Design and evaluation of e-learning knowledge management model for Iran's higher education system

Purpose:

Universities and higher education institutions are knowledge-oriented organizations and are recognized for carrying out scientific affairs. In this regard, knowledge is the main factor in the creation of higher education institutions and also its final product, and the correct management of knowledge can act as a strategic tool for higher education to achieve its advantages. Maintain and gain competitiveness. The effort to apply knowledge management in higher education shows the efforts of the academic community to strengthen intellectual capital and improve the effectiveness of universities in the progress and improvement of the country, and the implementation of knowledge management processes in organizations requires attention and design of a model that is compatible with the specific conditions and contexts of that organization. . Universities, as the main educational and knowledge-based institutions, play a fundamental role in the development and transfer of knowledge in society. By implementing e-learning knowledge management, they can increase their achievements and improve the effectiveness of scientific and educational activities while improving educational quality. These processes can help universities organize existing knowledge more efficiently and create opportunities for sustainable learning and better access to educational resources. Therefore, the purpose of this research is to design a suitable conceptual model for knowledge management of e-learning in higher education.

Method: This applied research was conducted using a survey method. The statistical population consisted of experts and faculty members in the fields of knowledge management and e-learning in universities. A total of 380 participants were selected through simple random sampling, and a researcher-made questionnaire was used for data collection. Data analysis and model fitness assessment were performed using confirmatory structural equation modeling (SEM) with the Smart PLS software.



Findings: The validation of the e-learning knowledge management model showed that all relationships in the model are significant at a 95% confidence level, with factor loadings having t-values above 1.96. The reliability of the questionnaires was confirmed using Cronbach's alpha and Average Variance Extracted (AVE), with AVE values above 0.50 and Cronbach's alpha above 0.70. The results indicate a positive and significant correlation among all research variables, confirming the strength of relationships within the model. Divergent validity assessment of the model also showed that the square root of the AVE for each variable is greater than its correlation with other main variables, confirming the model’s divergent validity. Overall, the results demonstrated that the model has an adequate fit to the data. In summary, the e-learning knowledge management model comprises 7 main processes and 21 mechanisms as a reference framework for higher education.



Conclusion: The final e-learning knowledge management model consists of seven key processes: knowledge selection, knowledge sharing, knowledge creation, knowledge organization, knowledge application and utilization, knowledge acquisition, and knowledge evaluation and auditing. The knowledge creation process includes mechanisms for knowledge discovery, identification, and retrieval; the sharing process includes mechanisms for knowledge presentation, dissemination, and training; the creation process involves mechanisms such as knowledge extraction, fusion, and gathering; the organization process includes knowledge representation, visualization, and storage mechanisms; the application and utilization process includes mechanisms for use, reuse, and improvement; the acquisition process includes mechanisms for knowledge exchange and research; and the evaluation and auditing process involves components for analyzing knowledge needs, knowledge inventory, knowledge network analysis, social network analysis, and knowledge validation. Since all these processes are essential, they should be integrated in knowledge management with necessary planning and strategies. Furthermore, universities and higher education institutions should maintain a balance among these processes according to their position.

These results can serve as a foundation for strategic knowledge management design in universities and higher education institutions. The proposed model in this study can be used as a roadmap for knowledge management in e-learning within universities and higher education institutions.