Reframing Failure

Image by Paul Keller, CC BY 2.0
  1. Have compassion. They at least showed up and so have some internal sense, whether latent or manifest in their minds, that they need or could otherwise benefit from what we are teaching.
  2. Acknowledge their feelings. We do that in our ground rules before class, but also in our approach of expressing gratitude for their contributions, no matter how small, not in an inauthentic, “touchy-feely” way, but an authentic place of gratitude and recognition that what they are doing is hard and they haven’t before had the chance to learn the skills, techniques, and mindsets we are demonstrating for them.
  3. Make our classes a safe place to fail. In fact, we encourage failure as an invitation to learning, giving each person permission to fail. In our R and Python classes, I get excited and celebrate when someone gets an error message so we can discuss the why and acknowledge how the experience of something failing can be a block to learning. I admit my own “not knowing” very overtly no matter the class I’m facilitating, modeling how I move through my feelings of vulnerability to arrive at knowing, and explicitly share this with them as a model for their own moments of not knowing. I hold their feelings of not knowing tenderly by generously giving them my attention as they explain what they did, why it didn’t work the way they intended, and patiently prompting them to think through the problem on their own. I try to normalize the experience of not knowing and provide them encouragement to continue working, reminding them the solution is within their capacity, giving them the answer only when they are too frustrated or just missing some key piece of information. I move them through the obstacle but then reflect with them on the process, asking for them to reflect on what just happened so they can internalize whatever technique or operation we just accomplished. If possible, I have them teach someone else who has a same or similar question so they can practice their new-found mastery of whatever they just learned.
  4. Model cooperation and collaboration as a strength. We often say “Don’t data alone” or “Data analytics is a team sport.” We say it as a joke, but there’s an embedded truth that we need to work together in order for the work we do to have the impact we want it to have. Our colleagues can be a source of criticism and blame, but they can also be a source of strength and support. Modeling the latter helps reduce the likelihood of the former, or at least provide better resilience when it unfortunately happens.



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