A Rubric Accompanying the Student Success Analytics Framework
Practitioners across campus can use a newly developed rubric to help create and sustain student success initiatives.
Maureen A. Guarcello has more than 20 years of higher education experience, with research and practice focused on the ways predictive and learning analytics inform student success interventions and higher education policy. Before joining San Diego State University, Maureen earned her PhD from the University of San Diego, where she was a full scholar and graduate research assistant.
Maureen serves as the director for SDSU's Program Evaluation, Compliance, and Assessment unit within Student Affairs and Campus Diversity. The research Maureen conducts with SDSU colleagues and education partners recognizes the presence of bias in student success interventions and risk assessment. Her work focuses on machine learning and statistical methods to reduce bias in the data, ultimately producing more accurate and equity-minded student support interventions for students.
When she is not geeking out on data and technology, Maureen is an avid runner, music lover, and San Francisco Giants fan.
Practitioners across campus can use a newly developed rubric to help create and sustain student success initiatives.
This framework introduces users to the four central components of a student success analytics initiative—Preparedness, Outcomes, Analysis, and Decisions—providing a shared point of reference for institutional stakeholders.
In a sea of data, the use of student success analytics may unintentionally result in consequences that benefit some students while harming others.
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