REMEDIAL MATH REPORT Fall 2010

Transcription

1 P a g e 1 REMEDIAL MATH REPORT Fall 2010 Photo Credit: John Filce Office of Institutional Research and Planning One Harpst Street Arcata, California

2 P a g e 2 Table of Contents Introduction 3 Milestone Events.. 4 Student Cohort Information Remedial Math Students Success in Remedial Math Courses. 5 Success in Subsequent College Level Math Courses.. 6 One and Two Year Retention Rates. 8 Regression Analyses on Retention Rates.. 11 Six Year Graduation Rates.. 13 Regression Analyses on Six Year Graduation Rates 18

3 P a g e 3 Introduction This report is part of an effort to identify successful paths to graduation as part of the California State University s Graduation Rate Initiative Project (GRIP). The Educational Trust working with the California State University Chancellor s Office has encouraged campuses to analyze data that can inform the process of increasing success, retention, and ultimately, graduation rates. Generally, institutions measure retention and graduation rates as key performance indicators for institutional effectiveness. These measures give an overall litmus test of the productivity of the institution, yet are measured after the fact, leaving little opportunity for immediate intervention. These rates are also aggregated across all students, and do not give us specific information as to why specific groups of students fail to be retained or graduate. The Educational Trust has suggested we perform a leaky pipeline analysis that helps us identify where we lose which students. They have encouraged us to determine what leading indicators are early signals that students may not succeed. In order to perform this analysis, the Institutional Research and Planning (IRP) Office conducted a remedial math study using ten years of longitudinal data which indicates benchmarks for success for students that begin in remedial math courses versus students that begin in college level math courses. This study will help identify what variables contribute to student success for one and two year retention rates as well as graduation rates based on several leading indicators.

4 P a g e 4 Milestone Events The Educational Trust has created a trajectory for students to achieve a baccalaureate degree measuring benchmarks along the way that contribute to or inhibit success in remedial students versus non remedial students. The Milestone Events look somewhat like this: The first measurement suggested is to determine success in remedial coursework. Accordingly, our first study in the process of measuring leading indicators is to examine our remedial math students. At Humboldt State, we measured remedial math students over a ten year period (Fall Fall 2009) on the following important outcomes: success rates in remedial and subsequent college level math courses, first and second year retention, and six year graduation rates. Students who tested directly into college level math were used as a reference group for which to compare success rates of remedial math students in college level math courses. In addition, we performed regression analyses to see if certain characteristics (i.e., demographics, attendance characteristics, and success indicators) would differentially predict graduation and retention for remedial math (RM) students compared with college level math proficient (CLMP) students. This paper will examine those results.

5 P a g e 5 Student Cohort Information First-time Fall-enrolled freshman cohorts were examined on a wide variety of demographic and attendance characteristics as well as success indicators for the academic years of Two sub-populations were defined by those students who at the time of the current study had a six year window to graduation ( ), and those students who did not yet have an opportunity to graduate in six years ( ). Accordingly, the regression analyses measuring graduation rates utilize the Fall cohorts; contrariwise, the regression analyses examining retention were performed on the Fall cohorts. Cohort data for 2009 was omitted from the regression analysis because two-year retention could not be assessed at the time of the current study. In , for first-time fall-enrolled freshman (n = 9,295), only 32% of males needed math remediation compared to 45% of females. Remediation rates were consistent for both subpopulations ( and ). Interestingly, 61% of males and 52% of all females who needed math remediation also needed English remediation. Results indicate that a significant amount female students begin college with math remediation needs than male students First-time freshman cohort by need of math remediation and gender Male Female Total Student type Count Percent Count Percent Count Percent College Level Math 2,748 68% 2,896 55% 5,644 61% Need Math Remediation 1,306 32% 2,345 45% 3,651 39% - Need Math only Remediation (509) (1,119) (1,628) - Need Math and English Remediation (797) (1,226) (2,023) Total 4,054 5,241 9,295 Note. Counts in parenthesis describe the number of students who needed math remediation only and the number of students who needed math remediation that also needed English remediation. Note. Significance was tested using a Pearson s Chi-Square. Remedial Math Students Success in Remedial Math Courses According to the Humboldt State University Advising Center, some students are admitted to the University with a need for further development in English and math, as measured by scores on the English Placement Test (EPT) and the Entry Level Mathematics (ELM) exams. In order to ensure academic success for all students, and in compliance with California State University regulations, Humboldt State University requires that all new students with ELM and/or EPT scores that indicate a need for remediation enroll in appropriate remedial classes their first term of attendance. Some students may need a sequence of remedial courses; these students must enroll in the appropriate remedial course each term of attendance until remediation is satisfied. All remediation must be completed within one year from a student s first term of enrollment at Humboldt. Students who do not satisfactorily complete the required courses within one year will not be eligible to continue at Humboldt. Satisfactory completion of remedial courses requires a grade of C- or higher.

