A Content Analysis of Elementary Textbooks Based on Attention to the Knowledge Management Concepts

Document Type : Original Article

Authors

1 Associate Professor, Department of Knowledge and Information Science, University of Qom, Qom, Iran

2 M.A. Science, Department of Knowledge and Information Science, University of Qom, Qom, Iran

10.22091/jrim.2024.10836.1076

Abstract

The aim of this study was to analyze the content of elementary school textbooks in terms of the extent to which knowledge management concepts are addressed. This research was quantitative in approach and applied in purpose. The research community included all analyzed textbooks, from which 3,669 components were identified. Content analysis was used for this research; the unit of analysis was pages (text, exercises, images, footnotes), which were reviewed through studies, images, exercises, and activities. Initially, the identified concepts were categorized into six components of the knowledge management building model: knowledge recognition, knowledge acquisition, knowledge development, knowledge distribution, knowledge utilization, and knowledge preservation. Data collection tools included a researcher-made checklist. Subsequently, the collected data were analyzed using Excel software and descriptive statistical indices in the Shannon Entropy analytical process. The results showed that the knowledge recognition component had the highest frequency, while the knowledge preservation component had the lowest one. Additionally, among the textbooks, the science textbook paid more attention to knowledge management concepts in comparison to other textbooks. Among the knowledge management concepts, normalized data by textbooks showed the highest importance coefficient for the knowledge acquisition component; by grade, the knowledge distribution component had the highest importance coefficient; and overall, the knowledge recognition component ranked third based on both textbooks and grades.

Keywords

References

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Journal of research in instructional methods
Volume 2, Issue 2 - Serial Number 6
September 2024
Pages 105-121

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History

  • Receive Date: 05 June 2024
  • Revise Date: 15 September 2024
  • Accept Date: 20 September 2024

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