Monitoring and Evaluation

Topics Covered:

• •Definitions, purposes, and key principles
• •Results-based management (RBM) cycle
• •OECD-DAC evaluation criteria

Practical Exercises:

Topics Covered:

• •Problem analysis and results chains
• •Assumptions and risks
• •Creating a Logical Framework Matrix

Practical Exercises:

• ✓Develop a sample Theory of Change

Topics Covered:

• •Types of indicators (input, output, outcome, impact)
• •SMART criteria and indicator quality
• •Setting baselines and targets

Practical Exercises:

• ✓Design SMART indicators for a sample project

Topics Covered:

• •M&E matrix, calendar, and responsibilities
• •Resource budgeting
• •Data Quality Assurance (DQA) components

Practical Exercises:

• ✓Create an M&E plan for a sample project

Topics Covered:

• •Qualitative & quantitative tools (FGDs, KIIs, surveys)
• •Sampling methods and ethics
• •Mobile data tools (KoboToolbox, ODK)

Practical Exercises:

• ✓Design a data collection tool using KoboToolbox

Topics Covered:

• •Data cleaning and coding
• •Statistical summaries and charts
• •Qualitative thematic analysis
• •Basic dashboarding in Excel/Power BI

Practical Exercises:

• ✓Create a dashboard using Excel or Power BI

Topics Covered:

• •Types of evaluations (formative, summative)
• •Experimental and mixed-methods approaches
• •Choosing appropriate evaluation designs

Practical Exercises:

• ✓Develop an evaluation design for a sample project

Topics Covered:

• •Writing Terms of Reference (TORs)
• •Selecting evaluators and QA of deliverables
• •Budgeting and scheduling

Practical Exercises:

• ✓Draft a Terms of Reference for an evaluation

Topics Covered:

• •After-action reviews and learning loops
• •Storytelling with data
• •Writing evaluation briefs

Practical Exercises:

• ✓Write a sample evaluation brief

Topics Covered:

• •Complexity-aware M&E (Outcome Harvesting, MSC)
• •Adaptive management and agile frameworks
• •Tools (DHIS2, CommCare, Power BI)

Practical Exercises:

• ✓Apply Outcome Harvesting to a case study