Date de l'événement : 2026-07-13 The Evaluators' Institute Date limite : 2026-07-09
AI-powered tools are rapidly transforming how data is analyzed, interpreted, and communicated. This course provides an accessible introduction to leveraging AI throughout the evaluation process—from literature review, research design, and data analytics, to writing reports and preparing presentations. Our goal is to explore the capabilities of AI across evaluation; where it’s strong, and where it should be avoided. Topics include AI-driven data cleaning and exploration, automating statistical analysis, enhancing visualizations, and using AI for reporting. We will also cover best practices for evaluating AI-generated outputs and avoiding common pitfalls. The course is designed for professionals who are already comfortable with fundamental statistical concepts and are ready to explore how AI can support and extend their analytical capabilities.
Contemporary evaluation theory and practice are changing rapidly to adapt to a new and rapidly evolving evaluation ecosystem. This course is designed to explore the new basics needed to be a successful evaluator and applied researcher in 2026 and beyond. Guided by the American Evaluation Association (AEA) foundational documents including the AEA evaluator competencies and public statement on cultural competence, this course will provide new and emerging evaluators, and applied researchers, with an up-to-date perspectives on evaluation theory, approaches, methods, and practice. Although the major focus of the course is program evaluation in multiple settings (e.g., public health, education, social services, business, and international development), examples from personnel evaluation, product evaluation, organizational evaluation, and systems evaluation will be used to illustrate the new basics. The course will conclude with how to plan, design, and conduct ethical and high-quality program evaluations using artificial intelligence and a contingency-based and culturally responsive approach.
Date de l'événement : 2026-07-14 The Evaluators' Institute Date limite : 2026-07-10
The tools and techniques of cost-benefit and cost-effectiveness analysis will be presented. The goal of the course is to provide analysts with the skills to interpret cost-benefit and cost-effectiveness analyses. Content includes identification and measurement of costs using the ingredients method; how to specify effectiveness; shadow pricing for benefits using revealed preference and contingent valuation methods; discounting; calculation of cost-effectiveness ratios, net present value, cost-benefit ratios, and internal rates of return. Sensitivity testing and uncertainty will also be addressed. Individuals will work in groups to assess various costs, effects, and benefits applicable to selected case studies across various policy fields. Case studies will be selected from across policy fields (e.g. health, education, environmental sciences).
Date de l'événement : 2026-07-15 The Evaluators' Institute Date limite : 2026-07-13
Most evaluation data are more complex than standard statistical methods assume. The constructs we care about cannot be observed directly and are measured imperfectly through surveys and instruments. At the same time, participants are nested within sites, sites within regions, and measures are often repeated over time. When evaluators apply conventional approaches to data like these, the result is often biased estimates, misleading conclusions, and findings that don’t hold up to scrutiny. This three-day course introduces structural equation modeling (SEM), including confirmatory factor analysis (CFA) and multilevel modeling (MLM). The course is organized around problems that evaluators regularly encounter, with methods introduced as tools to address them. Each day builds on the last, moving from measurement to data structure to their integration. Lectures and discussions are paired with applied software demonstrations throughout the course. Participants are encouraged to bring their own data for use during Day 3 application sessions.
Strategic planning is becoming a common practice for governments, nonprofit organizations, businesses, and collaborations. The severe stresses facing these entities make strategic planning more important and necessary than ever. For strategic planning to be really effective it should include systematic learning informed by evaluation. This course examines the theory and practice of strategic planning and management with an emphasis on practical approaches to identifying and effectively addressing organizational challenges – and doing so in a way that makes systematic learning and evaluation possible. The approach engages evaluators much earlier in the process of organizational and programmatic design and change than is usual. Topics covered include understanding why strategic planning has become so important; understanding what strategic planning is – and is not; the Strategy Change Cycle; key strategic planning tools and techniques; and designing formative, summative, and developmental evaluations of strategic planning processes, missions, strategies, and organizational performance.