Impact evaluation represents a critical framework for assessing how policies, programs, and projects influence development outcomes and institutional effectiveness. It provides evidence based insights into the relevance, efficiency, and sustainability of interventions, ensuring accountability and informed decision making. By combining structured evaluation models with advanced data collection and analysis methods, organizations can identify what works, what does not, and why. This training program introduces institutional approaches, analytical techniques, and reporting frameworks that support the design and implementation of credible impact evaluations.
Analyze the institutional role and principles of impact evaluation in policy and program management.
Design evaluation frameworks using theories of change, logic models, and performance indicators.
Classify data collection tools and techniques for both quantitative and qualitative evaluation.
Evaluate analytical models and statistical methods used for impact measurement.
Develop structured reporting frameworks to communicate findings and inform decision-making.
Government officials and policymakers.
Program managers and project coordinators.
Monitoring and evaluation professionals.
Development practitioners and consultants.
Institutional role of impact evaluation in assessing policies and programs.
Core principles, models, and frameworks guiding impact evaluation.
Classification of evaluation types, including formative, summative, and ex-post.
Ethical frameworks and governance considerations in evaluation processes.
Relationship between impact evaluation and accountability mechanisms.
Frameworks for defining evaluation questions and objectives.
Institutional structures for building theories of change and logic models.
Methodological strategies for selecting evaluation approaches.
Techniques for establishing evaluation criteria and performance indicators.
Governance models for evaluation planning and resource allocation.
Quantitative and qualitative data collection frameworks.
Institutional use of surveys, interviews, focus groups, and case studies.
Models for integrating secondary data and triangulation techniques.
Structures ensuring data quality, reliability, and validity.
Digital and technological tools supporting impact evaluation data collection.
Frameworks for analyzing quantitative and qualitative evaluation data.
Statistical models for impact estimation, including DiD and propensity score matching.
Institutional approaches to interpreting findings and assessing causal links.
Methods for identifying unintended outcomes and secondary impacts.
Strategies for translating data into actionable evaluation insights.
Structures for developing professional evaluation reports.
Frameworks for presenting findings to diverse stakeholders.
Techniques for linking results with institutional decision-making.
Strategies for using evaluation insights to refine policies and improve programs.
Approaches for ensuring transparency and knowledge sharing in evaluation outcomes.
