- Define and distinguish between monitoring and evaluation.
- Develop a program logic model to communicate an evidence-based program theory.
- Develop an M&E plan to track progress of program activities toward objectives and assess program effectiveness.
- Develop quantitative and qualitative indicators and targets for an M&E plan.
- Use relevant qualitative and quantitative data collection and analysis methods to track and evaluate program progress.
- Identify the qualities of effective qualitative and quantitative data collection tools.
- Describe how program data can be used for decision-making.
- Apply ethical guidelines for data collection and reporting.
Module 1: An introduction to monitoring and evaluating in global health
- Define monitoring and evaluation.
- Distinguish between monitoring and evaluation.
- Explain why M&E is important.
- Identify monitoring best practices.
- Explain how key M&E activities fit into a typical program cycle.
- Describe strategies to address common concerns about program evaluation.
Module 2: Program theory and frameworks
- Define what a program theory is.
- Identify three program frameworks.
- List the five main components of a logic model.
- Develop evidence-based program outcomes that align with program impact.
- Develop program outputs that align with program activities and outcomes.
Module 3: M&E plans
- Describe what an M&E plan is and why it is an important aspect of program success
- Explain the relationship between logic models and M&E plans
- Define the key components of an M&E plan
- Write SMART objectives
- Name and explain the qualities of effective program indicators
- Develop indicators and targets for an M&E plan according to specified criteria
- Describe the 6 steps involved in developing and implementing an M&E plan
Module 4: Monitoring
- Describe the basic steps to conducting effective program monitoring.
- List three potential data sources for program monitoring.
- Conduct descriptive analysis to summarize data for program monitoring.
- Describe three data visualization methods to visualize data for action.
Module 5: Evaluation
- Describe the main steps to conducting a program evaluation;
- Explain when the five types of program evaluations are used;
- Develop relevant program evaluation questions;
- Describe three program evaluation methodologies;
- Describe two quantitative designs commonly used in program evaluation;
- Name one key element to successful dissemination of evaluation findings.
Module 6: Quantitative data collection methods
- Explain quantitative sampling approaches, including what information is needed to calculate sample size.
- Explain three principles of data collection.
- Describe three data collection methods for program evaluation.
Module 7: Quantitative data analysis
- List the five main measures of data quality.
- Explain the importance of processing data for data analysis.
- Distinguish between descriptive and inferential analysis.
Module 8: Qualitative data collection methods
- Explain what qualitative data are and how they differ from quantitative data
- List the advantages and disadvantages of using qualitative data in program M& E
- Name and describe the steps involved in conducting a qualitative evaluation
- Describe strategies for planning qualitative evaluations
- Describe 7 commonly used qualitative sampling methods
- Explain the criteria used to inform sample size for qualitative data collection
Module 9: Qualitative data analysis
- Formulate effective open-ended questions to collect qualitative data
- Explain the overall structure of interview and focus group discussion guides
- Describe qualitative data collection methods (interviews, focus groups, and observations), when they are used, and their strengths and limitations
- Distinguish between subjective and objective qualitative observation data
- Define the 6 basic steps involved in thematic analysis
- Describe elements to include in a codebook and why codebooks are important
- Identify guidelines for writing up qualitative findings
Module 10: Ethics
- Explain what human subjects protections are and why they are important
- Name and define the three fundamental principles of ethics
- Explain what informed consent means and describe the key elements of a consent form
- Distinguish between anonymity, confidentiality, and privacy and describe methods to protect each
- Describe procedures that evaluators can adopt to minimize participant vulnerability
- Identify the four categories of safeguards for ethical data management and give examples of each
- Describe key recommendations to promote ethical reporting, dissemination, and use of findings
During the course, participants will be expected to:
- Analyze problem statements and develop outcomes
- Work with logic models
- Write SMART objectives and indicators
- Complete activities around data analysis and visualization (in Microsoft Excel)
- Assess evaluation questions
- Analyze qualitative methods
- Choose sampling methods
- Create open ended questions
- Work on an M&E plan