INFLUENCE OF MONITORING AND EVALUATION ON IMPLEMENTATION OF CLIMATE SMART AGRICULTURE PROJECTS IN NYANDO SUB-COUNTY
Rose Chemtai Manyu - Master of Science in Project Management, College of Human Resource Development, Jomo Kenyatta University of Agriculture and Technology, Kenya
Dr. Kinyanjui Ng’ang’a - Lecturer, Jomo Kenyatta University of Agriculture and Technology, Kenya
Dr. Assumpta Kagiri - Lecturer, Jomo Kenyatta University of Agriculture and Technology, Kenya
ABSTRACT
This study sought to determine the influence of monitoring and evaluation on implementation of climate smart agriculture projects in Nyando sub-county. In the Nyando Basin, climate change and variability are already evident. In response to these challenges, the CGIAR Research Program on Climate Change Agriculture and Food Security (CCAFS) has contributed specific interventions which unfortunately have not benefited the intended beneficiaries. A study done indicates that the project has not been successful due to lack of active participation by the organized community groups and challenges with proper record keeping resulting in cost overruns leading to delays in launching the project at a wider scale. The independent factors that were examined include the influence of participatory monitoring and evaluation system, monitoring and evaluation tools, monitoring and evaluation project team and monitoring and evaluation project funding on implementation of climate smart agriculture projects in Nyando sub-county. In the literature review, three theories namely Expectancy Disconfirmation Theory, Program Theory and Theory of Change were examined. The study was grounded on Theory of Change. A conceptual framework has been examined to demonstrate the relationship between the independent variables which are participatory monitoring and evaluation system, monitoring and evaluation tools, monitoring and evaluation project team and monitoring and evaluation project funding and the dependent variable which is the implementation of climate smart agriculture projects. The empirical review section looked at relevant studies done by other researchers. A critique of these studies was done and the existing research gaps identified. Descriptive research design was used to sample 35 respondents from a target population of 112 employees who were selected using purposive sampling technique. A pilot study was done to test the reliability and validity of the research instrument. The data was collected using structured questionnaires and the analysis was done by using descriptive statistics specifically calculating the arithmetic mean and standard deviation and presented using tables. Statistical software SPSS V 22.0 was used for statistical analysis. The results indicate that the implementation of climate smart agriculture projects in Nyando sub-county was fairly successful at 56.3%. The study also established that participatory monitoring and evaluation system, monitoring and evaluation tools, monitoring and evaluation project team and monitoring and evaluation project funding had an influence on implementation of climate smart agriculture projects in Nyando sub-county to varying degrees with mean scores of 3.46,3.55,3.53 and 3.53 respectively. Since the study focused on climate smart agricultural projects in Nyando Sub-county only, further studies should be carried out in other donor funded projects located in different regions in order to generalize the findings of this study. Similarly, since the study was limited in terms of the number of factors that were examined, future studies should examine other M&E factors that have the potential of affecting implementation of projects in Kenya.
