Research suggests that the standardized tests used by most institutions to place students into either developmental education or college-level courses do not always accurately determine which students will benefit from developmental education. CAPR’s assessment study addresses the following questions:
- How can colleges improve upon current assessments or assessment practices to make sure students are placed into appropriate-level courses?
- What are the effects of alternative assessment and placement strategies on students’ overall academic performance, persistence, and progress toward college degrees?
The five-year study is conducted in collaboration with community colleges from the State University of New York (SUNY) system that are interested in modifying their assessment procedures.
The Study Design
This random assignment study evaluates a “data analytics” placement method whereby colleges use multiple measures to predict student performance in college-level math and English courses. In addition to placement test scores, these predictive measures may include high school GPA, high school course-taking patterns, and noncognitive assessments. Data on these measures will be used in a predictive model, developed in collaboration with the colleges. A decision rule can then be used to assign students to college-level math and English courses or developmental courses in math, reading, and writing.
Students entering participating colleges in the fall of 2015 through the spring of 2016 will be randomly assigned to be placed either: (1) using the new decision rule, or (2) according to existing placement practices. A random assignment design is ideal for this study because any differences in later outcomes can be attributed to the way in which students were placed. Students will then be tracked for up to four semesters following placement to learn about their subsequent performance in college. The outcomes of primary interest will be completion of the first college-level courses in the relevant areas and total college-level credits earned.
- Multiple Measures Assessment for Placement: Understanding Their Construction and Implementation in a Policy Context
- Using Multiple Measures to Improve Placement Accuracy in Community Colleges
- Multiple Measures Assessment for Placement: How It Looks in the Real World
- Emerging Student Assessment and Placement Systems: Implementation and Research Using a Data Analytics Approach