Statistical Analysis of Writing Proficiency scores for transfer student factors

1. Statistical Analysis of Writing Proficiency scores for transfer student factors Robert Guzman Holly Reed Randy Timm Ed 850 – Seminar in Quantitative Inquiry

2. Transfer Students – Effects of Remediation • “Remediation programs, while intended to reduce disparities between advantaged and disadvantaged groups, end up serving those who are more likely to be successful. As Bahr, 2007 noted, “in the end those who most need remediation are the least likely to remediate successfully.” This is also referred to as the Mathew Effect referring to the biblical passage, "to everyone who has, more shall be given, and he will have an abundance; but from the one who does not have, even what he does have shall be taken away" (Matt. 25:29, New American Standard Bible). (Bahr, 2007; Bahr 2010) • In looking at transfer students who need remediation, what types of students are we talking about?

3. Study Purpose • Transfer students believe that their associates degree has prepared them for 4-year university work. While students may transfer with a high-medium or high grade point average they may then be required to remediate due to under-preparation. However not all transfer institutions prepare their students for 4-year university level work. It is necessary to address the factors leading to student’s leading to student’s needing 4-4-year writing remediation. • The purpose of this analysis is to determine whether there are differences in writing proficiency assessment scores by transfer college, ethnicity and entering GPA.

4. Problem Statement • The problem scrutinized within this study is an examination of the factors that might align with low performance on the writing proficiency examination. In examining these factors (Transfer institution, Ethnicity, and Transfer GPA) and matching them against WPA scores, we might be able to return to the community colleges with this data to better assist them in developing their programs for transfer student success.

5. Literature Review • Students with high levels of social and academic integration tended to have high levels of predisposition to transfer. Ethnic background was found to have no relationship to predisposition to transfer (Nora & Rendon, 1990) • When community college students transfer to institutions so vastly different in culture from the sending school, uneasiness and frustration with the receiving institution is likely to result (Townsend & Wilson, 2006). • The most predictive factor for transfer was taking courses prescribed in a transfer-focused community college curriculum. Successful transfers enrolled and passed courses in transfer-level English and mathematics as well as other courses (Hagedorn, et al., 2008) • Students with deep developmental needs averaged five years at the community college before transferring, and transferred only one year's worth of college-level courses. Of concern is the great number of African American and Latino students in remedial courses (Melguizo, et al., 2008)

6. Literature REview • Latino students are more likely to be in remediation programs than other ethnicities (Crisp & Nora, 2010) • Remediation programs may be perceived as a college access gatekeeper; 30% of students referred to remediation will not even enroll in the remediation course, and less than 50% of the students who are referred to remediation will complete the remediation course sequence (Nora & Crisp, 2012) • Academic performance has large effects on likelihood of retention and transfer; academic self-discipline, pre-college academic performance, and pre-college educational development have indirect effects on retention and transfer; and college commitment and social connectedness have direct effects on retention. Academic self-discipline led to greater first-year academic performance, which suppressed its effect on retention and transfer. (Allen, et al., 2008)

7. Data Collection - Methods • Data was collected from the student information management system (SIMS Data) at San Diego State University (SDSU). • Provided by the Student Testing and Assessment Research Office • Data reflects the 2009 transfer cohort into SDSU • Total number of transfer students represented: N=2438 • Data contains: • Transfer grade point average (GPA), • Transfer institution • Student Ethnicity • Scores on the Writing Proficiency Examination that determines remediation course requirements for incoming students • Scores of 0-6, requires 2 RWS courses: 1 remediation course and 1 junior level course. • Score of 8, requires 1 junior level RWS course • Scores of 9 and 10 are exempt from remediation courses

8. Analysis of Data – WPA score by Transfer College Data included transfer students from 9 local community colleges and a category representing all other community college transfer students from outside the service area. N= This study sought to determine whether there were significant mean differences between the students transfer institution and their scores on the WPA determining their remediation needs. Levine’s test for equality of variance indicated that the assumption of homogeneity of variance was not violated (p=n.s.). Therefor the ANOVA procedure was employed. The ANOVA indicated that there was a significant difference between groups. The effect size of the significance was assessed with a small effect size (n2 =.027). Seven Post-hoc tests showed significant mean differences.

