When I asked students about what they learned regarding data literacy, here's what they said:
"I think even the process of looking at output and being able to interpret that speaks to how much we're learning about data literacy, let alone the ability to run models and then be able to explain what they mean."
"It takes time and literacy comes in degrees. No one has learned 'everything' there is to know about how to analyze a dataset or the results that come from it. Instead you learn a number of tools that are widely applicable then need the skill to discern what tools will be most valuable in any given situation. That ability seems more useful and important than simple mathematical ability."
"Knowing some basic models and trends that can be applied to data, I have been able to interpret other data much more easily. While I don't think I could go into data interpretation very thoroughly, I can definitely read a spreadsheet or graph and understand the analyses done on them and start to weed out which are appropriate for the given data and which are not. I have begun to get an idea of the relevance of certain data tests and how you can manipulate data to get the significance you need out of them. It is not as obvious as I used to think it was."
Data and/or presentations of data can be deceiving to someone with an untrained eye. That said, I feel like I have a leg up in being more discerning after taking this class.
"I feel like I have learned concrete skills to approach a dataset that I know nothing about and be able to draw some meaning from it. This is not something I felt super confident doing before this class."
"I've learned not only how to read/analyze data, but I've also learned about how important it is to be able to do so. Data literacy is something that should be taught from an early age."
"I have learned about many more ways to analyze data that I had never even considered before, and also learned that there are a lot of ways to analyze data that I still haven't considered, which is a long way from my starting point of wondering what in the world there could possibly be to do other than t-tests and a basic correlation test. I've also learned a lot about what the measures we use to analyze data actually mean (and don't mean)."