Monitoring & Evaluation, Data Management & Analysis in Food Security & Nutrition Programmes

This AJT course emphasizes the need for careful selection of indicators in designing information support systems at various administrative levels and the skills required for analysis and interpretation of data collected for policy making. The demand for data on impact of policies, programmes and interventions on food and nutrition security is rapidly growing. Both governments and civil society have a need for information on food and nutrition conditions and trends and the impact of policies and interventions. Monitoring, evaluation and impact assessment are undertaken by governments, NGOs, international agencies and donors. The course is job-oriented and the training approach is interactive. It provides the participants with the possibility to learn from expert facilitators as well as from each other.

• Governments & Civil Societies
• Planners, Monitors & Evaluators
• Project Managers
• Nutritionist
• Non Governmental Organizations (NGOs)

• To learn the principles of participatory and orientated planning, monitoring and evaluation in food and nutrition security
• To learn clear ideas for improving M&E systems and impact assessments for food and nutrition security.
• To learn and understand the role of food and nutrition security for attaining SDGs
• To learn how to strengthen competence in designing an M&E-system including assessments for food and nutrition security programmes.

• Data use frameworks and key concepts
• Data demand
• Information availability
• Information use

• Data analysis key concepts
• Types of variables
• Basic analysis

• Numerical summaries for discrete variables
• Tables for dichotomous variables
• Tables for categorical variables
• Tables for ordinal variables
• Graphs and charts for dichotomous and categorical variables
• Graphs and charts for ordinal variables
• Tabulations for summary statistics for continuous variables
• Graphs and charts for continuous variables

• Planning for qualitative data analysis
• Reviewing the data
• Organizing your data
• Coding the data
• Introduction to use of qualitative data analysis software (NVivo)

• ### Planning for qualitative data analysis
• Comparison of Data analysis packages
• Basics for statistical analysis
• Testing for normality of data
• Choosing the correct statistical test
• Hypothesis testing
• Confidence intervals
• Tests of statistical significance (Parametric and non-parametric tests)
• Hypothesis testing versus confidence intervals
• Interpreting the data

• Introduction to Impact Assessment
• Programme Design Implications
• Impact Assessment in Programme Design

• Overview of Methods and Approaches
• Quantitative Methods: Household Surveys
• Quantitative Methods: Secondary Data
• Qualitative Methods
• Selecting Methods and Approaches

• What is M&E?
• M&E Plans
• M&E Frameworks
• Indicators
• Data sources collection and use
• Defining a good M&E system
• Relating Monitoring and evaluation to your project cycle
• Including M&E in food security programme design
• Identifying the challenges facing Monitoring and evaluation professionals in the Food Security and Nutrition sector
• Participatory M&E systems

• M&E Frameworks basics for Food Security and other programs
• M&E in Food Security and Nutrition context
• M&E Frameworks
• Developing and operationalizing M&E frameworks
• Linking M&E frameworks to indicators
• Using data
• Monitoring result and impact using a logical framework

• Introduction to M&E in Gender and Food Security
• Prioritizing gender in M&E plans
• Exploring gender in M&E plans
• Selecting indicators to measure gender related outputs and outcomes
• Gender considerations for data collection, interpretation and use

• Agree on the purpose and principles of the project M&E system
• Agree on and design core documents to setup an M&E system
• Establish project M&E system
• Agree on field monitoring data collection and management process
• Agree on Monitoring data analysis process
• Agree on process for monitoring data utilization and reporting
• Review and revise M&E plans based on progress
• Agree on process of evaluation management

• Communication and reporting for M&E
• Contemporarily methods of disseminating

• Data collection methods: How to undertake data collection (quantitative and qualitative)
• M&E field trips
• Increasing questionnaires response rates
• Data collection versus data analysis
• Data quality and data management
• Data quality dimensions
• Functional areas of data management systems
• Double counting
• Obtaining data from Social media

• ICT innovations
• Data collection implementation models
• Key choice of application to collect data in rural areas
• ICT tool for Data processing
• Using Mobile phones for data collection
• Dashboards; analytics, data management and stakeholders access
• Case study