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Using Entering Student Data to Estimate Campus Retention Rates. LINDA J. SAX Associate Professor & Associate Director of HERI University of California, Los Angeles May 31, 2005. Student-Right-To-Know Act. As of 1993, four-year institutions are compared on a six-year retention rate.

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using entering student data to estimate campus retention rates

Using Entering Student Data to Estimate Campus Retention Rates

LINDA J. SAX

Associate Professor & Associate Director of HERI

University of California, Los Angeles

May 31, 2005

student right to know act
Student-Right-To-Know Act

As of 1993, four-year institutions are compared

on a six-year retention rate

  • Ignores:
  • Stop-outs
  • Transfers
  • Differences between institutions (missions, resources)
  • Student background characteristics
      • Account for 2/3 variation in institutional degree completion rates
2000 heri retention study
2000 HERI Retention Study
  • 262 baccalaureate institutions
  • 56,818 students
  • 1994 CIRP Freshman Survey
  • 2000 Registrar’s Survey collected 4- and 6-year degree attainment data
slide4
Both retention measures (4-year and 6-year) highly dependent on student background characteristics
  • Strongest effects:
      • High school grades
      • SAT score
      • Gender
      • Race
slide7

How can we estimate an institution’s retention rate if we know the gender, high school grades and SAT scores of a college’s entering freshman class?

computing an expected retention rate
Computing an Expected Retention Rate

1. Compute for each student an expected probability of retention (Y-hat)

Formula 1: Y-hat = a + b1(HSGPA)

Formula 2: Y-hat = a + b1(HSGPA) + b2(SAT)

Formula 3: Y-hat = a + b1(HSGPA) + b2(SAT) + b3(Sex)

2. Compute mean Y-hat across all students

institutional effect
Institutional Effect =

Actual Expected

Retention - Retention Rate Rate

slide10

Major Historically

Research Black

University College

Actual

Retention = 35 36

Rate

slide11

Major Historically

Research Black

University College

Actual

Rate = 35 36

Expected

Rate = 64 22

“Effect” = -29 +14

4 year degree attainment formula 1
4-year Degree Attainment: Formula 1

Retention measure: Bachelor’s completion in 4 years

Input data considered: High school GPA

Expected retention rate = .0947 (GPA) - .1972

(HSGPA: A or A+ = 8; A- = 7; B+ = 6; B = 5; B- = 4; C+ = 3;

C or C- = 2; D or less = 1)

Examples: If A- average (GPA=7), probability = 47%

If C+ average (GPA=2), probability = 9%

4 year degree attainment formula 2
4-year Degree Attainment: Formula 2

Retention Measure: Bachelor’s completion in 4 years

Input data considered: High school GPA, SAT

Expected retention rate = .0670 (GPA) + .000522 (SAT) - .5633

Examples:

If A- average and 1300 SAT: Probability = 58%

If C+ average and 900 SAT: Probability = 11%

4 year degree attainment formula 3
4-year Degree Attainment: Formula 3

Retention Measure: Bachelor’s completion in 4 years

Input data considered: High school GPA, SAT, Sex

Expected retention rate =.0615 (GPA) + .000569 (SAT)

+ .0717 (Sex: Female) - .6879

Examples:

If female B student with 1200 SAT: Probability = 45%

If male B student with 1200 SAT: Probability = 37%

slide15

Dozens of CIRP Variables Predict Retention, including:

  • Parental income and educational level (+)
  • Financial aid and student loans (+)
  • Working for pay, working off campus (expectations) (-)
  • Propensity towards academic engagement (+)
  • Propensity towards extracurricular involvement (+)
slide16
Overall Retention Rate: 50%

Overall Prediction Using Formula 1: 37% (difference of –13%)

Overall Prediction Using CIRP Variables: 44% (difference of –06%)

Using CIRP Variables Greatly Improves the Accuracy of the Prediction