Role of College Decisions in Multiple Measures
Seven colleges in the State University of New York (SUNY) system developed multiple measures placement systems that used algorithms to weight different factors (placement test scores, high school GPAs, time since high school graduation, etc.) according to how well they predicted student success in college-level math and English courses. Researchers then simulated placement and success rates at each college as a basis for faculty decisions on where to establish cut scores that would distinguish students ready for college-level courses from those needing developmental education.
Math faculty chose more conservative cut scores than English faculty. As a result, the proportion of students whose placement determinations differed from what they would have been under the single test based system was greater in English than in math; 16 percent of students placed into a higher-level math course (i.e., college-level course) than would have been expected under the single test system, and 44 percent placed into a higher-level English course. It followed that impacts on course outcomes in English were larger than those in math, including enrollment and completion of college-level courses. This Points of Interest shows that college decisions influence the impact multiple measures systems can have on student outcomes, and that colleges should consider cut scores that allow more students into college-level courses.