Training in monitoring and evaluation, research methods and digital tools for development teams.
Core concepts and functions of monitoring and evaluation; the results chain; logical frameworks; indicator design; baselines and targets; data sources and collection methods; stakeholder roles; and the use of findings to guide a project.
Assessing information needs; developing a monitoring and evaluation matrix; indicator reference sheets; data collection and management plans; information flows; dashboards; and the roles, schedule and budget for the system.
Principles of results-based management; problem analysis; defining a vision for change; building causal pathways; making assumptions explicit; and linking theory of change, logical frameworks, monitoring and evaluation.
Combining quantitative and qualitative approaches; selecting a mixed-methods design; sampling; tool design; questionnaires, interviews and focus groups; integrated analysis; data triangulation; and presenting findings.
Preparing an evaluation; developing evaluation questions; the relevance, coherence, effectiveness, efficiency, impact and sustainability criteria; evaluation matrices; data collection and analysis; triangulation; conclusions, lessons and practical recommendations.
A practical overview of the data cycle, quality standards, indicators and dashboards, analysis and visualisation tools, data governance and the use of evidence to strengthen programme decisions and performance.
An introduction to AI, machine learning, generative AI and language models, with practical applications for monitoring and evaluation, data analysis, reporting and responsible programme management.
Tell us about your context, the skills you want to strengthen and your constraints. We can shape the programme and format together.
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