Faculty Scholarly Dissemination Grants




Movement Science Department


College of Liberal Arts and Sciences

Date Range



Physical Sciences and Mathematics


Abstract A Data Driven Advising Model for Student Retention and Success: A Pilot Programs Initial Steps Undergraduate advising has been identified as a key strategy in student retention and success. Current trend in advising is centered on a first year learning experience component aimed to increase students success in higher education as measured by retention and time to graduation. Current research and insights using data analytics has shown that attrition rates in the United States is trending upward with an increase of 1.5% for second and third year students while first year attrition rates have decreased by 2%. Further, 29% of student credit hours consist of coursework that does move the student to degree completion. This coursework, electives not in general education or the major, lost transfer credits, failed, withdrawn courses or zero credit, increases students costs and diverts university resources. The session describes the use of data analytics and technology to develop progress indicators for each academic program at Grand Valley State University. These indicators include: identification of courses most critical to complete early so that a student can progress through the major; identification of key predictors (customized success markers) which are those courses plus the grade achieved that determine whether a student stays in the major; identification of students who are off track in their academic progress (these are the B and C students who are seldom noticed; and metrics to show students majors that best match their academic achievement. Academic advising models differ widely among universities. While some rely on faculty as the primary advisors, others use professional advisors or some combination of professional and faculty advisors when working with undergraduates. Grand Valley State Universitys shared model of academic advising consists of teamwork among professional and faculty academic advisors. Initial training in the use of the data analytics for each unit is underway and a report on the initial progress of this new approach will be provided.

Conference Name

Hawaii International Conference on Education

Conference Location

United States

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