# A comparison between academic performance of native and transfer students in a quantitative business course

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4 456. There was a significant difference in the scores of these two groups (Table 3). The average final grade for native students was higher (M = 85.25, SD = 10.45) than the average for the transfer students (M = 78.06, SD = 13.32). Table 1 presents the information on which math prerequisite was taken. The results in Tables 4 and 5 reveal a significant effect for prerequisite. Of the 741 native students, 350 took MAC 1105, college algebra, and 390 took MAC 1140, pre-calculus. One student did not answer the question. The results in Table 4 show that there was a significant difference between the two groups, with students that took pre-calculus (M = 87.74, SD = 8.2) having a higher average final grade than the students that took college algebra (M =82.4, SD = 11.91). Of the 456 transfer students 299 took MAC 1105, college algebra, and 157 took MAC 1140 pre-calculus. Even in this case the results denote that students that took pre-calculus (M = 79.97, SD = 13.28) fare better than college algebra (M = 77.05, SD = 13.26) students (Table 5). The results in Tables 6 and 7 show that there is a statistical difference in student achievement for type of students (transfer, only state colleges, or native) with the same prerequisite, with native students doing better. Table 6 illustrates that native (M =82.4, SD = 11.91) students that took MAC1105 do better than transfer (M = 77.05, SD = 13.26) students with the same prerequisite. Table 7 indicates that native students that took MAC 1140 (M =87.74, SD = 8.2) have a higher average course score than transfer students that took MAC 1140 (M = 79.97, SD = 13.28). Tables 8 and 9 paint two different pictures regarding gender and student performance. Of the 456 transfer students, 177 were female (M =77.60, SD = 14.98) and 279 male (M =78.34, SD = 12.55). The results in Table 8 imply that the academic performance of transfer students for both genders is not statistically different. Of the 741 native students, 238 were female (M =87.02, SD = 10.56) and 502 male (M =84.40, SD = 10.32). One student did not answer the question. Table 9 points out that there is a statistical difference, with female students having a better average for the class. Lastly, Table 2 shows that 13% of the transfer students are 30 or older versus only 0.5% of the native. Also, the age distribution of transfer (state colleges) students seems more even throughout the age spectrum, while native students tend to be younger. CONCLUSIONS The study supports the hypothesis that students with stronger academic prerequisites for this class fair better. The study also shows that native and transfer with the same prerequisite have different academic achievement native students with stronger academic prerequisites fair better than transfer students with the same prerequisite class. Female transfers seem to do as well as male transfer students. That is not the case between native female students and native male students. Lastly, according to the data, students that transferred from a 4-year university averaged better than students that transferred from a community college. In summary, this research seems to support the conclusions reached by Friedl et al., (2012). They suggest that the performance of native students is not equal to the performance of transfer students. It is important to note that our findings do not imply that native students are better students than transfer students. The study only supports that they seem not to score the same in this particular quantitative class. Tobolowsky and Cox (2012) suggest that transfers could be helped with more coordination between the sending and receiving institutions. In fact, the transfer student population can play a big financial role by boosting income through A comparison between academic, page 4

5 tuition..fulfilling institutional and community needs. This is an important issue not only for students, less cost same benefits, but also for universities that are under pressure to be more focused on student achievement and increased graduation rates because of political/funding issues. The issue should be further researched. Specifically, a more relevant question might be whether transfer students fair as well as native in academic graduation since Best and Gerghing (1993) suggest they don t. A comparison between academic, page 5

6 APPENDIX Table 1 Complete Origin Enrollment Data and Pre-requisites STUDENTS TOTAL AVERAGE COURSE GRADE Native MAC 1105 (College Algebra) 350 Female 109 Male 241 MAC 1140 (Precalculus) 390 Female 129 Male 261 N/A 1 Male 1 Transfer from a State College MAC 1105 (College Algebra) 299 Female 114 Male 185 MAC 1140 (Precalculus) 157 Female 63 Male 94 Transfer from a 4-yr University MAC 1105 (College Algebra) 36 Female 20 Male 16 MAC 1140 (Precalculus) 20 Female 9 Male 11 None of the above MAC 1105 (College Algebra) 6 Female 3 Male 3 MAC 1140 (Precalculus) 4 Female 3 Male 1 Grand Total 1,263 A comparison between academic, page 6

7 Table 2 Partial Origin Enrollment Data and Age Distribution STUDENTS TOTAL AVERAGE COURSE GRADE Native Female or older 3 Male or older 1 Transfer from a State College Female or older 31 Male or older 28 Table 3 Results on Average Course Grade by Native and Transfer (State College) Students Student F-test Equality of Variances t-test Unequal Variances Native Transfer F df p t df p M (455, 740) <.001 * <.001 * SD n * Significantly Different (α =.05) A comparison between academic, page 7

8 Table 4 Results on Average Course Grade by Native Students with Different Pre-requisites: MAC 1105 (College Algebra) and MAC 1140 (Precalculus) Native F-test Equality of Variances t-test Unequal Variances F df p t df p M (349, 389) <.001 * <.001 * SD n * Significantly Different (α =.05) Table 5 Results on Average Course Grade by Transfer Students (State College) with Different Prerequisites Transfer F-test Equality of Variances t-test Equal Variances MAC 1105 MAC 1140 F df p t df p M (156, 298).967 ** * SD n * Significantly Different (α =.05) ** No Significantly Different (α =.05) Table 6 Results on Average Course Grade by Native and Transfer (State College) Students with same Pre-requisites (MAC 1105) MAC 1105 F-test Equality of Variances t-test Equal Variances Transfer Native F df p t df p M (298, 349).055 ** <.001 * SD n * Significantly Different (α =.05) ** No Significantly Different (α =.05) A comparison between academic, page 8

9 Table 7 Results on Average Course Grade by Native and Transfer (State College) Students with same Pre-requisites (MAC 1140) MAC 1140 F-test Equality of Variances t-test Unequal Variances Transfer Native F df p t df p M (156, 389) <.001 * <.001 * SD n * Significantly Different (α =.05) Table 8 Results on Average Course Grade for Transfer (State College) Students according to Gender Transfer F-test Equality of Variances t-test Unequal Variances Female Male F df p t df p M (176, 278).032 * ** SD n * Significantly Different (α =.05) ** No Significantly Different (α =.05) Table 9 Results on Average Course Grade for Native Students according to Gender Native F-test Equality of Variances t-test Unequal Variances Female Male F df p t df p M (237, 501).669** * SD n * Significantly Different (α =.05) ** No Significantly Different (α =.05) A comparison between academic, page 9

11 Xueli, W. (2009). Baccalaureate Attainment and College Persistence of Community College Transfer Students at Four-Year Institutions. Research In Higher Education, 50(6), doi: /s z Wolfle, J. D., & Williams, M. R. (2014). The Impact of Developmental Mathematics Courses and Age, Gender, and Race and Ethnicity on Persistence and Academic Performance in Virginia Community Colleges. Community College Journal Of Research & Practice, 38(2/3), doi: / Woosley, S., & Callahan, T. (2011). The Effects of Prerequisites and Curricular Continuity: Domestic Versus Imported. College Student Journal, 45(3), A comparison between academic, page 11

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