Predicting Success in College: The Importance of Placement Tests and High School Transcripts

This paper uses student-level data from a statewide community college system to examine the validity of placement tests and high school information in predicting course grades and college performance. It considers the ACCUPLACER and COMPASS placement tests, using two quantitative and two literacy tests from each battery. The authors find that placement tests do not yield strong predictions of how students will perform in college. Placement test scores are positively—but weakly—associated with college grade point average (GPA). The correlation disappears when high school GPA is controlled for. Placement test scores are positively associated with college credit accumulation even after controlling for high school GPA. After three to five semesters, a student with a placement test score in the highest quartile has on average nine credits more than a student with a placement test score in the lowest quartile. In contrast, high school GPAs are useful for predicting many aspects of students' college performance. High school GPA has a strong association with college GPA; students' college GPAs are approximately 0.6 units below their high school GPAs. High school GPA also has a strong association with college credit accumulation. A student whose high school GPA is one grade higher will have accumulate approximately four extra credits per semester. Other information from high school transcripts is modestly useful; this includes number of math and English courses taken in high school, honors courses, number of F grades, and number of credits. This high school information is not independently useful beyond high school GPA, and collectively it explains less variation in college performance. The authors also calculate accuracy rates and four validity metrics for placement tests. They find high "severe" error rates using the placement test cutoffs. The severe error rate for English is 27 to 33 percent; i.e., three out of every ten students is severely misassigned. For math, the severe error rates are lower but still nontrivial. Using high school GPA instead of placement tests reduces the severe error rates by half across both English and math

Should Community College Students Earn an Associate Degree Before Transferring to a Four-Year Institution?

Community colleges are the postsecondary entry point for thousands of students each year in the United States. Over 80 percent of these students indicate a desire to earn a bachelor’s degree or higher (Horn & Skomsvold, 2011). However, according to studies by the National Student Clearinghouse, only about 15 percent of all students who start at two-year public colleges earn a bachelor’s degree within six years (Shapiro et al., 2012). Although the expected pathway for community college students seeking a bachelor’s degree includes earning an associate degree, little is known about the impact of earning an associate degree on bachelor’s degree completion. This paper thus seeks to answer the following question: Are community college students who earn an associate degree before transferring to a four-year college more likely to earn a bachelor’s degree? Using data on students in one state who entered community college and then transferred, we find large, positive apparent impacts of earning the transfer-oriented (e.g., Associate in Arts) associate degree on the probability of earning a bachelor’s degree within four, five, and six years. However, we do not find any apparent impact associated with earning one of the workforce-oriented (e.g., Associate in Applied Science) degrees that are awarded by programs typically designed for direct labor market entry. This is an important distinction, as all associate degrees are not equal in their potential impacts on future baccalaureate completion

Characteristics of Early Community College Dropouts

Students who drop out of community college are expensive. Over a five-year period, federal, state, and local authorities spent about $4 billion on community college students who began as first-time, full-time, degree-seeking students but did not return for a second year of school (Schneider and Yin, 2011). In an era where the policy focus is on accountability and efficiency, improving first-year persistence is a critical goal. For colleges to develop effective dropout prevention strategies, it is necessary to have a clear picture of who these early dropouts are. This report aims to identify distinguishing characteristics of this group by analyzing six years of transcript data on 14,429 first-time college students who in 2005 and 2006 enrolled at one of five community colleges in a single state. Of these students, 28 percent never returned to the same college after their first semester. This outcome represents the most common enrollment and exit pattern among students in the sample—more students dropped out en masse after the first term than at any other time. The majority of these students never attended any college again. This analysis departs from other work on dropout and persistence in two important ways: It includes part-time students (who constitute a majority of first-time enrollees at community colleges), and it focuses on very early dropouts—those who enrolled for one term of study but never returned to the same college for another term. For the purposes of this report, these early dropouts are compared with a group called early persisters (67 percent of students in the sample)—those who enrolled at least twice in the first four enrollment terms (fall, spring, summer, and fall)

Intensity and Attachment: How the Chaotic Enrollment Patterns of Community College Students Affect Educational Outcomes

This study examines the relationship between community college enrollment patterns and two successful student outcomes—credential completion and transfer to a four-year institution. It also introduces a new way of visualizing the various attendance patterns of community college students. Patterns of enrollment intensity (full-time or part-time status) and continuity (enrolling in consecutive terms or skipping one or more terms) are graphed and then clustered according to their salient features. Using data on cohorts of first-time community college students at five colleges in a single state, the study finds that, over an 18-semester period, ten patterns of attendance account for nearly half the students, with the two most common patterns characterized by enrolling in one semester full-time or one semester part-time. Among the remaining students who persisted, there is astounding variation in their patterns of enrollment. Clustering these patterns reveals two relationships: the first is a positive association between enrollment continuity and earning a community college credential, and the second is a positive association between enrollment intensity and likelihood of transfer

