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Institutional and Student Characteristics that Predict Graduation and Retention Rates Braden J. Hosch, Ph.D. Director of Institutional Research & Assessment.

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Presentation on theme: "Institutional and Student Characteristics that Predict Graduation and Retention Rates Braden J. Hosch, Ph.D. Director of Institutional Research & Assessment."— Presentation transcript:

1 Institutional and Student Characteristics that Predict Graduation and Retention Rates Braden J. Hosch, Ph.D. Director of Institutional Research & Assessment November 4, 2008 North East Association for Institutional Research Annual Meeting Providence, RI This presentation and paper are online at

2 Overview Impetus for Study – Institutional Findings Methodology Correlations and Major Factors in Isolation Results from Regression Analyses Implications

3 Caveats Graduation/retention rates of full-time, first- time students have serious limitations as metrics Institutions participating in data sharing consortium have a special interest in progress rates Institutional metrics include only students who enroll at these institutions

4 Institutional Profile: Central Connecticut State University Public – part of Connecticut State Univ. System Carnegie 2005 Master’s-Larger Programs New Britain, CT (Hartford MSA) Fall 2008 Enrollment: 12,233 headcount (9,906 undergraduate, 23% residential); 9,429 full-time equivalent enrollment 52% female; 17% minority Full-time, first-time students: 1,303 (57% residential) Full-time, new transfer students: 779 Six-year graduation rates: 46% full-time, first-time students entering F ‘02 57% transfer students (full-time upon entry F ‘02)

5 CCSU Six-Year Graduation Rates and One-Year Retention Rates

6 CCSU Six-Year Graduation Rates Disaggregated (Entry F’99-F’01)

7 Graduation Rates of FT, FT Students by Number of Course Grades of D, F, or W Full-Time, First-Time Students Entering CCSU in Fall 2001

8 Methodology Data requested from Consortium for the Study of Retention Data Exchange (Appendix 3) for Full-Time, First-Time Cohort Entering Fall 2001 Institutions missing data about HS performance excluded Supplemented with Data from IPEDS Peer Analysis System

9 Institutions in Study Population Carnegie ClassificationPrivatePublicTotal Baccalaureate-Associate's1 01 Baccalaureate-General Baccalaureate-Liberal Arts3912 Others 022 Master's I Master's II10515 Doctoral/Research Intensive (DRI) Doctoral/Research Extensive (DRE)78996 Grand Total

10 Correlations with Six-Year Graduation Rates and Other Progress Rates Factors Related to 6-Year Graduation RateN Pearson’s RR2R2 Current Cohort’s Five-Year Graduation Rate Previous Cohort’s Six-Year Graduation Rate Current Cohort’s One-Year Retention Rate (Fall to Fall)

11 Relationship Between Six-Year Graduation Rates and One-Year Retention Rates

12 Factors that Correlate with Six- Year Graduation Rates Factors Related to 6-Year Graduation RateN Pearson’s RR2R2 SAT (Math + Verbal) or ACT Composite Score High School Rank (Percent in Top Quartile) Percent of All Undergraduate Who Attend Part-Time Cohort’s Mean First Semester GPA Percent of Cohort with First Term GPA Below Percent of Cohort that Resided in Campus Housing (1 st Year) Percent of Cohort Over Age Financial Aid: Percent of Cohort Receiving Federal Grants Expenditures on Instruction and Academic Support per FTE Percent of Cohort from Underrepresented Minority Groups Percent of Undergraduates in Headcount Financial Aid: Percent of Cohort Receiving Institutional Grants

13 Relationship Between SAT Scores and Success Rates *Includes converted ACT scores

14 Relationship Between Six-Year Graduation Rates and SAT Scores Math + Verbal SAT Score; includes converted ACT scores

15 Relationship Between HS Rank and Success Rates

16 Relationship Between Six-Year Graduation Rate and HS Rank

17 Relationship Between 1 st Semester GPA and Success Rates

18 Relationship Between Six-Year Graduation Rate and First Semester GPA

19 Relationship Between Campus Housing and Success Rates

20 Relationship Between Six-Year Graduation Rate and Housing

21 Relationship Between Federal Grant Aid and Success Rates

22 Relationship Between Six-Year Graduation Rate and Federal Grant Aid

23 Relationship Between Expend On Instruction + Academic Support per FTE on Success Rates

24 One-Year Retention Rate Regression Model Using SAT Scores Institutional One-Year Retention Rate (Adj. R 2 =0.642) β S.E. tSig. (Constant) Combined Math and Verbal SAT score* *** Baccalaureate Institution (dummy var.) *** Pct of Cohort Resided in Campus Housing *** Addition of following factors can increase model power by 4.1% (R 2 =0.681): percent graduating in the top quartile of HS class; percent of cohort receiving student loans, and the percent of the cohort receiving federal grants; Percent of Cohort with 1st Term GPA Under 2.0.

