Mahmoud Maqableh

The impact of knowledge management on job performance in higher education: The case of the University of Jordan

This is an empirical study of knowledge management performance (KMP) at a university and the purpose of this paper is to examine the relationship between knowledge management process (KMPR), KMP and job performance (JP).,The data were collected using a questionnaire, as the instrument for the primary data collection, with total collected back responses of 207 from university lecturers who have actually participated. Structural equation modeling technique was used to fully analyze the data in order to determine what level of the relationship between knowledge management (KM) and JP existed.,The main findings were related to confirming the two main hypotheses of the research that were related to testing if there were relationships between the KMPR (represented by seven surrogate measures, namely, knowledge identification, knowledge creation, knowledge collection, knowledge organizing, knowledge storage, knowledge dissemination and knowledge application) and KMP, as well as if the KMP was related to the JP.,This paper focuses on investigating the actual role of KM at a university, which is assumingly a knowledge factory. Contrary to the conventional wisdom that presumes the importance of KM and specially when there is no proper KM regiment in place, the paper reports the limited influence KM has on staff JP. It is one of the few studies that fills the gap in the literature concerned with the relationship between KM and JP and perhaps the first to provide insights about the KM intricacies at a Jordanian University.

Factors influencing students’ adoption of e-learning: a structural equation modeling approach

Purpose This research aims to examine the factors that may hinder or enable the adoption of e-learning systems by university students. Design/methodology/approach A conceptual framework was developed through extending the unified theory of acceptance and use of technology (performance expectancy, effort expectancy, hedonic motivation, habit, social influence, price value and facilitating conditions) by incorporating two additional factors, namely, trust and self-efficacy. Data were collected from students at two universities in England using a cross-sectional questionnaire survey between January and March 2015. Findings The results showed that behavioral intention (BI) was significantly influenced by performance expectancy, social influence, habit, hedonic motivation, self-efficacy, effort expectancy and trust, in their order of influencing the strength and explained 70.6 per cent of the variance in behavioral intention. Contrary to expectations, facilitating conditions and price value did not have an influence on behavioral intention. Originality/value The aforementioned factors are considered critical in explaining technology adoption but, to the best of the authors’ knowledge, there has been no study in which all these factors were modeled together. Therefore, this study will contribute to the literature related to social networking adoption by integrating all these variables and the first to be tested in the UK universities.

Social media networks and pedagogy at the University of Jordan

This study examined impact of a social media networks course on student use of SNSs performance. Moreover, it examined the associations among course design, course materials, learning experiences and a social media networks course. Survey instrument is used to examine the relationships in the proposed model. A total of 380 questionnaires have been collected from students at the University of Jordan who studied the social media networks course. A structural equation modelling approach based on AMOS 20.0 statistical software is used to study the causal relationships and test the hypotheses between the observed and latent constructs in the proposed research model. The analysis results revealed that course materials and learning experiences directly, positively and significantly impacted the social media networks course, which in turn had a significant impact on students’ use social networks sites performance. Course design, however, did not impact the social media networks course. Our findings have important implications as we demonstrated the validity of the joint two different models and provide information about impact of studying social media networks course on students’ academic performance.