Trends in Enrollment Patterns Among Community College Students

Community college programs are designed around regularity. Degrees and certificates are often branded with an expected or “regular” completion time (e.g., two-year associate degree, one-year certificate), and suggested course sequences often assume this underlying time structure. In reality, however, relatively few students finish their course sequences and programs of study so quickly. Instead, students generate a diverse array of attendance patterns that may include periods of non-enrollment and shifts in part-time/fulltime status. Indeed, the notion of a regular enrollment pattern is quickly challenged through analysis of data on how students actually attend community college. Using a large dataset, this report (based on a longer paper—see Crosta, 2013) reveals the diversity of enrollment patterns among community college students as they progress along their education pathways. It also demonstrates a novel graphical technique for displaying large numbers of student enrollment patterns in terms of continuity (whether or not a student enrolls in a given semester) and intensity (whether a student enrolls part-time or full-time)

What Can Student Right-to-Know Graduation Rates Tell Us About Community College Performance?

This paper examines the validity of the Student Right-to-Know (SRK) graduation rates as measures of community college performance. The SRK rates are the only performance measures available for every undergraduate institution in the U.S. Many community college educators argue that the SRK rates give an inaccurate picture of community college outcomes. Using data from national longitudinal surveys of college students, we examined criticisms commonly leveled against the SRK measures and found that the SRK rates do indeed yield a biased and potentially misleading picture of individual community college student outcomes. We then analyzed the usefulness of the SRK rate as a measure of relative institutional performance. Specifically, we considered whether using different measures of performance would result in substantially different rankings of Florida’s 28 community colleges. Contrary to initial expectations, we found that the relative performance of the colleges did not change substantially as different students or outcomes were used. Even after we adjusted for student characteristics that might affect outcomes, the college rankings were still fairly stable

The Value of Student Right-to-Know Data in Assessing Community College Performance

Traditionally, community colleges were judged on their number of enrollments and their ability to provide postsecondary education to a wide variety of students. Recently, however, state and federal policymakers have become increasingly concerned with student outcomes, and some states have even begun to consider linking the funding of community colleges to their performance on student outcome measures. In 1990, Congress passed the Student Right-to- Know (SRK) and Campus Security Act. It requires that all colleges report graduation rates to the National Center for Education Statistics (NCES) in order for their students to receive federal financial aid. These Student Right-to-Know graduation rates are part of the Integrated Postsecondary Education Data System (IPEDS). The SRK rates are the only performance measures available for virtually every undergraduate institution in the nation, including community colleges, but critics assert that the rates understate the success of community colleges in several important ways

What Can Student Right-to-Know Graduation Rates Tell Us About Community College Performance?

This paper examines the validity of the Student Right-to-Know (SRK) graduation rates as measures of community college performance. The SRK rates are the only performance measures available for every undergraduate institution in the U.S. Many community college educators argue that the SRK rates give an inaccurate picture of community college outcomes. Using data from national longitudinal surveys of college students, we examined criticisms commonly leveled against the SRK measures and found that the SRK rates do indeed yield a biased and potentially misleading picture of individual community college student outcomes. We then analyzed the usefulness of the SRK rate as a measure of relative institutional performance. Specifically, we considered whether using different measures of performance would result in substantially different rankings of Florida’s 28 community colleges. Contrary to initial expectations, we found that the relative performance of the colleges did not change substantially as different students or outcomes were used. Even after we adjusted for student characteristics that might affect outcomes, the college rankings were still fairly stable

Can Community Colleges Afford to Improve Completion? Measuring the Costs and Efficiency Effects of College Reforms

Community colleges are under pressure to increase completion rates and efficiency despite limited evidence of the economic consequences of different reform strategies. We introduce an economic model of student course pathways linked to college expenditures and revenues. Using detailed data from a single college, we calculate baseline efficiency and differences in efficiency for students who follow different pathways. We simulate changes in output, expenditures, revenues, net revenues, and efficiency assuming that the college meets particular performance targets. Findings indicate substantial differences in efficiency across pathways and significant differences in efficiency across strategies to help students complete college. They also suggest that increasing the completion rate is difficult and typically requires additional resources beyond the costs of implementing particular strategies. The model has wide practical application for community colleges

Improving the Targeting of Treatment: Evidence from College Remediation

At an annual cost of roughly $7 billion nationally, remedial coursework is one of the single largest interventions intended to improve outcomes for underprepared college students. But like a costly medical treatment with non-trivial side effects, the value of remediation overall depends upon whether those most likely to benefit can be identified in advance. This NBER working paper uses administrative data and a rich predictive model to examine the accuracy of remedial screening tests, either instead of or in addition to using high school transcript data to determine remedial assignment. The authors find that roughly one in four test-takers in math and one in three test-takers in English are severely mis-assigned under current test-based policies, with mis-assignments to remediation much more common than mis-assignments to college-level coursework. Using high school transcript information—either instead of or in addition to test scores—could significantly reduce the prevalence of assignment errors. Further, the choice of screening device has significant implications for the racial and gender composition of both remedial and college-level courses. Finally, if institutions took account of students’ high school performance, they could remediate substantially fewer students without lowering success rates in college-level courses