INFLUENCE OF THE INSET EVALUATION MECHANISM ON THE JOB PERFORMANCE OF POLICE OFFICERS IN KENYA
Keywords:
INSET Evaluation Mechanism, Job Performance, Police Officers, National Police Service, KenyaAbstract
This study investigated the influence of in-service training (INSET) evaluation mechanisms on the job performance of police officers in Nairobi City County, Kenya. Anchored on the Context Input Process Product (CIPP) model, the study specifically examined how evaluation processes in INSET programs contribute to enhancing the knowledge, skills, and operational effectiveness of police officers. A mixed-methods approach employing a convergent parallel design was adopted. The target population comprised 3,556 officers and instructors drawn from Embakasi “A” and “B” Campuses of the National Police Service. A sample of 329 respondents was selected using purposive and stratified sampling techniques. Data were collected through semi-structured questionnaires administered to officers and instructors, and interview schedules with 20 key informants. Both validity and reliability tests were undertaken. Quantitative data were analyzed using descriptive statistics and one-way ANOVA, while qualitative data were subjected to thematic analysis. The findings revealed that INSET evaluation mechanisms significantly and positively influence police officers’ job performance by ensuring accountability, measuring training effectiveness, and informing continuous program improvement. The results showed that systematic evaluation fosters the acquisition of relevant competencies, enhances decision-making, strengthens professional conduct, and improves operational outcomes in areas such as community policing, counterterrorism, and cybercrime investigations. The study concludes that evaluation is a critical determinant of the effectiveness of INSET programs in shaping police officers’ performance. It recommends that the National Police Service adopt comprehensive and standardized evaluation frameworks, integrate feedback mechanisms into training cycles, and use evaluation data to guide policy and resource allocation for sustained improvements in job performance.
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Copyright (c) 2025 Grace Wangui Kamau , Dr. Peter Nyaga , Dr. Florence Itegi (Author)

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