I have been talking to undergraduates about survey methodology. The students I talk to have learned either some social research methods or statistics. I think that many are interested in data science and/or big data.
From these conversations, I found it was useful to describe survey methodologists as "data quality specialists." Survey methodology is not a field that most undergraduates are even aware of. But when I started talking about how we evaluate the quality of data, I could see ears perking up. It reinforced for me the idea that the Total Survey Error perspective is valuable for Big Data.We can talk about nonresponse and measurement error in a coherent way.
Raising questions about the quality of the data, the need to understand the processes that generated those data, and methods for evaluation of the data were all ideas that seemed to resonate with undergraduates... well, at least some. It was energizing and exciting to speak with them. Hopefully they bring that energy to our field!
From these conversations, I found it was useful to describe survey methodologists as "data quality specialists." Survey methodology is not a field that most undergraduates are even aware of. But when I started talking about how we evaluate the quality of data, I could see ears perking up. It reinforced for me the idea that the Total Survey Error perspective is valuable for Big Data.We can talk about nonresponse and measurement error in a coherent way.
Raising questions about the quality of the data, the need to understand the processes that generated those data, and methods for evaluation of the data were all ideas that seemed to resonate with undergraduates... well, at least some. It was energizing and exciting to speak with them. Hopefully they bring that energy to our field!
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