I consider teaching and presenting an integral part of my job as a data scientist. One way to become better at teaching is to collect feedback from the learners. I tried different ways of collecting feedback: passing a questionnaire, Polldaddy surveys or Google forms, or simply asking (no, begging) the learners to send me an e-mail with the feedback. Nothing really worked. The response rate was pretty low. Moreover, most of the feedback was a useless set of responses such as “it was OK”, “thank you for your time”, “really enjoyed”. You can’t translate this kind of feedback to any action.
Recently, I figured out how to collect the feedback correctly. My recipe consists of three simple ingredients.
Collecting feedback. The recipe.
working time: 5 minutes
- Open-ended mandatory questions: 1 or 2
- Post-it notes: 1 – 2 per a learner
- Preventive amnesty: to taste
Our goal is to collect constructive feedback. We want to improve and thus, are mainly interested in aspects that didn’t work well. In other words, we want the learners to provide constructive criticism. Sometimes, we may learn from things that worked well. You should decide whether you have enough time to ask for positive feedback. If your time is limited, skip it. Criticism is more valuable than praises.
Pass post-it notes to your learners.
Next, start with preventive amnesty, followed by mandatory questions, followed by another portion of preventive amnesty. This is what I say to my learners.
[Preventive amnesty] Criticising isn’t easy. We all tend to see criticism as an attack and to react accordingly. Nobody likes to be attacked, and nobody likes to attack. I know that you mean well. I know that you don’t want to attack me. However, I need to improve.
[Mandatory question] Please, write at least two things you would improve about this lecture/class. You cannot pass on this task. You are not allowed to say “everything is OK”. You will not leave this room unless you handle me a post-it with two things you liked the less about this class/lecture.
[Preventive amnesty] I promise that I know that you mean good. You are not attacking me, you are giving me a chance to improve.
When I teach using the Data Carpentry methods, each of my learners already has two post-it notes that they use to signal whether they are done with an assignment (green) or are stuck with it (red). In these cases, I ask them to use these notes to fill in their responses — one post-it note for the positive feedback, and another one for the criticism. It always works like a charm.