1. Persistence to Graduation for Transfer and "Native" Students: A Case Study John W. Miller, Ph.D. President, Central Connecticut State University Braden J. Hosch, Ph.D. Director of Institutional Research & Assessment, CCSU Association for Institutional Research Annual Forum Seattle, WA May 26, 2008

2. Overview Institutional Profile Overview of the problem → to what extent do differences in earned credit hours contribute to differences in graduation rates? Methodology and Results Conclusions and Implications

3. Institutional Profile: Central Connecticut State University Public – part of Connecticut State Univ. System Carnegie 2005 Master’s-larger programs Fall 2007 Enrollment: 12,106 headcount (9,704 undergraduate, 23% residential); 9,288 full-time equivalent enrollment 52% female; 16% minority Full-time, first-time students: 1,469 (56% residential) Full-time, new transfer students: 678 Six-year graduation rates: 44% full-time, first-time students 56% transfer students (full-time upon entry)

4. Methodology Divide subjects by origin Full-time first-time student Full-time transfer students Group subjects by credits earned rather than by fall of entry Measure time to graduation (Fall-to-Fall), regardless of time at institution e.g. after earning 76-90 credits, how many graduated in 1, 2, 3, 4, 5, 6, and 10 years? Produce descriptive statistics and run logistic regressions

5. Study Population Unduplicated, Full-Time Students in Study Population, Fall 1991-2006 Native StudentsTransfer Students Grand Total Race/EthnicityWomenMenTotalWomenMenTotal Non-Resident Alien1251412666449113379 African American/Black6647571,4213703787482,169 American Indian434083251843126 Asian168210378146184330708 Hispanic5425041,0462831954781,524 White7,6127,45515,0673,6753,6797,35422,421 Unknown3974348312342434771,308 Grand Total9,5519,54119,0924,7974,7469,54328,635 Total observations (duplicated individuals): 86,342 over 16 years

6. Graduation Rates by Credits Earned Credits Earned at Beginning of Fall Semester Yr. Of Entry* 16-3031-4545-6061-7576-9091-105106+ FTFTTransfFTFTTransfFTFTTransfFTFTTransfFTFTTransfFTFTTransfFTFTTransf In 1 YrGraduated (%)0% 14%9%46%32%72%56% 91-'06Basis Obs. (N)10,6402,4034,0172,7067,0123,9054,1013,8024,8813,6793,6933,3084,7385,598 In 2 YrsGraduated (%)0%1% 3%13%11%37%27%64%46%77%64%84%75% 91-'05Basis Obs. (N)9,8582,2173,6482,5036,4813,5953,6713,4814,4083,3903,2863,0254,1605,160 In 3 YrsGraduated (%)11%10%25%26%54%41%66%53%78%64%83%76%87%81% 91-'04Basis Obs. (N)9,1082,0413,2572,3245,8993,2733,2573,1773,8833,0902,8942,7593,6064,739 In 4 YrsGraduated (%)41%31%50%44%67%54%72%61%81%70%85%79%89%83% 91-'03Basis Obs. (N)8,3891,8542,8992,0925,2542,9942,8552,8883,4102,8052,5062,5173,1054,312 In 5 YrsGraduated (%)52%41%56%49%71%59%74%64%83%73%86%80%90%84% 91-'02Basis Obs. (N)7,5201,6832,5071,9164,6742,7192,4592,6132,9742,5352,1672,2932,6853,923 In 6 YrsGraduated (%)55%44%58%53%73%62%76%66%85%75%88%82%91%85% 91-'01Basis Obs. (N)6,7651,5132,1281,7214,0962,4642,1062,3462,5522,3141,8392,0592,2603,522

7. Differences in Graduation Rates

8. Logistic Regression (1) Two variable model (Forward conditional) BS.E.WaldExp(B) Total Credits Earned0.0210.0005,9211.022 Transfer-0.4370.0243430.646 Constant-0.4490.0158860.638 All variables significant at p<0.001 Model accuracy: 68.9% correct Cox & Snell R 2 : 0.138 Nagelkerke R 2 : 0.188

9. Logistic Regression (2) Multivariate model (Forward conditional) BS.E.WaldExp(B) Total Credits Earned0.0200.0003,5181.020 Transfer-0.4130.0262480.661 GPA Earned 1 st Fall0.2400.0181701.271 Hrs Attempted 1 st Fall0.0750.0052241.078 GPA Earned in Fall of Analysis0.8930.0163,2992.443 Constant-4.0260.0703,2740.018 All variables sig. at p<0.001 Model accuracy: 75.1% correct Cox & Snell R 2 : 0.273 Nagelkerke R 2 : 0.371 Additional Significant Variables: Female African American/Black Hispanic But model accuracy improved by only 0.1% or less with inclusion

10. Major Findings Total credits earned is most significant predictor of graduation Native students graduated at higher rates than transfer students after controlling for credits earned Other significant predictors: First semester GPA Credits attempted first semester GPA in term of analysis

11. Conclusions and Implications (1) 1. At CCSU, and I suspect at other institutions, we need to recognize the lower success rate of our transfer students by comparing their progress to their equivalent credit counterparts. 2. While recognizing and respecting the experiences of transfer students, we must appreciate that they still need similar support to FT/FTs modified for them (e.g. FYTE course).

12. Conclusions and Implications (2) 3. More careful exploration of our transfer compacts to determine how to better pave the way for transition is required. 4. We must more deeply study our “counting” of credits as meeting requirements, used as electives, or not counted at all to ensure maximum appropriate progress toward completion at time of transfer.

13. Persistence to Graduation for Transfer and "Native" Students: A Case Study Contact Information: John W. Miller, Ph.D. President, Central Connecticut State University millerjw@ccsu.edu Braden J. Hosch, Ph.D. Director of Institutional Research & Assessment, CCSU hoschbrj@ccsu.edu