9. Significant Data Points – Transfer Institution • Those students who came from Grossmont College had significantly higher scores on the WPA than students from SD City College by .641 points (p<.001). • Those students who came from Grossmont College had significantly higher scores on the WPAthan students from Southwestern College by .523 points (p<.001) • Those students who came from Mira Costa College had significantly higher scores on the WPA than students from SD City College by 1.176 points (p<.01) • Those students who came from Mira Costa College had significantly higher scores on the WPA than students from Southwestern College by 1.057 points (p<.05) • Those students who came from outside the service area (Other) had significantly higher scores on the WPAthan students from SD City College by .734 points (p<.001) • Those students who came from outside the service area (Other) had significantly higher scores on the WPAthan students from Miramar Community College by .525 points (p<.05) • Those students who came from outside the service area (Other) had significantly higher scores on the WPAthan students from Southwestern College by .615 points (p<.001)

10. Analysis of Data – Wpa score by Ethnicity • Data included information on student ethnicity using the 9 category ethnicity reporting. This includes typical ethnic categories or Native American, African American, Latino American, Southeast Asian American, Asian American, Filipino American, European American, Other (two or more) and No Response. • This study sought to determine whether there were significant mean differences between the students ethnicity and their scores on the WPA determining their remediation needs. Levine’s test for equality of variance indicated that the assumption of homogeneity of variance was not violated (p=n.s.). Therefor the ANOVA procedure was employed. The ANOVA indicated that there was a significant difference between groups. The effect size of the significance was assessed with a medium effect size (n2 =.06). Ten Post-hoc tests showed significant mean differences.

11. Significant Data Points - Ethnicity • Students identifying as European American had significantly higher scores on the WPA assessment than students identifying as African American by .907 points (p<.001) • Students identifying as European American had significantly higher scores on the WPA assessment than students identifying as Latino American by .677 points (p<.001) • Students identifying as European American had significantly higher scores on the WPA assessment than students identifying as Southeast Asian American American by .941 points (p<.001) • Students identifying as European American had significantly higher scores on the WPA assessment than students identifying as Asian American by 1.031 points (p<.001) • Students identifying as Other – Two or more Ethnicities had significantly higher scores on the WPA assessment than students identifying as African American by .707 points (p<.05) • Students identifying as Other – Two or more Ethnicities had significantly higher scores on the WPA assessment than students identifying as Latino American by .477 points (p<.05) • Students identifying as Other – Two or more Ethnicities had significantly higher scores on the WPA assessment than students identifying as Southeast Asian American by .741 points (p<.05) • Students identifying as Other – Two or more Ethnicities had significantly higher scores on the WPA assessment than students identifying as Asian American by .831 points (p<.001) • Students identifying as Filipino American had significantly higher scores on the WPA assessment than students identifying as Asian American by .722 points (p<.01) • Students identifying as No Response or Decline had significantly higher scores on the WPA assessment than students identifying as Asian American by .759 points (p<.001)

12. Analysis of Data – WPA score by Incoming Transfer GPA • Data included information on transfer GPA, divided into 5 categories, low (0.00 to 2.80), Low Mid (2.80 – 3.10), Mid (3.10 – 3.40), High Mid (3.40 – 3.70), and High (3.70 – 4.0). • This study sought to determine whether there were significant mean differences between the students entering GPA by category and their scores on the WPA determining their remediation needs. Levine’s test for equality of variance indicated that the assumption of homogeneity of variance was violated (p<.001). Therefor the Welch procedure was employed. The Welch indicated that there was a significant difference between groups. The effect size of the significance was assessed by with a large effect size (n2 =.186). Nine Post-hoc tests showed significant mean differences.

13. Significant Data Points – Transfer GPA • Students with High GPAs had significantly higher scores on the WPA than students with High Mid GPAs by .566 points (p<.05) • Students with High GPAs had significantly higher scores on the WPA than students with Mid GPAs by .890 points (p<.05) • Students with High GPAs had significantly higher scores on the WPA than students with Low Mid GPAs by .1.127 points (p<.05) • Students with High GPAs had significantly higher scores on the WPA than students with Low GPAs by 1.598 points (p<.05) • Students with High Mid GPAs had significantly higher scores on the WPA than students with Mid GPAs by .324 points (p<.05) • Students with High Mid GPAs had significantly higher scores on the WPA than students with Low Mid GPAs by .561 points (p<.05) • Students with High Mid GPAs had significantly higher scores on the WPA than students with Low GPAs by 1.032 points (p<.05) • Students with Mid GPAs had significantly higher scores on the WPA than students with Low GPAs by .708 points (p<.05) • Students with Low Mid GPAs had significantly higher scores on the WPA than students with Low GPAs by .471 points (p<.05)

