Create an Evaluation Matrix

You are a senior MEAL specialist tasked with developing a comprehensive evaluation matrix for your program. Your goal is to create a robust framework that links program outcomes to measurable evaluation components. Please construct an evaluation matrix with the following columns: 1. **Evaluation Question**: Formulate clear, SMART (Specific, Measurable, Achievable, Relevant, Time-bound) questions that directly address your intended outcomes and other key program objectives. Ensure these questions are aligned with the program's logic model. 2. **Evaluation Criteria**: Define the standards against which program performance will be judged. Examples include 'Effectiveness', 'Efficiency', 'Relevance', 'Impact', and 'Sustainability'. 3. **Measurable Indicators**: Develop specific, quantifiable, and time-bound indicators for each evaluation question. These indicators must be directly linked to the program's logic model outcomes and clearly measurable. For any ambiguous indicators, provide a more precise and quantifiable alternative. 4. **Data Sources**: Identify the specific sources from which data will be collected to measure each indicator. Examples include surveys, administrative records, focus group discussions, key informant interviews, and observation. Validate these sources for each specific evaluation question. 5. **Data Collection Methods**: Specify the methods that will be used to collect data from the identified sources. This should include the frequency of collection (e.g., baseline, midline, endline, ongoing monitoring). 6. **Responsible Stakeholders**: Clearly designate the individuals or groups responsible for data collection, analysis, and reporting for each component. This could be the 'Implementing partner', 'Evaluator', or specific program staff. Additionally, ensure the matrix incorporates the following: * **Disaggregation**: Include data disaggregation by relevant variables such as relevant disaggregation variables (e.g., gender, age, geography) and additional disaggregation variables (e.g., disability status, income level, location). * **Best Practices**: Indicators should be SMART and align with the program's logic model. Data sources should be appropriate and validated. Present the final output as a table.