Module 1: Fundamentals of MEAL and Data Ecosystem

• Introduction to MEAL frameworks and data lifecycle

• Role of data in program design, monitoring, and evaluation

• MEAL indicators and results-based frameworks

• Hands-on Exercise: Mapping MEAL data sources in a sample project

Module 2: Designing MEAL Data Collection Tools Using ODK

• Digital survey design with ODK

• Creating forms with constraints, skips, and calculations

• Field testing and deployment via mobile data collection

• Hands-on Exercise: Design and deploy an ODK form

Module 3: MEAL Data Management Best Practices

• Organizing, storing, and securing MEAL data

• Data quality assurance (accuracy, completeness, timeliness)

• Documentation and version control

• Hands-on Exercise: Develop a data management plan for a real project

Module 4: Data Cleaning and Pre-Processing Techniques

• Common data errors and inconsistencies

• Cleaning datasets using Excel and SPSS

• Handling missing values, outliers, and duplicates

• Hands-on Exercise: Clean a raw dataset in SPSS and prepare for analysis

Module 5: Quantitative Data Analysis Using SPSS

• Descriptive and inferential statistics

• T-tests, ANOVA, correlation, regression analysis

• Application to MEAL indicators and logframes

• Hands-on Exercise: Conduct a full analysis using SPSS on MEAL data

Module 6: Qualitative Data Analysis for MEAL

• Coding and thematic analysis approaches

• Analyzing qualitative data from interviews, FGDs, and open-ended surveys

• Manual and software-assisted methods (e.g., MAXQDA overview)

• Hands-on Exercise: Analyze sample qualitative responses and generate themes

Module 7: Interpreting MEAL Data and Drawing Conclusions

• Making sense of data: trends, patterns, and relationships

• Linking data to project objectives and outcomes

• Validating findings through triangulation

• Hands-on Exercise: Develop key findings and conclusions from provided data

Module 8: Data Visualization and Reporting

• Designing visualizations (charts, tables, dashboards)

• Tools: Excel, Tableau, Power BI

• Reporting formats for different stakeholders

• Hands-on Exercise: Create a MEAL report with visualizations

Module 9: Promoting Accountability Through Data Sharing

• Feedback mechanisms and participatory analysis

• Community engagement in data review

• Ethical and secure data dissemination

• Hands-on Exercise: Develop a data feedback and sharing plan

Module 10: Adaptive Learning and Real-Time Decision-Making

• Using MEAL data for adaptive programming

• Real-time dashboards and rapid learning loops

• Embedding learning into organizational systems

• Hands-on Exercise: Simulate adaptive management using a project case