University First-Time-in-College Students’ Mathematics Placement and Outcomes - Leadership Response to Local Data

Oct 15, 2026

Data-driven decision making strengthens educational leadership by translating local evidence into improved student success. This study examines how a four-year university used existing student data to address high first-time-in-college withdrawal/failure rates in initial algebra courses and their negative impact on retention and completion. Analysis across four student cohorts explored placement practices, identified potential at-risk learners, and assessed policy options to raise early math pass rates.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

AccessFree to download

Introduction

Literature Review

College Math Placement Practices

College Math Placement Practices (Placement Criteria and Outcomes)

University First-Time-in-College Students’Mathematics Placement and Outcomes: Leadership Response to Local Data Jenifer J. Hartman University of South Florida St. Petersburg Radford Janssens University of South Florida St. Petersburg Karina K. R. Hensberry University of South Florida St. Petersburg Data-driven decision making is a critical leadership skill. This study describes how leadership at a four-year university used extant data to improve student outcomes. The University identified the high rate of first-time-in-college (FTIC) student withdrawal/failure in initial algebra courses as having a detrimental effect on other student success metrics such as student retention and completion rates. The study was initiated to determine how analysis of extant student data could enable leaders to better understand the problem, identify ways in which university policies and/or practices could be modified to increase students’pass rates in their initial math courses, and ultimately result in improved student outcomes. Data from four cohorts of first time in college students were analyzed to better understand the effects of the university placement practices on student outcomes, and potentially identify students who may be at-risk of failure to provide early intervention. The initial results indicate under-placement of female students in lower math courses at a statistically significant level, and potential use of students’ high school GPA as an earlywarning indicator of failure. The study highlights the importance of leaders monitoring and analyzing local data to assess the impact of current policies and practices on student outcomes. Keywords: data-driven decision making, leadership, mathematics courses, placement ICPEL Education Leadership Review, Vol. 21, No. 1– December, 2020 ISSN: 1532-0723 © 2020 International Council of Professors of Educational Leadership One of the hallmarks of effective educational leadership is continuous process improvement to increase student success (Gill, Bordon, & Hallgren, 2014; Mandinach, 2012) . Educational settings vary in many ways including, but not limited to, student composition and needs, instructors’experience and expertise, and local resources. Leadership decision-making and practice must adapt to individual institutional needs, and therefore, must be rooted in local information and data. This study describes how leadership at a four-year university used extant data in a datadriven decision making process to improve student outcomes. The University identified the detrimental effect of first-time-in-college (FTIC) student withdrawal/failure in initial algebra courses on other student success metrics such as student retention and completion rates, which were considerably lower than for other campuses in the regional system. This study was initiated to determine how analysis of extant student data could enable leaders to better understand the problem, identify ways in which university policies and/or practices could be modified to increase students’ pass rates in their initial math courses, and ultimately result in improved student outcomes. It builds on research regarding difficulties inaccurate FTIC math placement primarily at the community college level (Bracco et al., 2014; Burdman, 2011; Hodara & Cox, 2016; Jaggars & Hodara, 2013; Scott-Clayton, Crosta, & Belfield, 2014).), and research on the use of early warning indicators of failure for early intervention in K- 12 schools (Allensworth & Easton, 2007; DePaoli et al., 2015; Hartman, Wilkins, Gregory, Gould,& D’Souza, 2011) . In addition to improving FTIC student success, this study was also intended to provide an example of a four-year university analysis of extant data to inform policies and practices. Literature Review College and career readiness has been a major focus in K-12 education for the last decade. Oneof the goals of the federal initiative Race to the Top (2009) was that all high school students gr

FAQs

What leadership problem does the study address?

It addresses high withdrawal/failure rates among first-time-in-college students in initial algebra courses and how that harms other success metrics such as retention and completion.

How did the university use data in the study?

Leaders analyzed existing student data from four cohorts to understand effects of placement practices and to identify students who may be at risk of failure for early intervention.

What early indicators did the initial results suggest?

The study indicates statistically significant under-placement of female students in lower math courses and suggests high school GPA may function as an early-warning indicator of failure.

Oct 15, 2026

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