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Activity Number:
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90
- Invited EPoster Session
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Type:
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Invited
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Date/Time:
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Sunday, July 28, 2019 : 8:30 PM to 10:30 PM
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Sponsor:
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Section on Statistical Learning and Data Science
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Abstract #306926
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Title:
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Making an Impact in an Institutional Research Office: On Data Champions and Machine Learning
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Author(s):
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Richard Levine* and Juanjuan Fan and Joshua Beemer and Jeanne Stronach
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Companies:
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San Diego State University and San Diego State University and San Diego State University and San Diego State University
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Keywords:
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predictive analytics;
STEM;
Higher Education Research;
data science;
random forest
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Abstract:
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As a strategy to support data-informed decision making at SDSU Analytic Studies & Institutional Research (IR) established a Statistical Modeling Group (SMG) within its operation. SMG is a collaborative team of machine learning experts from the Stat Dept and IR data management and visualization experts tasked with developing and applying predictive analytics methods to solve institutional effectiveness problems. In this poster, we will highlight the role of SMG on our campus. Focusing on a SMG success story in STEM program retention and graduation success, we will 1) introduce the predictive analytics infrastructure and machine learning methods developed for student success efficacy studies; 2) show novel visualizations and dashboards developed for STEM advisors and campus administrators; 3) outline the Data Champions program instituted to expand University data capabilities and leverage our analytic tools to inform SDSU efforts to improve student success metrics; and 4) present our vision for Statistical Modeling Groups in IR units as an effective strategy for training Statistics/Data Science graduate students and delivering actionable information to campus stakeholders.
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Authors who are presenting talks have a * after their name.
