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Content Analysis Of National Documents On Scientific Cooperation And Interactions Between Faculty Members In Agricultural Higher Education System
[Full Text]
AUTHOR(S)
Mahshid Bahadori, Enayat Abbasi, Hassan Sadighi, Saeed Gholamrezaei
KEYWORDS
Interactions, Scientific Collaboration, National and Certain Documents, Content Analysis, Agricultural Higher Education System.
ABSTRACT
Scientific interactions and cooperation are considered as the main components in the production of science; interaction and communication between professors are also considered as the most important areas of communication in higher education. Therefore, the level of interactions, communications, and collaborative activities plays a key role in the professional development of faculty members. The purpose of this research is to answer this fundamental question which should be considered on the basis of the transactional and National and Certain Documents for the formulation of the components of scientific cooperation and interaction between faculty members. This research is a descriptive analysis in terms of nature in which content analysis and documentary analysis are used. The population of the study includes the extra and determined documents out of which five documents are sampled by purposive sampling. Phishing, checklist and researcher forms have been the tools for data collection required for research. Descriptive analysis has been used to interpret and analyze the data. The categories of education, research and outsourcing services are classified based on the findings of the research, and ultimately these components were extracted, which include international participation, collaborative research interactions and multidisciplinary interactions in research category, joint courses and joint international interactions in the field of training and team interaction, international engagement and technological interactions in the field of outsourcing services. Accordingly, professional inputs and collaborations among faculty members will be highly valued if the inference components are taken into consideration.
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