zahra Mohammadi - Management Department, Islamic Azad University, West Tehran Branch, Tehran, Iran
Hadi Rezghi Shirsavar - Department of Management, West Tehran Branch, Islamic Azad University, Tehran, Iran
Mohammad Sadegh Ziaeiy - Department of Management, West Tehran Branch, Islamic Azad University, Tehran, Iran
Shahram Hashemnia - Department of Management, West Tehran Branch, Islamic Azad University, Tehran, Iran

One of the traits of excellent organizations is to effectively use staff that present desirable performance and have engagement towards their organizations while trying to promote their knowledge, skill, and attitude and the other employees to solve issues and problems in working context. The aim of this research is to design an on-The- Job Training(OJT) Model and test it to promote and improve staff s performance among staff of Iran Forensic Medicine Organization (IFMO). This is a cross-sectional study which is done based on descriptive and analytical method. The study population is 2800 people working in IFMO in 2017 among which 338 persons were randomly selected based on Cochran s Formula using multi-stage clustering sampling among 15 selected provinces. Data was gathered via two researcher-structured questionnaires including OJT and performance improvement parameters. Face-related and constructive validity of the questionnaires were approved by elite and experts while using Cronbach s Alpha Coefficient showed an acceptable reliability, respectively 0.89 and 0.87. Some appropriate statistical indices were used to analyze the gathered data including frequency, Mean, SD, Pearson s Correlation Coefficient, and SEM. Findings show that there isa positive significant relationship between OJT s indices including need assessment, aims and priorities, content, planning and implementation, way of evaluation, executive management, facilities and equipment, technology and learners with PI s factors including job performance, individual performance, and organizational performance. Also, findings show that the best predictor is modern technology for PI regarding OJT-based model.

OJT- Based Model, Performance, Improvement, Staff, IFMO