Leveraging survey data and predictive analytics to support first-year students

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dc.contributor.authorBombaugh, M.
dc.contributor.authorCole, J.
dc.date.accessioned2019-09-18T20:23:14Z
dc.date.available2019-09-18T20:23:14Z
dc.date.issued2019-02-17
dc.descriptionPresented at the 2019 Annual Conference on the First-Year Experience in Las Vegas, NV.
dc.description.abstractThis session will discuss the emerging trend of using predictive data to identify and support first-year students. For several years, USF-Tampa has been using an in-house persistence model to identify 10-12% of new first-year students at risk of not persisting to the second year. In Fall 2016, USF incorporated BCSSE data into the predictive model. BCSSE Advising Reports and results are shared with academic advisors, first-year seminar instructors, and housing personnel who provide targeted interventions for these students. BCSSE data not only strengthened the statistical model, but also identified which BCSSE variables were significant predictors of first-year persistence.
dc.identifier.urihttps://hdl.handle.net/2022/24111
dc.publisherAnnual Conference on the First-Year Experience
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleLeveraging survey data and predictive analytics to support first-year students
dc.typePresentation

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