6 P a g e 6 Humboldt State has been very successful with math remediation by remediating between 77% and 89% of students requiring math remediation within a year of entering the University. Interestingly, only 4% to 8% of students taking math remediation fail the course in their first year and are forced to leave Humboldt State. Fall First-time freshman cohort proficiency at entry to HSU and one-year later follow-up Year % of regular admits who needed math Completed math Remediation Failed math remediation, but allowed to Failed remediation and left HSU Transferred before being remediated remediation continue % 80% 9% 8% 3% % 77% 9% 8% 6% % 89% 5% 4% 2% % 86% 5% 6% 3% % 86% 7% 4% 4% % 84% 8% 5% 3% % 82% 6% 6% 6% Note. Information was retrieved from the CSU Analytic Studies, CSU Proficiency Report Success in Subsequent College Level Math Courses Research shows that passing college level math courses is challenging for most students. This is exemplified in a ten-year average of nine introductory college courses having an average nonsuccess rate (below C-) of 23%. Of interest is whether remedial math (RM) students do as well as college level math proficient (CLMP) students overall and by course. When compared to the total success rate, CLMP students (n=1,464) have higher numbers of students who are successful in college level math courses as compared to RM students (n= 631). However, when compared to their respective groups, 31% of RM students were not successful in a subsequent college math course compared with only 21% of CLMP students who went directly into a math course. Comparison of college level math course non-success rates over 10 years ( ) of students who completed a math remediation course and students who were proficient in college level math College level math proficient Needs remedial math Course name Number Percent Number Percent MATH % % MATH % 33 53% MATH % 9 15% MATH % 30 43% MATH % 75 48% MATH % 65 11% STAT % 62 31% STAT % 69 38% BIOM % 49 37% Note. Percentages shown are for each course within either the RM or CLMP group.

7 P a g e 7 Seven of the nine college level math courses included in the analysis showed significant differences in success for RM students compared to CLMP students. Success rates between RM and CLMP students showed the greatest disparity for calculus courses (Math 109, 106, & 105), followed by statistics courses (Stat 106, Stat 108, and Biom 109), and a pre-calculus course (Math 115). There was no difference between success rates for RM and CLMP students courses designed exclusively for general education, such as Critical Thinking in Mathematics course or Contemporary Mathematics course (Math 108 and Math 103, respectively). Of the calculus courses, RM students underperformed CLMP students the most in Calculus for the Biological Sciences & Natural Resources (Math 105) followed by Calculus 1 (Math 109) and Calculus for Business & Economics (Math 106). Non-success rates for RM students ranged from 43% to 53% whereas CLMP students non-success rates ranged from 21% to 29%. Of the statistics courses, RM students underperformed CLMP students the most in Introductory Biometrics (Biom 109), followed by Elementary Statistics (Stat 108), and Introduction to Statistics for the Health Sciences (Stat 106). Non-success rates for RM students ranged from 31% to 38% whereas non-success rates for CLMP students ranged from 16% to 24%. The largest enrolled course (n=2,892) was the Algebra & Elementary Functions course (i.e., precalculus; Math 115). RM student s underperformed CLMP students: RM students had a non-success rate of 39% compared with CLMP students non-success rate of 25%. Math 115 is a gateway course to student success because it is a prerequisite for other math courses such as calculus and statistics. In some cases it serves as a prerequisite to a math course (Math 105, Math 109, stat 109) required for graduation. Students who do not pass Math 115 are forced to repeat it until earning a C- grade or better. This is an issue for remedial math students who start college at least one semester in math behind their peers, putting them at greater risk of being lost in the leaky pipeline. For students who are not successful in Math 115, they may be forced to change majors or may risk ending their higher education. College level math courses over 10 years ( ) by success rates by remedial math status College level math proficient Needs remedial math Cramer s V Course name Number Success Rate Number Success Rate MATH % %.131*** MATH % 62 47%.146*** MATH % 60 85%.023 MATH % 70 57%.131*= MATH % %.224*** MATH % %.005 STAT % %.131** STAT % %.148** BIOM % %.193*** Total 7,099 79% 2,058 69%.100*** Note. Cramer s V is a measure of effect size (magnitude of difference) associated with a Chi-Square analyses - ranging from zero (very small) to one (very large). * Indicates a statistically significant (p <.05) level of independence. ** p <.01 *** p <.001

