Greetings! I’m Paula Richardson from Salanga, an organization dedicated to reimagining monitoring and evaluation practices for community ownership, gender equality, and transformative change. Through our work with 50+ communities worldwide, we have gained insights and identified key takeaways from implementing a Community-Led monitoring, evaluation, accountability and learning approach (CoLMEAL).
In spring of 2018, Sharon, Natalie, and I (ARCHES Evaluation Team) began to examine the insights gained from juxtaposing the Self-Assessment Survey with the Outcome Indicators of the ARCHES Logic Model. The Self-Assessment Survey was initially created as a reflective instrument for clients to independently gauge their progress. However, the Outcome Indicators, identified through the comparative analysis, were diagnostic by nature. These indicators were intended to inform how ARCHES could tailor its support for a collaborative’s development via its Just in Time Service Model.
The Evaluation Teams’ work in 2017 also intersected with the development of an evaluation design. In a previous evaluation effort, ARCHES had developed a self-assessment survey tool that was used to document the development of intersegmental collaboratives. From this tool a list of indicators was developed and comparatively analyzed to outcome indicators listed in the logic model. This process resulted in a refined set of outcome indicators that served as the foundation for developing an evaluation design for ARCHES. As the lead evaluator, I developed an initial draft of the Evaluation design and presented it to Sharon and Natalie in January of 2018. They were tasked with peer editing the document which would be finalized and approved by March 2018.
I’m Dan Turner, Ph.D., and I serve as the Assistant Director of the Community-Engaged Data and Evaluation Collaborative (CEDEC) at the Swearer Center for Public Service at Brown University in Providence, Rhode Island. A recently launched initiative, CEDEC connects campus, nonprofit, and public agency partners, leveraging Brown’s resources to advance data and evaluation capacity in …
We are Nubia Goodwin (Research Associate) and Carolyn Fisher (Research and Evaluation Scientist) of the Institute for Community Health. We are both members of a project team that conducted a social network analysis as part of our evaluation of a multi-year, national funding project focused on community power building.
Janelle, JoAnna, Mary, and Christiana here, evaluators from Emory Centers for Public Health Training and Technical Assistance. We had the opportunity to present a session entitled No More Crappy Surveys at last year’s AEA Summer Evaluation Institute. We are on a mission to rid the world of crappy surveys, and are here to share some of our Hot Tips and Rad Resources to do so.
If you haven’t already, check out the first blog post in this series, No More Crappy Surveys – Best Practices in Survey Design for Evaluations (you can check it out here). Today, we’ll be following up with some tips on how to analyze your surveys (which, of course, you’ve made sure are not crappy!). Stay tuned for our final post of this series, on how to report your findings to different audiences.
Hi, I am Megha Pradhan, Director for the Center for Learning on Evaluation of Results – South Asia (CLEAR South Asia), which is a center for evaluation capacity development and an Implementing Partner of the Global Evaluation Initiative (GEI).
Hi, I am Heather Bryant, a member of the Global Evaluation Initiative (GEI) Global Team. The GEI supports developing countries in strengthening their monitoring and evaluation (M&E) systems to help governments gather and use evidence that improves the lives of their citizens. The GEI believes that to effectively support countries in this process and to be able to provide tailored, context-specific advisory services, it is first necessary to understand the existing systems that affect M&E in the country. To assist in this effort, the GEI Global Team, in collaboration with the global network of Centers for Learning on Evaluation and Results (CLEAR), developed the Monitoring and Evaluation Systems Analysis (MESA) diagnostic tool. The MESA is a tool that guides stakeholders (e.g., government entities, evaluation professionals, civil society) in gathering, structuring, and analyzing information on the current capacity of their country’s M&E ecosystem. Since the tool’s launch in early 2022, the GEI Global Team and colleagues in the CLEAR network have been using it to help identify what is working well, what needs to be improved, and to inform capacity-development strategies meant to strengthen the systems that enable M&E to flourish. We have learned a few things along the way – both in the development and in the use of the tool.
My name is Liane Ventura and I serve as a faculty Research Associate with the Center for Applied Research and Evaluation (CARE) in Women’s Health at East Tennessee State University (ETSU). I am an applied Public Health researcher who is interested in mixed methodology and community-engaged approaches.
Hi everyone, my name is Wai Lam Wong and I’m an information systems analyst at a community health organization in California. My academic background is in computational social sciences and I’m always looking for ways to leverage technology for social impact. This post is about using Google BigQuery to enable a small nonprofit’s project team …
Tech TIG Week: Supporting Data Analytics with Google BigQuery by Wai Lam Wong Read More »
