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Developmental Education in North Carolina Community Colleges

Developmental Education in North Carolina Community Colleges. Charles T. Clotfelter Helen F. Ladd* Clara Muschkin Jacob L. Vigdor Sanford School of Public Policy Duke University *hladd@duke.edu . Introduction and Summary.

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Developmental Education in North Carolina Community Colleges

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  1. Developmental Education in North Carolina Community Colleges Charles T. Clotfelter Helen F. Ladd* Clara Muschkin Jacob L. Vigdor Sanford School of Public Policy Duke University *hladd@duke.edu

  2. Introduction and Summary • We use policy variation across NC community colleges to examine effects of remediation on college success and other outcomes. • Findings: Remediation • Reduces probability of college success • Reduces the probability of passing a college level course in the remediated field • Has no adverse effects on short run college persistence (Some differential effects by prior achievement quartile, gender, and income )

  3. Policy context and conceptual foundation • North Carolina Community College System • 58 CCs (56 in this study) • No uniform test or policy for determining college readiness • About 48 percent of our sample takes remedial math and 37 percent remedial English • Possible functions of remedial education Developmental function Discouragement of students Diversion function

  4. Prior research Policy variation: Bettinger and Long (JHR 2009) – positive effects Ohio colleges, both 4-year and CC Restricted to students who took ACT Positive effects of remediation How relevant to CC students? Regression discontinuity studies- small or mixed effects Martorell and McFarlin (2011) Texas Calagno and Long (2008) Florida Scott-Clayton and Rodriguez (2012) How generalizable ? Experimental designs to look at specific programs- mixed effects Barnett et al. (2012); Visher et al, 2012

  5. North Carolina Data Linked student level admin data from NCCCS and NC public schools • CC students can be linked to their 8th grade test scores -- and various other variables. Sample. All 8th graders in 1999 who subsequently enrolled in a CC before 2006 (other than Wake and Mecklenburg)

  6. Initial Model Outcomeij = α + βCij + γXij + εij (i is student, j is college attended) Four outcomes : two related to probability of college success, two related to short run persistence C :enrollment in a math or reading developmental course, different levels (only one type of course in each equation) X: student variables, including quartile of 8th grade achievement distribution Parameter of interest is β

  7. Problems with initial model • Potential bias in estimate of β • Downward because of left out variables • Upward because of differential compliance • Confounding effects at the college level Solutions Use an instrument for actual enrollment in a developmental course Add community college fixed effects

  8. Construction of the instrument(s) For each student: • Use college-specific probability of enrollment that differs by the student’s position in the 8th grade achievement distribution (i.e. Q1, Q2, Q3 or Q4) – based on actual patterns in each college. • Use the college that is closest to the student’s high school rather than the community college actually attended . Example. The value of the instrument for a students whose high school is closest to Wilson CC would differ depending on the student’s 8th grade achievement quartile as follows: Q1 = 0.91 , Q2 = 0.74, Q3 = 0.63, Q4 = 0.10

  9. Evaluation of the instruments First stage regression: Cijk = ak + bZk + cXijk+ eijk (i is student, j is college attended, k is closest college) Z is the relevant instrument. Coefficients on instruments are typically in the range of 0.6 to 0.8, all with small standard errors, sigh large F statistics in all cases. => The instruments are strong

  10. Testing for developmental function of remedial education Effective requirement of remedial education reducesprobability of college success MathEnglish Any develop -0.198* Any develop –0.155** Course <= 70 -0.227*** Course <=85 -0.174*** Course <= 60 -0.179*** (Reduced form estimates)

  11. Developmental function (cont.) Effective requirement of remedial education reduces probability of ever passing a college level course in the remediated subject. Math English Any develop -0.211** Any develop –0.225*** Course <= 70 -0.266***Course <=85 -0.235*** Course <= 60 -0.222*** (Reduced form estimates)

  12. Testing discouragement No adverse effects on short run persistence (based on two measure of persistence). => Main function of remedial education is to divert students from college level courses.

  13. Effects by subgroup Remediation has more negative effects on college outcomes for : • Students who are in the lowest 2 quartiles of the 8th grade achievement distribution in math; lowest quartile in English • Female students relative to male students in both math and English (but females more likely to succeed than males) No differential effect of remediation by poverty status (as measured by FRP lunch in school)of students (but poor non-remediated students are less likely to succeed than poor students)

  14. Conclusions • No support for the developmental function of CC remediation. (Consistent with most studies other than Bettinger and Long, 2009) • No adverse effects on short run persistence • Main effect is to divert students away from college level courses. May be a reasonable thing to do. Policy implication: Assure better skills in high school Cautionary note. Our results apply only to traditional age students.

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