8 P a g e 8 Underrepresented minority (URM) students historically underperform on outcomes related to graduation and retention at HSU. URM students include American Indian, Black, Hispanic/Latino, and two or more ethnicities. We defined non-urm students as White or Asian because these groups perform similar in terms of graduation and retention. To further examine the issue of the leaky pipeline for RM students, URMs non-success rates were examined for Math 115 for the years of A total of 169 students showed a high overall non-success rate (44%) compared to the ten year trend (39%). Within minority status, non URM students (45%) did not have a significantly higher non-success rate than URM Students (43%). Math remediation students success and non-success counts in Math 115 from by underrepresented minority status Non-URM URM Cramer s V Successful Not Successful Successful Not Successful MATH Note. Cramer s V is a measure of effect size (magnitude of difference) associated with Chi-Square analyses - ranging from zero (very small) to one (very large). One and Two Year Retention Rates Retention rates were measured for first-time full time students during the years of Fall One year retention rates for remedial math students lagged slightly behind those of college level math students. There was a large decrement in retention rates from the first to second year for remedial math students (15%) as well as for college level math students (12%). Overall, it does not appear that remedial math students are too far behind college level math students in two year retention rates, although further examination is necessary to see whether there are factors that differentially predict retention rates for remedial versus college level math students. Accordingly, this section examines one and two year retention rates of math students by factors in the following categories: demographics, attendance characteristics, and success indicators. One and two year retention rates for remedial vs. college level math students (Fall ) One year retention Two year retention Student type Number Percent Number Percent RM % % CLMP % % Total % % Females are more likely to be retained than males after the first year regardless of whether remediation in math is necessary. One year retention rates for females are about 9% higher among both student types. Two year retention rates for RM and CLMP students follow a similar pattern, where male retention lags behind females at about 8-9%.

9 P a g e 9 Retention rates for remedial vs. college level math students by sex One year retention Two year retention Student type Male Female Male Female RM 380 (66%) 723 (74%) 300 (52%) 586 (60%) CLMP 844 (71% 959 (79%) 703 (59%) 811 (67%) Exceptional admits are comprised of students who did not meet some requirement for admission e.g., a certain high school GPA or SAT score but were allowed admission into HSU. They consistently show lower rates of graduation and retention than regularly admitted students as well as more trouble finishing gateway courses. Finding that exceptional admits lagged behind regularly admitted students in retention rates across student types is no surprise. However, it is interesting to note that exceptional admits who need remediation in math lagged behind college level math exceptional admits in first and second year retention by only 1-2%, compared with a 5% gap for regularly admitted students. Retention rates for remedial vs. college level math students by admission status One year retention Two year retention Student type Exception admit Regular admit Exception admit Regular admit RM 358 (66%) 745 (73%) 281 (52%) 605 (60%) CLMP 282 (68%) 1521 (77%) 221 (53%) 1293 (65%) Freshman who live in dorms during their first year were about 7% more likely to be retained than freshman living off campus. This effect was the same for both RM and CLMP students. Retention rates for remedial vs. college level math students by housing status On campus Off campus Student type Number Percent Number Percent RM % % CLMP % % Predictably, math students on academic probation were much less likely to be retained after the first and second year than students in good standing. For two year retention, RM students in good standing were over twice as likely to be retained as RM students on academic probation; likewise, CLMP students in good standing were almost twice as likely to be retained after two years as CLMP students on academic probation. Retention rates for remedial vs. college level math students by academic standing One year retention Two year retention Student type Good Probation Good Probation RM 938 (79%) 165 (46%) 774 (65%) 112 (31%) CLMP 1555 (83%) 248 (48%) 1322 (70%) 192 (37%)

