Course description
Agriculture forms the backbone of many developing countries and is the main economic activity for rural communities. Since its modest beginnings, the agricultural sector has become increasingly complex and multi-faceted.
The challenge agriculture faces today is how to feed the world population in an equitable manner while protecting the environment from irreversible negative changes.Monitoring and Evaluation tools and techniques play a key role in ensuring Agriculture and Rural Development (ARD) projects are designed and implemented as planned to aid in ending hunger and poverty.
Monitoringand Evaluation for Agriculture and Rural Development Course equipthe participants with adequate skills to develop and manage robust M&E systems to effectively manage ARD projects and programs. The learner is introduced to M&E frameworks indicators, tools and techniques for M&E for ARD.
Upcoming start dates
Suitability - Who should attend?
Monitoring and Evaluation for Agriculture and Rural Development Training course isdesigned for:
- Project staff, development practitioners,
- Managers and decision-makers are responsible for the project,
- Program or organization-level M&E in Agriculture and Rural Development programs.
Outcome / Qualification etc.
By the end of this monitoringand Evaluation for Agriculture and Rural Development course, the participants will be able to:
- Understand monitoring and evaluation (M&E) for ARD programs
- Design ARD projects using a logical framework analysis approach
- Define different ARD indicators
- Track performance indicators over the life of the project
- Evaluate ARD programs against objectives and targets
- Understand gender roles in M&E in ARD programs
- Conduct impact evaluations of ARD programs
Training Course Content
Day 1
Introduction to monitoring and evaluation
- Definition of Monitoring and Evaluation
- Why Monitoring and Evaluation are important
- Key principles and concepts in M&E
- M&E in project lifecycle
- Complementary roles of Monitoring and Evaluation
Agriculture and Rural Development Policy issues
- Sustainable agriculture and rural development
- Economic contribution of agriculture
- Link between agriculture and rural development
- Agriculture and food security
Day 2
M&E Frameworks in Agriculture and Rural Development
- ARD Conceptual Frameworks
- ARD Results Frameworks
- Logical Framework Analysis (LFA)
- LogFrame - Design of ARD projects using LogFrame
Day 3
Agriculture and Rural Development Indicators
- Indicator metrics
- Linking indicators to results
- Indicator Matrix
- ARD indicator performance tracking
- Sector-wide indicators for Agriculture and Rural Development
- Specific indicators for Sub-sectors of Agriculture and Rural Development
- Indicators for Thematic Areas related to Agriculture and Rural Development
Day 4
M&E System and M&E Planning in ARD
- Importance of an M&E Plan
- Documenting M&E System in the M&E Plan
- Components of an M&E Plan-Monitoring, Evaluation, Data management, Reporting
- Using M&E Plan to implement M&E in a Project
Data Management for M&E in Agriculture and Rural Development
- Sources of Data: Information systems, surveys, participatory poverty assessments, financial management tools
- Use of different Surveys in data collection for ARD
- Participatory methods of data collection for ARD
- Data analysis for ARD
Gender integration in M&E for Agriculture and Rural Development
- Gender integration during project activities design
- Gender indicators in ARD
- Cross cutting gender issues in ARD
- Measure of gender outcomes
Day 5
Performance Evaluation of Agricultural and Rural Development programs
- Determining evaluation points from the results framework
- Components of evaluations: implementation and process evaluations.
- Evaluation designs- experimental, quasi-experimental and non-experimental
- Performance evaluation process
- Evaluation questions
- Evaluation findings sharing and dissemination
Impact Evaluations for Agriculture and Rural Development
- Introduction to impact evaluation
- Attribution in impact evaluation
- Estimation of counterfactual
- Impact evaluation methods: Double difference, Propensity score matching
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