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Key Takeaways: Using Data to Understand the Community You Serve


Key Takeaways: Using Data to Understand the Community You Serve

Approximately thirty participants -- Extension professionals from all over the US, from Oregon to Ohio, Connecticut, and Virginia -- joined us today for a productive Connect Extension Virtual Chat on Using Data to Understand the Community You Serve. We discussed their experiences with data, their data-related needs, and and how we might best design and bring data literacy resources to  Extension. You can access the chat transcript here, and read our chat highlights below.

Extension Professionals' Experiences with Data

Our participants reported that they value data and use it in their work and decision-making to the extent possible. They reported relying on data for informing their reports and presentations, in conducting program evaluation and for program improvement, and for better understanding their stakeholders.

All participants reported they would like to use data more often; some mentioned that the absence of data makes problems "invisible" or makes it difficult to understand problem context. However, Extension professionals face several barriers in relying on data more heavily: relevant resources that can inform solutions are not always available or granular enough, data may be difficult to collect or its quality can be poor, agents can be unaware of data resources, and they may not have the training or tools to use them.

Despite these barriers, most participants were aware of at least some data resources that pertain to their problem areas. Many were familiar with CountyHealthRankings, an excellent resource for social determinants of health data. They also reported using local resources like AllThingsMissouri, issue-specific datasets like those provided by the Environmental Protection Agency, and some mentioned using GIS and spatial data to better understand their counties.

A number of Extension professionals reported that they've done their own data analyses as well. Most used Microsoft Office tools like Excel, statistical programming environments like Statistical Package for Social Sciences (SPSS) and Stata, NVivo for qualitative coding, and platforms like Tableau for descriptive data analysis and visualization.

Extension Professionals' Data Needs

Our participants provided helpful suggestions for designing a guide to getting started with data and data analysis for Extension professionals. In a getting started guide, they reported they'd like to read about options for collecting data and understanding what sources that could inform their programs already exist. They would like to be introduced to data analysis tools, and see illustrations and data analysis applications through case study examples. Since communicating results to stakeholders was important to our participants, they would also want to learn about presenting results and making them appealing through visualizations.

Besides reading about the importance of data in driving decision-making, Extension professionals would be willing to get "hands-on" and try following a data analysis tutorial. Their ideal tutorial would be approachable and presented in an engaging way, using worked-out, step-by-step case studies and multiple modes of presentation, like text, video, and images.  Participants agreed that simpler is better when it comes to getting started, as agents have varying levels of data skills and experiences.

Overall, Extension professionals who participated in the discussion would welcome new data literacy resources. With the helpful input they provided to our New Technologies for Agricultural Extension team, we hope we can bring them one this summer!

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