14. Discussion of Findings • Transfer institutions can better prepare students for the WPA and for success at transfer. Transfer colleges from higher socio-economic neighborhoods tend to have students who perform better. It is also possible that these institutions have more comprehensive transfer programs which could indicate better preparedness (Hagedorn, et al., 2008) • European American Students and Students identifying as Other – two or more races may be better prepared for college and less likely to need remediation • Although students with higher GPAs tend to require less remediation, it is still interesting to note that almost half of the students with GPAs in the mid range (3.1-3.4) still require two remediation courses. • This data shows that transfer students are still largely unprepared for the 4-year environment. • Limitations of this study include the fact that this data only represents one year and one region. Additionally this data is not separated by gender which limits the possible conclusions. This might make it difficult to generalize these results to a larger population.

15. Conclusions • The data show that there are clear indicators for a decreased need for remediation. • Consistent with the data, students from colleges with structured transfer programs are more likely to need decreased remediation. • Consistent with the literature, European American students are less likely to need remediation • Interestingly, Students identifying as Bi or Multi-Racial are also less likely to need remediation. • Students with higher transfer GPAs are less likely to need remediation. • Further research is needed to determine if these predictors have any effect on 2 and 4 year graduation rates.

16. Future Questions for Research • For those students who have taken a several remediation courses in their community college coursework, does being remanded to remediation at the University decrease their academic self-esteem and their likelihood to remain at the institution? If so, how and why? • What are the effects of dual remediation on transfer students’ University degree attainment? Does being required to take both writing remediation and math remediation decrease the likelihood of University degree attainment?

17. Recommendations for Policy and Practice • Discuss preparation for the WPA with all transferring institutions. Provide students with a solid realization of their likely remediation status before they transfer to the University. • Discuss grade point average with specific community colleges. How can it be that students receive a mid-high GPA and then are required to take two levels of remediation at the University? Grade inflation? Transfer Shock? Testing Shock? • For those institutions where transfer remediation is pervasive, consider two-sided bridge programs to the University. The front side of the bridge should be in the preparation to transfer and the second side should be at the University to assist in transfer transition.

18. References • Allen, J., Robbins, S. B., Casillas, A., & Oh, I. S. (2008). Third-year college retention and transfer: Effects of academic performance, motivation, and social connectedness. Research in Higher Education, 49(7), 647-664. • Bahr, P. R. (2010). Revisiting the efficacy of postsecondary remediation: The moderating effects of Depth/Breadth of deficiency. Review of Higher Education, 33(2), 177-205. Retrieved from http://search.proquest.com/docview/220824223?accountid=13758 • Crisp, G., & Nora, A. (2010). Hispanic student success: Factors influencing the persistence and transfer decisions of latino community college students enrolled in developmental education. Research in Higher Education, 51(2), 175-194. doi:10.1007/s11162-009-9151-x • Hagedorn, L. S., Cypers, S., & Lester, J. (2008). Looking in the review mirror: Factors affecting transfer for urban community college students. Community College Journal of Research and Practice, 32(9), 643-664. • Hagedorn, L. S., Moon, H. S., Cypers, S., Maxwell, W. E., & Lester, J. (2006). Transfer between community colleges and 4-year colleges: The all-American game. Community College Journal of Research and Practice, 30(3), 223-242. • Melguizo, T., Hagedorn, L. S., & Cypers, S. (2008). Remedial/developmental education and the cost of community college transfer: A Los Angeles County sample. The Review of Higher Education, 31(4), 401-431. • Nora, A., & Crisp, G. (2012, 07). Hispanic participation and success in developmental education. White paper prepared for the Hispanic Association of Colleges and Universities Hispanic association of college and universities. doi: http://www.eric.ed.gov.libproxy.sdsu.edu/PDFS/ED537724.pdf • Nora, A., & Rendon, L. I. (1990). Determinants of predisposition to transfer among communitycollege students: A structural model. Research in Higher Education, 31(3), 235-255. • Townsend, B.K. & Wilson, K.B. (2006). “A hand hold for a little bit”: Factors facilitating the success of community college transfer students to a large research university. Journal of College Student Development, Vol. 9, No. 4, 439-456. Retrieved from: http://muse.jhu.edu/journals/journal_of_college_student_development/v047/47.4townsend.html