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Playing Well with Others: Can We Apply Prior Survey Data to New Problems?

Length
45 minutes
Track
Privacy and Security
Higher Education
Data Analytics for Decision Making
Type
Roundtable

Educational institutions conduct a lot of surveys, leading to massive amounts of data and concerns about over-surveying. Student surveys ask about experiences as first-year, transfer, or international students; learning abroad; being employed on campus; and feeling safe and respected, to name just a few topics. Survey results then guide program improvement decisions (e.g., student orientation, department or campus-wide training). Plus, student ratings of teaching are common practice: these results also inform decisions (e.g., tenure/promotion, improving instruction, and student course selection). Meanwhile, institutions convene committees for mission-critical strategic improvements, many on topics that could benefit from insights embedded in existing data. At the U of M, some committees are becoming aware of data and beginning to consider whether analysis of those data sets might help guide direction. But awareness is not widespread, and using this data is rarely straightforward. Complexities include institutional policy, individual resistance to sharing, data access, varying data definitions, appropriate use of data, and data privacy compliance. This session offers a facilitated discussion on using existing data. How can committees learn of previous surveys? How can data owners learn of initiatives that may benefit from their data? How can we encourage collaboration and data sharing aligned with data privacy and best practices?

Speaker(s)

Stephanie Klein, University of Minnesota