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 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 in the Mobile Technology Learning Center. Situated in the Academic Technologies Research and Initiatives area within the Information Technology Division, Maureen also holds a special appointment in Analytic Studies and Institutional Research, where she is working on a student data lake project and several data informed strategic planning initiatives.
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 indicators in high challenge courses at SDSU. When she is not geeking out on data and technology, Maureen is an avid runner, music lover, and an unapologetic 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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