Course Objectives:

  • 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

Course Activities:


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