Data Jam Toolkit

The Data Jam Toolkit consists of three documents that will help you plan and execute your data jam. Additionally, you will find information on Adult Education principles in Data Jams, Literature on Data Jams, and example products from Data Jams on this website.

Please contact Christian.Schmieder@wisc.edu if you have any questions or if you would like to request coaching and consulting services related to Evaluation Capacity Building through Data Jams. 

Free PDF Data Jam materials:
Planning a Data Jam
Using QualPal to prepare for Data Jams and execute Data Jams
Customizable agenda for a 2-day Data Jam

An approach to analysis skill building grounded in Adult Education principles

Data Jams are not an analysis method – they are an approach to teaching qualitative analysis, and a support tool for mentorship of analysts. Data Jams are intentionally designed to create spaces for Legitimate Peripheral Participation (Lave & Wenger, 1991), i.e. they are spaces in which less experienced analysts have an opportunity to work with more experienced analysts on authentic tasks within a safe environment. Data Jams are designed to bring people together around shared analytic tasks and around a shared desire  to learn collaboratively; as such, they are a powerful tool to foster and authentically convene communities of practice (Wenger & Trayner, 2015).

The tangible goal of Data Jams is to walk away with a useful, material analysis product. This focus on ‘learning-by-making’ grounds our approach deeply in the tradition of constructionism (Papert & Harel, 1991). Data Jams are essentially pop-up methods makerspaces (Schmieder, 2020), since they are “informal sites (…) where people of all ages blend digital and physical technologies to explore ideas, learn technical skills, and create new products.” (Sheridan et al, 2014).

As an approach to qualitative methods pedagogy, Data Jams are designed to translate (Woolf & Silver, 2018) between analytic tools (such as Qualitative Data Analysis Software) and analytic method.  A discussion of Data Jams as an approach to methods pedagogy has been provided by Silver, Bulloch, Salmona & Woolf in the Handbook of Teaching and Learning Social Research Methods (Nind, 2023)

Literature related to Data Jams

  • Christina Silver, Sarah L.  Bulloch, Michelle Salmona & Nicholas W. Woolf (2023): Integrating the online teaching of qualitative analysis methods and technologies: challenges, solutions and opportunities. In Nind M (ed.) Handbook of Teaching and Learning Social Research Methods. Edward Elgar Publishing, pp 316-331.
  • Christian Schmieder (2020): Qualitative data analysis software as a tool for teaching analytic practice: Towards a theoretical framework for integrating QDAS into methods pedagogy. In: Qualitative Research, 20(5), pp. 684-702.
  • Christian Schmieder / Kyrie E.H. Caldwell / Ellen Bechtol (2018): Readying Extension for the Systematic Analysis of Large Qualitative Data Sets. In: Journal of Extension 56(6), Article 26.
  • Christian Schmieder (2017): Constructing and Using a Large Organizational Dataset: Identifying Equity Practices in an Institutional Civil Rights Database. In: Woolf, Nicholas H. & Silver, Christina:: Qualitative Analysis Using MAXQDA: The five-level QDA method. New York: Routledge. Pp. 177-190.