10 P a g e 10 Being an undeclared major at the outset of college was negatively related to first year retention for RM but not CLMP students. The one year retention rate of RM students with a declared major was 10% higher than undeclared RM students. Being an undeclared major was not significantly related to second year retention for either student type; however, we did not have data on whether students had declared a major by the second year. As a result, the present analysis examined second year retention based on being an undeclared major during freshman year. Retention rates for remedial vs. college level math students by undeclared major One year retention Two year retention Student type Declared Undeclared Declared Undeclared RM 944 (73%) 159 (63%) 745 (57%) 141 (55%) CLMP 1538 (75%) 265 (74%) 1292 (63%) 222 (62%) Being in a freshman interest group (FIG) was positively related to first year retention for both RM and CLMP students. Math students who took part in a FIG were retained at a 6% higher rate than students not in a FIG. Moreover, the effects of FIGs appear to carry over into subsequent years: being in a FIG was significantly related to two year retention for CLMP students and marginally related to retention for RM students p =.056. Retention rates for remedial vs. college level math students by Freshman Interest Group FIG One year retention Two year retention Student type FIG Not in FIG FIG Not in FIG RM 409 (75%) 694 (69%) 330 (60%) 556 (55%) CLMP 858 (78%) 945 (72%) 747 (68%) 767 (59%) The educational opportunity program EOP has the mission of increasing access and improving retention of low-income and historically underrepresented. Accordingly, the current analysis looks at the effect of EOP on retention only for URM students. EOP was related to first and second year retention for remedial math URM students. However, EOP was not related to retention for college level math proficient URM students, wherein first and second year retention rates were only 2% higher among college level URM math students who took part in EOP and those who did not. Retention rates for remedial vs. college level math URM students by EOP One year retention Two year retention Student type EOP Not in EOP EOP Not in EOP URM needs remediation 218 (77%) 701 (71%) 184 (65%) 571 (57%) URM college level math proficient 89 (78%) 1372 (76%) 76 (67%) 1166 (65%) High school grade point average HS GPA, fall semester HSU GPA, and fall semester units earned were positively related to first and second year retention for both RM and CLMP students. What is more, these variables were among the most effective predictors of retention.

11 P a g e 11 Means and standard deviations for High School HS GPA, Fall semester HSU GPA, and units earned at the end of Fall semester by retention and math student type Retained year one Not retained year one Retained year two Not retained year two M SD M SD M SD M SD HS GPA RM CLMP Fall semester RM HSU GPA CLMP Fall semester RM units earned CLMP Regression Analyses on Retention Rates Comparison of first and second year retention rates of remedial math students with those ready for college level math Fall student cohorts First-year retention Second-year retention Remedial CL ready Remedial CL ready Demographic and Attendance Characteristics Male Age ns ns ns - URM ns ns ns ns Disabled ns ns ns ns HS GPA SAT math ns ns ns ns SAT verbal ns ns ns ns Needs remediation in English ns ns ns ns CA resident ns ns ns ns Exception admit Low income ns ns ns ns Success Indicators FIG + + ns* + EOP - URM ns* ns ns ns In dorm + + Academic probation Undeclared major - ns ns ns Fall semester Humboldt GPA Units earned at the end of Fall semester Indicates a statistically significant (p <.03) positive relationship with likelihood of retention. - Indicates a statistically significant (p <.03) negative relationship with likelihood of retention. ns Statistically not significant, * indicated a marginally significant predictor (p <.06).

