Participatory Data Analysis, Integration, and Synthesis (DAIS)
To promote evaluation use, evaluators must effectively analyze, integrate, interpret, and synthesize data into information that can be shared. We do our best to emerge with the most truthful narrative our data can tell. This effort is particularly challenging in mixed methods evaluations, where teams work with data from various sources that may have been analyzed at different times and by different people.
This course provides participants with the DAIS approach, a highly participatory, rigorous approach to integrating data, which evaluation teams can use to get from data collection and analysis to a coherent narrative arc and a roadmap for completing the evaluation product. Using this approach, the evaluation team can feel confident that their findings, conclusions, and recommendations represent the story the data are telling.
The DAIS approach works for large and small evaluations and for teams that work virtually or in person. It uses creative facilitation methods to produce more truthful integration and appropriate interpretation of analyzed data, which support crisp findings, strong evidence-based conclusions, and most importantly, appropriate recommendations.
By the end of this course, participants will be able to prepare and conduct a DAIS, including producing analysis summaries, drafting findings, moving from integrated findings to conclusions and recommendations grounded in the data, and adapting the DAIS approach to varying teams and types of evaluation.
This program, delivered in two virtual, instructor-led modules, focuses on a real-life case study and practical application. Read about each of the modules below.
Module 1: Overview, Steps, and Getting to Findings
July 26, 12 p.m.–3 p.m. EDT
This module introduces the DAIS approach and the case study, and then takes participants through the process of determining what team members will share from their analysis with others and how (from various data sources or other grouping), and how to integrate the data to develop strong, evidence-based, balanced statements of findings. Throughout the session, we will explore how this approach can be applied in the context of evaluations that participants have conducted or are conducting.
Module 2: Getting to Conclusions, Recommendations, and a Strong Evaluation Product
July 28, 12 p.m.–3 p.m. EDT
This final module will cover moving to conclusions and recommendations, and getting to a narrative arc for the evaluation product. This module will continue the case study, and end with a discussion of how this approach can be adapted to a range of evaluation types and contexts.