Water, water everywhere, but not a drop to drink. That’s a sailor cast away on the high seas, surrounded by a never-ending ocean but without a sip of liquid to sustain life.
In like manner, extension administrators and faculty are surrounded by oceans of data but without the means to make sense of that data to help sustain their programs.
Christian Schmieder, eXtension Fellow and Qualitative Research Specialist at the University of Wisconsin Extension, says, “We collect over 1,200 impact statements and 600 to 800 program narratives every year. That’s a lot of time and money invested, but if we don’t use those data well, it’s money out the window.” Schmieder and his colleagues are changing that by teaching extension professionals how to deal with large amounts of textual data through the Data Jam Initiative.
What Is a Data Jam?
Single- or multi-day Data Jams provide an opportunity for extension colleagues to get together in an intensive experience to do analytic work using analysis software. The goal is to end the experience with concrete write-ups, models, theories and visualizations that can be shared with colleagues, partners and relevant stakeholders.
Josset Gauley, Program Development & Evaluation Specialist, FoodWise, at UW-Extension, says, “A neat thing about the Data Jam is putting aside a whole day to talk about your program outside the normal work-day routine. When you have 5 to 10 people, all concentrated on the same task, you can accomplish a lot. You can see what’s missing, where the gaps are.”
In Data Jams, groups of 4 to 12 extension colleagues look at narratives and impact statements from central data collection systems to answer questions such as, “How do our programs affect those in poverty?” Creating and fostering a common institutional language is key to this process because “analysts need to agree on the meaning of core terms – for example what ‘program’ means, or what we institutionally mean when we say ‘poverty,’” according to Schmieder.
Schmieder continues, “Oftentimes we do analysis in silos; that means that the knowledge we produce remains also in silos, and we keep on re-inventing the wheel.” Data Jams – and the institutional use of specialized analysis software – allow extension personnel to build on each other’s analytic work to “radically reduce the amount of time it takes to analyze and synthesize massive amounts of data.”
Collecting usable and relevant data is one of the core challenges for institutional data sets. Engaging more colleagues in the analysis of data increases institutional buy-in into reporting, which ultimately strengthens data quality. During Spring 2017, John Pinkart, FoodWIse Program Coordinator, Oconto and Marinette Counties, Wisc., participated in a three-day Data Jam coordinated by Schmieder and colleagues. What Pinkart discovered was, “We do a good job of setting the context, describing what we’re doing and writing results narratives, but we really struggle to see a lot of evidence of behavior change and impact.” Pinkart’s FoodWise program receives federal SNAP-Ed funding, so he’s very aware of the need for accessible, useful impact data. Pinkart says after the Data Jam, he and those he coaches will be “much more mindful in describing impact and focus more on holistically connecting direct education, policy system work, and results.”
Gauley allows that not every extension professional is excited about reporting and data evaluation. He says Data Jams are “super valuable” because educators “walk away with a better understanding of how their data are used, and they feel appreciated and more valued by the organization.” Then, in the future, as they report outcomes and impacts to teachers, parents, policymakers, county boards and others interested in obesity prevention, they will do a better job.
What Is Next?
Schmieder and colleagues are taking a big-picture approach to data analysis and organizational change. Justin Smith, eXtension GODAN Fellow and county extension director in Mason County, Wash., and Schmieder are currently developing and testing analytic workflows based on Data Jams that can be used to seed crowd-analysis of massive data sets, and to quality-control automated categorization of data.
Last March, Smith and Schmieder co-conducted a Data Jam focusing on extension data related to climate change. Smith says, “Ultimately, someone will be able to query the eXtension system and be connected not only to extension literature but also local information and data sets from around the world about weather, health, vegetation, population and more to solve problems, such as those related to climate change.”
“We also want to connect people – experts with particular skills and knowledge to inform the data and help design research models,” Smith says, all with an eye toward giving educators the gulps of life-giving knowledge they need to serve their publics.
For More Information
Additional sites to learn about Data Jams:
- Minnesota Extension Family Matters Blog: http://blog-family-matters.extension.umn.edu/2017/07/jam-that-data-jam-it-good.html
- eXtension website: https://www.extension.org/2017/03/28/datajams_datachallenge/
Contact Josset Gauley at: firstname.lastname@example.org or 608-265-4975