25 Six-Year Graduation Rate Regression Model Using SAT Scores Institutional Six-Year Graduation Rate (Adj. R 2 =0.764) β S.E. tSig. (Constant) Combined Math and Verbal SAT score† *** Pct of Cohort Resided in Campus Housing *** Percent of Cohort w1 st Term GPA Under *** Addition of following factors can increase model power by 4.5% (R 2 =0.811): Percent of all undergraduates who attend part-time, baccalaureate institution (dummy var.), percent graduating in the top quartile of HS class; percent of cohort receiving student loans, and the percent of the cohort receiving federal grants.

26 One-Year Retention Rate Regression Model NOT Using SAT Scores Institutional One-Year Retention Rate (Adj. R 2 =0.595) β S.E. tSig. (Constant) Pct of Cohort Graduated in Top HS Quartile *** Pct of Cohort Resided in Campus Housing *** Baccalaureate Institution (dummy var.) *** Addition of following factors can increase model power by 6.7% (R 2 =0.662): percent of the cohort receiving federal grants; expenditures on instruction and academic support per FTE; percent of cohort with a 1st term GPA under 2.0, public (dummy var.); percent of undergraduates who attend part-time, and percent of the cohort receiving student loans.

27 Six-Year Graduation Rate Regression Model NOT Using SAT Scores Institutional Six-Year Graduation Rate (Adj. R 2 =0.732) β S.E. tSig. (Constant) Pct of Cohort Graduated in Top HS Quartile *** Pct of Cohort Resided in Campus Housing *** Pct of Cohort that Received Federal Grants *** Percent of Cohort w1 st Term GPA Under *** Addition of following factors can increase model power by 4.5% (R 2 =0.811): Percent of all undergraduates who attend part-time, baccalaureate institution (dummy var.), percent graduating in the top quartile of HS class; percent of cohort receiving student loans, and the percent of the cohort receiving federal grants.

28 Six-Year Graduation Rate Regression Model Using Academic Inputs ONLY Institutional Six-Year Graduation Rate (Adj. R 2 =0.790) β S.E. tSig. (Constant) Mean Institutional SAT score *** Pct of Cohort Resided in Campus Housing *** Percent of Cohort 24+ years *** Pct of Cohort Graduated in Top HS Quartile ***

29 Implications and Conclusions (1) Results confirm and extend previous research: Most predictive factors: Admission inputs (SAT, followed by HS rank) Proportion living in campus housing First semester performance Race, gender, and SES appear not to add significant predictive power AFTER controlling for above factors

30 Implications and Conclusions (2) Policy implications: Evaluate institutional graduation rates in the context of an expected graduation rate Communicate realistic expectations to stakeholders

31 Implications and Conclusions (3) Recognize the impact of academic inputs BEFORE and DURING college experience Selectivity is a significant factor that intersects degree production as well as access; consider implications of resource allocation in context of degree yield rates Set incentives to promote performance during college, e.g. loan forgiveness vs. merit-based scholarships

32 Implications and Conclusions (4) Gaming the system - Institutions may continue to realize incentives to inflate grades

33 Implications and Conclusions (5) Arms race in selectivity will be exposed by demographic change in next decade; downward pressure on graduation rates is likely SOURCE: Knocking at the College Door (2008, Western Interstate Commission for Higher Education) Reproduced in The Chronicle of Higher Education Projections of Graduates of Public High Schools, by Racial and Ethnic Group in North East White, Non-Hispanic Hispanic Black, Non-Hispanic Asian/Pacific Islander

34 Institutional and Student Characteristics that Predict Graduation and Retention Rates Braden J. Hosch, Ph.D. Director of Institutional Research & Assessment November 4, 2008 North East Association for Institutional Research Annual Meeting Providence, RI This presentation and paper are online at


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