Eexplanation of Dimensions, components of appropriate core Training in police (Case Study: force of police Islamic Republic of Iran)
Subject Areas : Educational Science
Seyyed Hasan Khalili Hoseinabadi
1
(PhD student in curriculums, department of educational sciences,, Isfahan (khorasgan) Branch, Islamic Azad university, Isfahan, Iran)
Zohreh Saadatmand
2
(department of educational sciences,, Isfahan (khorasgan) Branch, Islamic Azad university, Isfahan, Iran)
Narges Keshtiaray
3
(Associate Prof. Educational sciences, Isfahan (Khorasgan) Branch.Islamic Azad University , Isfahan, Iran)
Keywords: Validation, Training, merit-based police,
Abstract :
The current research has been done to validate and explain indexes of merit-based police training. The used method was combined qualitative-quantitative. In the first stage upstream documents such as statements of supreme leader of I.R. Iran, strategic plan of NAJA, training script of NAJA, collector training system of NAJA, recruitment laws of NAJA, constitution law, instructions and circulars and measures made by the NAJA chief were analyzed using the qualitative content analysis of inductive category method. The sampling method in the qualitative section was purposive and research-based. The analysis method of the first stage was subject coding including the three “open”, “Axial” and “selective” areas. Based on the findings of the first stage of research and after coordinating concept codes, 27 subcategories and 7 main categories was extracted which included thought-based and value-based merits with 3 components, perceptual merits with 2 components, self-management merits with 4 components, excellence in organizational behavior merits with 5 components, personality merits with 4 components, communicational merits with 2 components and proficiency merits with 8 components. In the second stage the CVR method (content validity ratio) was used for validation. Components and indexes extracted from first stage was given to 15 specialists and experts in the format of a questionnaire and indexes higher than 0.49 was chosen and extracted.
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