12 P a g e 12 Four years of cohorts were aggregated in the final regression analyses on retention after analyses on individual cohorts evidenced a similar pattern of results. Overall, the results on retention rates of RM and CLMP students point to some very obvious predictors as well as some possible interventions for increasing retention. In all cases, being a male, an exceptional admit, or on academic probation was negatively related to first and second year retention for both student types. HS GPA, Fall semester HSU GPA, and Fall semester units earned were consistently the strongest predictors of retention for math students. Higher GPA s and a larger number of accumulated units were associated with stronger first and second year retention rates. Living in a dorm during the first year of college was positively related to first year retention for all math students. This finding suggests that requiring students to live in dorms during their freshman year may be a valuable way to increase retention. Being an undeclared major was negatively related to first year retention for RM but not CLMP students. Therefore, it may be advantageous for Humboldt State to implement policy requiring RM students to seek advising about possible career options and choosing a major early on. Being in a FIG was positively related to first and second year retention for both student types. Students who were in a FIG were more likely to be retained after the first and second year than students who did not take part in a FIG. Thus, a promising intervention strategy for increasing retention may be to make first year experiences mandatory for freshman. For remedial math URM students, being in EOP was positively related to first and second year retention. However, it is important to note that we cannot establish that being in an interest group caused retention to increase due to the fact that these analyses are correlational. For instance, it may be the case that more motivated students seek out interest groups than less motivated students; motivation being the factor accounting for higher retention rates in this scenario. Nonetheless, these results are promising and point to FIGs and EOP as possible intervention strategies for remedial math students. The next section will address six year graduation rates of RM versus CLMP students.

13 P a g e 13 Six Year Graduation Rates Retention rates allow us to examine where and when we lose students; however, retention is just an antecedent to the more important outcome graduation. We tend to see a large discrepancy between RM and CLMP students in six year graduation rates. Students who tested directly into college level math had six year graduation rates roughly 10% higher than those of remedial math students. Unfortunately, six year graduation rates are quite low for both RM 35% and CLMP students 45%. Six year graduation rates for remedial vs. college level math students Fall Student type Number Percent Needs math remediation % College level math proficient % Total % Humboldt State has an indisputable problem with graduating male students. Six year graduation rates for male RM students were 9% less than that of female RM students. This gap is substantially larger for CLMP students, where six year graduation rates for males were 15% lower than that of females. A comparison within gender categories shows a smaller discrepancy between male RM and CLMP students than females: female CLMP students had 13% higher six year graduation rates than female RM students, whereas male CLMP student six year graduation rates were only 7% higher than male RM students. Six year graduation rates for remedial vs. college level math students by sex Male Female Student type Number Percent Number Percent RM % % CLMP % % Overall, URM students had the lowest six year graduation rate 31% followed by unknown 37% and non URM 45%. There was no significant difference between males and females in six year graduation rates within URM status. However, there was a difference between URM status and needing math remediation, hinting at a possible interaction effect. Students who were URM and needed math remediation had the lowest six year graduation rate 27% while non URM college level math proficient students had the highest six year graduation rate 48% First-time freshman cohort graduation counts and rates in six years Non URM URM Unknown Number Percent Number Percent Number Percent Graduated % % % Not graduated % % % Note. Overall graduation rate was 41.2%.

