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Using Analytics to Predict & Improve Sophomore Retention

10% don't return for a 5th term

Location

Online

Date & Time

October 14, 2022, 12:00 pm1:00 pm

Description

Note: The virtual meeting URL will be added here on the day of the event.



Second year retention rates (i.e., fifth semester) are a key to increasing graduation rates.  And for good reason--approximately 10 percent of each cohort of new freshmen do not return for their third year.  To better support student success and enrollment, the Data Science Team has worked with HelioCampus to build very accurate models that predict second year retention at the beginning of their third semester.  The results from the initial run of these models have now been deployed.  Robert Carpenter and Len Mancini, of DoIT and the Provost's Office, and Delana Gregg, from the Division of Undergraduate Academic Affairs (DUAA), will lead a discussion of how the models work, the key inputs into them, where to find the results, and (importantly) how we might act on them.

Also, this workshop is part of the Fall 2022 data science and learning analytics workshops. More info.

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