Measuring What Matters: The UW Flexible Option's Framework to Measure Success from the Student Vantage Point

Measuring What Matters: The UW Flexible Option's Framework to Measure Success from the Student Vantage Point

Aaron Brower, Sandra Kallio, Rebecca Karoff, Mark Mailloux, David Schejbal
DOI: 10.4018/978-1-5225-0932-5.ch014
(Individual Chapters)
No Current Special Offers


This chapter demonstrates that competency-based education requires a different set of student success metrics, and introduces the metrics framework developed by and for the University of Wisconsin's UW Flexible Option (UW Flex). UW Flex is a direct assessment competency-based self-paced model for earning degrees and certificates from institutions in the UW System. It was supported by a grant from Lumina Foundation to develop a competency-based education blueprint for success and includes a set of student-centric metrics meaningful to the model, the curriculum, and the students who are being served in Flex programs. The framework defines student success as students moving through programs at their own pace, demonstrating mastery of subject matter, and meeting academic goals. Program-level metrics aggregate each of these three student-level metrics to provide useful information about the success of a program. The authors also build the case that strategic management of resources is required to overcome challenges inherent in implementing the UW Flexible Option metrics framework.
Chapter Preview


Long-held measures of student success, such as retention and graduation rates, are rooted in the traditional academic term. The credit hour has driven determinations of student success in American higher education for more than a century, deeply affecting the architecture, delivery, and accountability of post-secondary academic programs (Laitinen, 2012). There are powerful reasons why conventional success metrics are grounded in the credit hour. Factors include the higher education regulatory environment, entrenched academic calendars, and visibility to policy-makers and the general public.

The paradigm of credit hour-based metrics was established in the early 1900s to measure faculty workload, primarily for pension purposes. Over time, the paradigm evolved in imperfect ways to gauge student success, student learning, and a range of other institutional functions from admissions to financial aid. Much of the evolution of the credit hour into a proxy for student learning emerged from the regulatory environment. The U.S. Department of Education (“the Department”) adopted the credit hour to standardize the unit of transaction between students and their institutions of higher learning, equating time with learning. Credit hour-based metrics have been particularly well suited for traditional residence-based colleges and universities, with physical classrooms and traditional students in them, as the dominant model for the latter half of the 20th century.

The Department’s data center, the National Center for Education Statistics’ Integrated Postsecondary Education Data System (IPEDS), tracks student success measures that are determined almost exclusively on the credit hour ( The IPEDS obtains the required, standardized higher education data from every college, university, and technical and vocational institution that participates in federal student financial aid programs. Chief among their data collection efforts is an annual survey that collects data on time- and cohort-defined retention and graduation rates (Institutional Retention and Graduation Rates for Undergraduate Students, 2014). The Higher Education Act of 1965, as amended, requires institutions participating in federal student aid programs to report data on enrollments, program completions, graduation rates, faculty and staff, finances, institutional prices, and student financial aid. These data are made available to students, parents, researchers, and the public.

The measures that IPEDS gathers tend to be directed toward program and institutional success rather than individual student-level progress and success. Some examples of success as determined by credit hour-based metrics include:

  • High first- to second-year retention rate among first-time, full-time students.

  • High four-, five- and six-year graduation rates.

  • Selectivity represented by various admissions yields.

  • High financial aid/low cost to attend.

  • Core revenues per full-time equivalent by source.

  • Abundant on-campus opportunities for student engagement.

  • High percentage of teaching staff with a terminal degree.

Other more public facing college evaluation systems also base their assessments on IPEDS data. In response primarily to state and federal policy-makers, for example, the Voluntary System of Accountability (VSA) is a recent initiative by public four-year universities to supply clear, accessible, and comparable information on the undergraduate experience through a web-based report called “The College Portrait” ( This report predominantly provides IPEDS data. VSA also includes indirect measures of student learning in critical thinking, which is a step toward bringing student learning into the reporting environment.

Key Terms in this Chapter

Competency-Based Education: An educational method focused on learning outcomes and the demonstration of knowledge and skills by students rather than on seat time and traditional credit hours.

Non-Term: Student enrollment not based on a time period with a set start and stop of academic work for a student cohort.

Direct Assessment: The specific type of competency-based education based on the direct measurement of what a student knows and can do, regardless of the source of that knowledge and skills.

Competencies: Learning outcomes—including knowledge, skills, attitudes, and behaviors—a student is expected to master.

Complete Chapter List

Search this Book: