International Journal of Knowledge Processing Studies

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Designing and Fitting the Knowledge-Enhancing Model in Effective Teaching with knowledge Management Aproach

Document Type : Original Research Manuscripts

Authors

1 Ph.D. candidate of Educational Management, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.

2 Department of Educationa Management, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

Abstract

The current research aimed to design and fit the knowledge-enhancing model of effective teaching. knowledge-enhancing in teaching, as a condition of "life, durability and survival", displays the dynamic spirit of education and is created in three pyramid heads (students, parents, and teachers). The research method is mixed and practical in nature. The statistical population includes all teachers working in the education ministry in Fars province. The sample size of 18 people sample selection was determined in the qualitative section by the purposeful sampling method. Quantitative sampling was obtained according to Cochran's formula of 376 people. The data collection tool, in the qualitative part, included two parts, a semi-structured interview and review of upstream documents, and in the quantitative part, a researcher-made questionnaire tool. Data analysis in the qualitative section was based on thematic analysis in ATLAS TI software. Structural equation modeling was used in SMARTPLS software to fit the model. The obtained findings led to the identification of 3 dimensions, 10 components, and 176 indicators, and finally, the research model was presented. The results showed that each of the dimensions, respectively: teaching and evaluation, scientific-educational (/66), and individual (/57) affected effective teaching in elementary school. Students learn by connecting new knowledge with existing knowledge and concepts, constructing new meanings. Knowledge-based education emphasizes primary education on deep and powerful teaching and learning from shared knowledge.

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References
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International Journal of Knowledge Processing Studies
Volume 4, Issue 1
December 2023
Pages 52-64
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History
  • Receive Date: 09 April 2023
  • Revise Date: 18 April 2023
  • Accept Date: 21 July 2023
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