14 P a g e First-time freshman cohort graduation counts and rates in six years by URM and math remediation Non-URM URM Unknown Number Percent Number Percent Number Percent RM % % 74 32% CLMP % % % Note. Graduation rates shown are within URM status and math status, not of total. Math students who needed remediation in English evidenced lower six year graduation rates than math students who did not need remediation in English. Students who needed remediation in both math and English had the lowest six year graduation rates at a meager 30%. Students who needed remediation in math but not English had a 5% higher graduation rate than students who needed remediation in English only. Seemingly, needing just English remediation is a greater barrier to student success than needing remediation in math alone. Six year graduation rates for remedial vs. college level math students by remedial English status Needs English and math remediation Needs only math remediation Student type Number Percent Number Percent RM % % CLMP % % Exceptional admits have extremely low six year graduation rates. Even for CLMP students, those who were exceptional admits had a 25% six year graduation rate. Additionally, exceptional admits who needed math remediation had six year graduation rates only 2% lower than that of CLMP exceptional admits. Hence, it does not appear that needing remediation in math affects exceptional admits all that much due to the fact that their six year graduation rates are already so poor. For regularly admitted students, those who were CLMP had 7% higher six year graduation rates than those who needed math remediation. The difference in six year graduation rates between regular and exceptional admits is staggering especially among CLMP students: exceptional admit CLMP students had six year graduation rates 21% lower than that of CLMP regular admits, whereas RM exceptional admits six year graduation rates were 16% lower than that of RM regular admits. Six year graduation rates for remedial vs. college level math students by admission status Exception admit Regular admit Student type Number Percent Number Percent RM 82 23% % CLMP 38 25% %

15 P a g e 15 Low income students were more likely to graduate than non low income students. This result is unanticipated, given that low income students historically show lower graduation rates than non low income students. Interestingly, low income RM students had six year graduation rates equivalent to CLMP non low income students 40%. RM non low income students had by far the worst six year graduation rates at 28%, whereas almost half of low income CLMP students graduated within six years. Six year graduation rates for remedial vs. college level math students by low income Low income Not low income Student type Number Percent Number Percent RM % % CLMP % % Students on academic probation were not likely to graduate, regardless of whether they needed remediation. For both CLMP and RM students on academic probation, six year graduation rates were the same: 17%. This appears to be the lowest graduation rate for any group of students. Among students in good standing, RM students lagged behind CLMP students in six year graduation rates by 11%. Six year graduation rates for remedial vs. college level math students by academic standing Good academic standing Probation Student type Number Percent Number Percent RM % 48 17% CLMP % 71 17% Being in a Freshman Interest Group (Fig) was positively related to graduation for RM students only. RM students in a FIG had six year graduation rates 9% higher than RM students who were not in a FIG. Six year graduate rates for remedial vs. college level math students by FIG FIG Not in FIG Student type Number Percent Number Percent RM % % CLMP % % EOP was negatively related to six year graduation rates for URM students who needed remediation in math; however, EOP was unrelated to graduation for URM college level math proficient students. URM students who needed math remediation in EOP had a 10% lower graduation rate than students not EOP.

16 P a g e 16 Six year graduate rates for remedial vs. college level math URM students by EOP EOP Not in EOP Student type Number Percent Number Percent URM needs math remediation 60 23% 66 33% URM college level math proficient 32 39% 83 35% SAT scores were related to six year graduation rates for only RM students, wherein stronger SAT scores related to higher six year graduation rates. On average, there was a 20 point difference in SAT math scores for RM students who graduated in six years versus RM students who did not graduate in the six year time frame. Verbal SAT scores show a similar pattern: about a 25 point difference between RM students who graduated in six years versus RM students who did not. HS GPA continues to be a strong predictor of success; stronger HS GPA was associated with higher six year graduation rates for both RM and CLMP students. Additionally, first semester HSU GPA and units earned was strongly related to six year graduation rates for all math students. Means and standard deviations for SAT scores, HS GPA, Fall semester HSU GPA, and units earned at the end of Fall semester by six year graduation and math student type Graduate in six years Did not graduate in six years M SD M SD SAT math RM CLMP SAT verbal RM CLMP HS GPA RM CLMP Fall semester RM HSU GPA CLMP Fall semester RM units earned CLMP

