Ommiting Responses & Quantitative vs. Qualitative Data about questionnaire HOT 4 OPEN

Good questions--curators/analyzers should answer on this thread

from questionnaire.

I omitted the students who did not provide the 4 learning style scores

from questionnaire.

our group decided to first analyze the numerical data by omitting the students who didn't provide their score (Kristina suggested how here: #4). Then, once we have a sense of the distribution, we'll see if we can estimate the non-numeric responses (e.g. "I like hands-on projects and lectures" might indicate a kinesthetic and aural learner) and incorporate them. If it seems to skew the distribution too much, we might reconsider that method.

from questionnaire.

@teresita As we discussed during office hours yesterday, this is an excellent strategy! This is a thoughtful approach that is mindful of the balance between getting a good answer and throwing out too much data in a way that would skew the results. Whichever path you ended up choosing, being explicit about what method you used so that it is reproducible by someone starting with the same input data as you means that if they disagree with the decision that you made they can adjust the processing pipeline with their own strategy to see how that will affect the end result.

Great work!

from questionnaire.