Collecting large amounts of textual data is easier than ever – but analyzing those growing amounts of data remains a challenge. The University of Wisconsin – Extension responds to this challenge with the “Data Jam Initiative”, an Evaluation Capacity Building model that focuses on the collaborative, making-centered use of Qualitative Data Analysis Software. In this first of three blog posts I will provide a brief overview over the Initiative, the tools we’re using, and the products we’re making in Data Jams.
Extension’s Data Challenge
Extensions collect large amounts of textual data, for example in the form of programming narratives, impact statements, faculty activity reports and research reports, and they continue to develop digital systems to collect and store these data. Collecting large amounts of textual data is easier than ever. Analyzing those growing amounts of data remains a challenge. Extensions and other complex organizations are expected to use data when they develop their programs and services; they are also expected to ground their communications and reports to stakeholders in rigorous data analysis.
Collaborative, Software-Supported Analysis as a Response
The University of Wisconsin-Extension responds to this expectation with the Data Jam Initiative, an Evaluation Capacity Framework that utilizes Qualitative Data Analysis Software. In monthly full-day Data Jams and multi-day analysis sessions, colleagues meet to explore and analyze data together. Data Jams are inspired by the concept of Game Jams. In Game Jams, game developers meet for a short amount of time in order to produce quick prototypes of games.
Asking Real Questions, Analyzing Real Data
The most important feature of Data Jams is that we work with data and questions that are relevant to our colleagues; in fact, most topics in Data Jams are brought up by specialists and educators from across the state. By collaboratively analyzing programming narratives and impact statements from our central data collection system, we start answering questions like:
- How are equity principles enacted in our Community Food Systems-related work?
- How do our colleagues state-wide frame their work around ‘poverty’?
- How does state-wide programming in Agriculture and Natural Resources address Quality Assurance?
- How are youth applying what they’ve learned in terms of life skills in our state-wide 4-H and Youth Development programming?
- How does FoodWIse (our state-wide nutrition education program) partner with other organizations, both internally and externally?
Using Qualitative Data Analysis Software, Data Jammers produce concrete write-ups, models, initial theories and visualizations; these products are subsequently shared with colleagues, partners and relevant stakeholders.
Building Institutional Capacity to Analyze Large Datasets
Through the Data Jam Initiative, we build institution-wide capacity in effectively analyzing large amounts of textual data. We connect teams, researchers, evaluators and educators to develop commonly shared organizational concepts and analytic skills. These shared skills and concepts in turn enable us to distribute the analysis of large data sets across content and evaluation experts within our institution. The overall goal of the initiative is to enable our institution to systematically utilize large textual datasets.
Since early 2016, we use the Data Jam model in monthly one-day Data Jams across Wisconsin, in regular internal consulting and retreat sessions for project and program area teams, and in graduate methods education on the UW-Madison campus. We have hosted external Data Jams on the University of Washington Pullman campus and at the United Nation’s Office of Internal Oversight Services (OIOS).