17 Units earned at the end of Fall semester P a g e 17 Six year graduation rates by Fall semester units earned Student type RM CLMP Benchmark for CLMP Benchmark for RM Yes No Graduate in six years Note. Error bars represent 95% confidence intervals. RM = remedial math students. CLMP = college level math proficient students. One of the milestone events in student pathway to completion set forth by the Educational Trust is to earn 24 college level units by the end of the first year. For that reason, earning 24 college level units can be taken as a benchmark indicator of success. Broken down by semester, the benchmark indicator is an average of 12 college level units i.e., half the original number of units. The above graph shows that CLMP students who graduated in six years fell above the benchmark indicator of 12 units, whereas CLMP students who did not graduate in six years fell below the benchmark indicator. For RM students, the benchmark indicator is slightly different because we need to

18 P a g e 18 account for the fact that remedial math course units do not count toward overall college level units. Thus, if the average remedial math course is worth three units e.g., Math 44 that do not officially count toward college level units, and we make the assumption that most remedial math students take remedial math during their first semester, then we would expect the average RM student to accumulate three units less than CLMP students at the end of their first semester. Given these assumptions, RM students would have earned 9 college level units by the end of the first semester; thus for these students 9 units would be considered a benchmark indicator of success. The data presented in the graph support this hypothesis: for RM students who graduated in six years, the average number of units earned by the end of Fall semester fell above the benchmark indicator, whereas the average number of units for RM students who did not graduate in six years fell below the 9 unit mark. Regression Analyses on Six Year Graduation Rates Comparison of six year graduation rates of remedial math students with those ready for college level math Fall inclusive Remedial Students CL Math Students Demographic and Attendance Characteristics Male - - Age ns ns URM - - Disabled ns ns HS GPA + + SAT math + ns SAT verbal + ns Needs remediation in English - - Exception admit - - Low income + + Success Indicators FIG + ns EOP - URM - ns In dorm ns ns Academic probation - - Undeclared major ns ns Fall semester Humboldt GPA + + Units earned at the end of Fall semester Indicates a statistically significant (p <.03) positive relationship with likelihood of retention. - Indicates a statistically significant (p <.03) negative relationship with likelihood of retention. ns Statistically not significant, * indicated a marginally significant predictor (p <.06).

19 P a g e 19 Regression analyses on six year graduation rates among math students were performed on individual cohorts from Fall 2000 Fall After finding similar results across years, the decision was made to aggregate the data for final analyses. Results show that six year graduation rates for males lagged behind females for both RM and CLMP students. Other factors that were negatively related to six year graduation rates for all math students included being a URM, needing remediation in English, being an exceptional admit, and being on academic probation. Factors positively related to six year graduation rates were HS GPA, low income, Fall semester HSU GPA, and units earned at the end of Fall semester. HS GPA, Fall semester HSU GPA and units earned were the strongest predictors of six year graduation rates among all variables tested. Because of the strong predictive power of these variables, it may be promising to monitor student progress more closely in order to implement interventions for students who are not meeting benchmark indicators of success after their first semester i.e., a certain GPA and number of college level units. Unfortunately, these indicators must be measured after the fact, lessening the chance that these students will be retained and graduated. The result that low income was associated with stronger six year graduation rates for math students is puzzling because it is not supported by research literature. Generally, low income students have lower graduation rates than non low income students. It may be the case that there is an interaction between low income and financial aid, making the relationship between low income and graduation more complex than it seems at first glance. By triangulating financial aid data with low income status, we may be able to delineate a more complete picture of this relationship in future analyses. Factors that predicted six year graduation rates for RM but not CLMP students include SAT scores, being in a FIG, and being in EOP for URM students. Higher SAT scores and being in a FIG were associated with greater success among RM students, whereas being in EOP was inversely related to success for URM remedial math students i.e., URM remedial math students in EOP had lower retention rates than URM remedial math students not in EOP. It is surprising that EOP was negatively related to six year graduation rates for URM remedial math students because EOP was associated with higher first and second year retention rates for math students. It could be the case that this result was obtained by chance and does not reflect a true difference i.e., a Type I error occurred. The finding that FIGs was associated with higher six year graduation rates for RM students adds validity to earlier analyses on the relationship between FIGs and retention. Taken together, these analyses suggest First year freshman experiences are a promising intervention for retaining and graduating remedial math students. Perhaps by requiring remedial students to take part in a, HSU may increase success among these students.