Love is blind, and far too often, our relationships with quantitative data remain unhealthy. Despite evidence to the contrary, too many of us still believe that grades provide insight and that standardized test scores suggest solutions. Going gradeless isn’t easy, though. Numbers are far more efficient to work with. They seem to create quick and false certainty during trying times, too. Using data in healthy ways is difficult work. It keeps us on the move, and it reminds us, over and over again, that if we’re going to get real about using evidence to serve learners, our analysis will likely never end. It will only deepen and perhaps, intensify.

Many of the teachers that I support appreciate the power of qualitative data. They know that documenting learning made visible provides insight that numbers alone cannot, and they’re happy for the opportunity to collect and analyze these data. The greatest challenge they face? Managing it all.

Interviews, photographs, videos, and anecdotal notes from observation are powerful data sources, but those who have spent more than a handful of days capturing this kind of data know all too well how quickly they begin to pile up. Sharan Merriam offers a variety of powerful recommendations to those who work with qualitative data. I’ve adapted them for classroom applications:

Ten Ways to Avoid Drowning in Qualitative Data

  1. As you begin learning from the data you are gathering, narrow your study.
  2. Then, narrow your view within this smaller study.
  3. Use analytic questions to refine your perspective and begin limiting the data you gather.
  4. Plan your next study in response to the findings from your last study.
  5. Reflect on your findings as you go, and make helpful notations.
  6. Share the hunches you’re developing with your students, and invite them to help you tighten your focus.
  7. Research your topic, and use what others are learning to inform your work.
  8. Create metaphors and analogies for your discoveries.
  9. Use visual devices to represent the story of your learning.
  10.  Code your data.

All of these suggestions make this kind of data work a far more tidy and purposeful endeavor, but the tenth suggestion is by far the most effective when it comes to harnessing and making meaning from robust amounts of qualitative data.

How do we code qualitative data?

Coding involves assigning simple and very distinct words, letters, or numbers to bits of data that seem particularly relevant to our research questions. For instance, I recently reviewed several dozen video interviews with young writers who were asked to describe their experiences with revision. Over and over again, writers spoke to the timeliness, amount, and quality of feedback they received from their teachers. I coded these bits of data “feedback” and in doing so, I began establishing a cluster of common qualitative data points. As themes emerge across them, categories begin to take shape.

Rather than attempting to create a code for every bit of data gathered, consider your research questions and code in ways that are relevant to your studies. As you begin, keep an open mind and a very wide perspective. One of the greater benefits of qualitative data analysis is its potential to inspire emergent theories. This can only happen if we’re willing to let go of what we know and what we’re looking for long enough to notice things that we didn’t expect to.

The poster below can guide your first steps. You can grab it on Canva too.








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