e-Learning is a key strategy in the course of higher education to improve the results of the educational process and stimulate student motivation. The COVID-19 pandemic imposed on Algerian universities to adopt e-Learning systems to search for effectiveness and efficiency of academic approaches. This paper seeks to remedy these problems by analyzing the impact of e-Learning systems on student motivation and outcomes. A mixed-method approach was used in the data analysis. We conducted the study as a survey, with data being gathered via questionnaires distributed to 398 students. The questionnaire includes open questions that were qualitatively analyzed using content analysis with Nvivo, besides Likert scale questions were quantitatively analyzed and modeled using Structural equation modeling (SEM) with Amos to accomplish the path analysis of the research model. The results of the study showed that student motivation (Attention, Relevance, Confidence, and Satisfaction) and student outcomes (knowledge, skills, and attitudes) are significantly affected by e-Learning systems (Technical and electronic requirements, personal requirements, perceived value, and credibility of e-Learning). The key findings are discussed, and they provide recommendations for future research.
Artificial neural networks are considered one of the work areas of artificial intelligence on the representation of the human spirit through a digital data network (representing the nerve cell) connected balanced links (which represent the links between cells),which are processed by the specified mathematical model. The data are only takes no effect, but if these data are united with the weight they carry in the definition of the task of the neural network. Where he became one of the most important methods used in contemporary organizations, and the method used to control risks and their impact on the performance of the organization, it has increased interest for them, especially with open markets and increased competition and increased rapidly changing environment, current affairs, hence the multiplicity of sources of risk to follow up is required for each Foundation seeks to stay and continue on themarket.
This study investigated the relationship between organizational culture types according to Competing Values Framework (Clan, Adhocracy, Market, Hierarchy) and Knowledge Management Processes (Creation, Dissemination, Storage, Application) using meta-analytic path analysis. To produce the necessary pooled correlation matrix for model testing, we used the univariate (r) approach to carry out two additional meta-analyzes. Based on data collected from several research databases, we extracted the paired correlation coefficients (r) among knowledge management processes (k = 32, N = 6835) then the inter-correlations between knowledge management processes and culture types (k = 7, N = 865). The findings revealed that no particular culture type has a stronger effect on all KM processes. Clan, Adhocracy and Market have significant but varying effects on Knowledge Management processes. Notably, the clan is more associated with knowledge creation, while Adhocracy has a greater effect on knowledge application, and market has a stronger effect on knowledge dissemination and storage. However, hierarchical culture has an insignificant effect on knowledge creation and the lowest effects on the rest of Knowledge Management processes. Therefore, the study concluded that knowledge management success is determined by developing a balanced portfolio of cultural traits from clan, adhocracy and market cultures.
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