Course Aim
- Have developed a deeper understanding of the characteristics of effective M&E and M&E systems
- Have reviewed approaches to planning for M&E, including Theory of Change, and explored some of the challenges with these
- Be able to select and use appropriate data collection methods and tools effectively and explored debates around newer qualitative and participatory approaches
- Have considered principles and steps in data analysis and the issue of quality of evidence
- Have explored ways to address issues around impact assessment and the M&E of outcomes and impact
- Have considered their own role in bringing about improved M&E within their projects, programmes and organisations
Course Description:
This course builds on participants' understanding and skills of how to develop sustainable and cost effective monitoring and evaluation processes and practices within their own projects, programmes and organisations. It is also relevant for those trying to improve and enhance current monitoring and evaluation (M&E) systems, or supporting partners to develop and implement effective M&E. The course provides an overview of all aspects of M&E from planning to M&E and impact assessment, with a focus on ensuring that M&E contributes towards improving organisational learning and accountability
Course Content:
- Clarifying M&E terminology and the uses of M&E
- Introducing a structure for addressing practical issues and challenges in M&E
- The components of an effective M&E system
- Indicators and how to identify them
- Overview of planning tools to help understand the logic of an intervention and provide a foundation for good M&E
- Strengths, weaknesses and applications of quantitative and qualitative data collection methods and tools
- Introducing more complex tools and methodologies for collecting outcomes and impact data including e.g. RCTs, contribution analysis, outcome mapping, process tracing, most significant change etc.
- Issues to consider when designing and managing an effective evaluation process, and how to close the learning loop and ensure results are used for improvement
- Steps in analysing quantitative and qualitative data, and what makes good quality evidence
- Incorporating learning into M&E - strategies for encouraging results of M&E to be valued and used.
