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Tatiana Melguizo & Bo Kim (USC) Hans Bos (American Institutes for Research)

Using a Regression Discontinuity Design to Estimate the Impact of Placement Decisions in the Los Angeles Community College District. Tatiana Melguizo & Bo Kim (USC) Hans Bos (American Institutes for Research) George Prather (LACCD, Retired)

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Tatiana Melguizo & Bo Kim (USC) Hans Bos (American Institutes for Research)

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  1. Using a Regression Discontinuity Design to Estimate the Impact of Placement Decisions in the Los Angeles Community College District • Tatiana Melguizo & Bo Kim (USC) • Hans Bos (American Institutes for Research) • George Prather (LACCD, Retired) • Presented at the Research and Planning Group conference, April 2, 2013 • This research is funded by a grant from the U.S. Department of Education’s Institute of Education Sciences (IES).

  2. The Problem • Community college students have widely varying initial skill levels and the majority arrive with substantial remedial needs in math • Colleges have to offer classes to meet the needs of their diverse students and have to keep heterogeneity in the classrooms manageable • Placing students incorrectly can reduce the likelihood that students succeed

  3. Math Placement in the Los Angeles Community College District About sixty percent of the entering students need at least one remedial class before taking a math class that counts towards a degree

  4. Some Controversy about Impact of Remedial Education • Some research finds that remedial education provides the preparation necessary for students to succeed in college (Boylan, Bliss, & Bonham, 1994; 1997; Lazarik, 1997) • Critics contend that remedial education may hold students back and be ineffective (Calcagno & Long, 2008; Martorell & McFarland, 2011) • We argue that it depends on how students are placed and how cut points between levels are set

  5. Focus on Cut Points • Math faculty set the cut points between the different levels based on who applies and how their course offerings are distributed • If the cut points are too high, too many students languish in remedial courses • If the cut points are too low, too many students fail higher-level courses and present a challenge to the instructors • Getting the cut points just right is important

  6. Changing Cut Scores

  7. Different Pathways to Success(Arithmetic vs. Pre Algebra) Next course Success Placed in Pre-Algebra Enroll in Pre-Algebra Failure No enrollment Test Success Placed in Arithmetic Enroll in Arithmetic Failure

  8. Success Above Cut Point Next course Success Placed in Pre-Algebra Enroll in Pre-Algebra Failure No enrollment Test Success Placed in Arithmetic Enroll in Arithmetic Failure Direct but academically challenging

  9. Success Below Cut Point Next course Success Placed in Pre-Algebra Enroll in Pre-Algebra Failure No enrollment Test Success Placed in Arithmetic Enroll in Arithmetic Failure A less academically challenging but more time-consuming trajectory

  10. The Impact Question • For a student at the margin, does the longer road to success produce better results? • Is greater likelihood of success worth the extra time and effort? The Policy Question • Are cut points between math placement options set correctly?

  11. Using Regression Discontinuity to Evaluate Placements • Regression discontinuity analysis is the strongest non-experimental method to estimate causal effects • It depends on a continuous forcing variable and an exogenously established cut point • Those two conditions are present in this situation

  12. Regression Line Outcome Arithmetic Impact Pre-Algebra Placement Test Score

  13. Analytical Details • Not everyone follows the placement test’s recommendation • Some students enroll below or above their placement level • Compliance was high • Impacts are estimated using discrete time survival analysis implemented within a regression discontinuity framework • The density of the forcing variable around the cut point was normal (confirmed with McCrary test)

  14. The Impact of Placement Decisions Needs to be Observed Over Time

  15. The Impact of Placement Decisions Needs to be Observed by College

  16. The Impact of Placement Decisions Needs to be Observed by Level

  17. Students are not Being Placed Effectively in the Higher Levels (Elementary versus Intermediate Algebra)

  18. Students Placed in Lowest Levels Accumulate More Degree Applicable Credits

  19. Placement in Less Effective in Terms of Transfer Degree Credit Accumulation

  20. Conclusions • Cut points between elementary algebra and intermediary algebra may be set too high as marginal students do worse in elementary algebra • At lower levels the cut points appear to be in the right place • For students placed in lower levels of math sequence, there is no penalty in terms of accumulating 30 degree applicable credits • For students placed in higher levels there is a penalty in terms of completing 30 transfer credits

  21. THANK YOU! Questions Tatiana Melguizo melguizo@usc.edu http://www.usc.edu/dept/education/rossier_faculty/tmelguizo/

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