institutions are expecting to adopt online learning to reach more students, there are still many challenges for institutions to retain students in their online courses. The literature review conducted in this research indicated that the Technology Acceptance Model (TAM) has successfully explained students\u27 behaviors when they use educational information systems. In addition, the additional perceived resources variable in the PRATAM also showed a significant influence on the other belief and intention variables. The study analyzed a total of 115 students responses in two surveys administered during two WebCT based courses taught at a large southeastern public university. The beliefs, attitudes, intentions, and behavioral constructs of PRATAM showed significant goodness-of-fit indices and coefficient of determination after analyzing the data in both surveys. However, the results indicated several exceptions on PRATAM\u27s constructs and causal relationships. First, the path coefficient between perceived resources to behavioral intention to use in both pre-test and post-test were insignificant. Second, the path coefficient between behavioral intention to use and actual system use in pre-test was insignificant. Third, the path coefficient between perceived resources and perceived usefulness in post-test were insignificant. In addition, the research also suggested an additional link between perceived ease of use and behavioral intention to use at the pre-test data. Overall, this research validated the influences of PRATAM\u27s constructs factors to students\u27 acceptance behaviors toward WebCT. The findings of this research could provide a guideline for future implementations of online learning systems in higher education

Factors Influencing the Adoption of Mobile Learning

Education delivery by mobile devices enables anywhere / anytime learning. Mobile learning has the potential to allow students to more closely integrate learning activities into their busy lives. At this early stage in its development, this is an opportune time to initiate a stream of research that examines the adoption of m-learning applications. This study determines the key factors influencing the behavioural intention for adoption of mobile learning. Several external variables are incorporated into the Technology Acceptance Model and tested in six New Zealand universities. Six of the seven variables – self-efficacy, perceived usefulness, subjective norm, attitude, perceived ease of use, and perceived financial resources were accepted. Prior use of e-learning was not accepted and reasons for this are explored in the study