Monitoring and Evaluation

This lecture provides examples of everyday use of the terms 'monitoring' and 'evaluation' and defines Monitoring and Evaluation in the context of government or development programmes, policies or services. 

This video highlights that monitoring and evaluating are related, but very different activities.

Based on the previous lectures, this video explains in more detail what we mean when we speak of monitoring.

This lecture describes in more detail what evaluation is, how they are carried out and why it is different from monitoring.

This lecture argues that Monitoring and Evaluation is currently undergoing rapid changes due to three reasons: 

• a focus on real results, 
• an increasingly complex and fast-changing environment and 
• accelerating technological changes that are both an opportunity and a threat to Monitoring and Evaluation.

This section starts with a simple example to illustrate measurements: a cat.

This lecture introduces the concept of measurements as a reduction in uncertainty - not necessarily a precise number.

This lecture argues that a common fallacy is the assumption that certain things cannot be measured. It argues that if you can observe a thing in any way at all, it can also be measured in some way.

This lecture explores the everyday use of the term 'results' We then turn to the idea of a hierarchical 'chain of results'  - and illustrate it with a practical example how to apply it to our personal lives.

This somewhat longer lecture takes an in-depth look at the different levels of the results chain. 

It should allows students to critically review existing result chains (for example in logical frameworks) and properly define their own result chains with inputs, activities, outputs, outcomes and impact.

This lecture provides two typical but simplified examples of a result chain: reducing smoking and a reduction in domestic violence.

This lecture explains the difference between three terms that are frequently misunderstood: data, information and knowledge.

This lecture highlights the differences between quantitative (=numbers) and qualitative (=text) data; it argues that both types of data are required and should be combined for more credible evidence.

This longer lecture highlights the fundamental differences between secondary data (=data that has already been collected) and primary data (=data that we still need to collect) and its advantages and disadvantages.

It also describes the toolbox available to us to carry out primary data collection.

The lecture in this final section of the course looks at reasons why we should consider using indicators - and that Monitoring and Evaluation often requires difficult decisions about what not to measure.

This key lecture explains the six element that - as a minimum requirement - any indicator must include: a description, a baseline, a target, a source, the frequency of data collection and responsibilities.

Based on the previous lecture, this video shows four examples of real-life indicators are discusses their characteristics.

The resources linked to this lecture provide you with more advanced and more detailed reading recommendations.