A Quantitative Approach to the Identification of Factors that Contribute to Graduation & Attrition at an Hispanic Serving Institution

Size: px

Start display at page:

Download "A Quantitative Approach to the Identification of Factors that Contribute to Graduation & Attrition at an Hispanic Serving Institution"

Elinor Weaver
5 years ago
Views:

A Quantitative Approach to the Identification of Factors that Contribute to Graduation & Attrition at an Hispanic Serving Institution The University of

1 A Quantitative Approach to the Identification of Factors that Contribute to Graduation & Attrition at an Hispanic Serving Institution The University of Texas at El Paso Center for Institutional Evaluation, Research and Planning CIERP gratefully acknowledges the support of Lumina Foundation for Education

2 Presentation Outline UTEP s Efforts to Ensure Student Success UTEP s context Efforts over last 20 years and their impact Current challenges Student Success Project: methodology Findings, implications and next steps

3 UTEP s Context El Paso, Texas El Paso County-3rd poorest large county in the US 1 Population: 724,000 81% Hispanic Border community, very dynamic flow of residents and students across the border Limited educational opportunities American Community Survey of the US Census

UTEP s Efforts over last 20 years President Diana Natalicio has rededicated UTEP s mission to ensure the widest possible access to all students from the region, and to focus on

4 UTEP s Efforts over last 20 years President Diana Natalicio has rededicated UTEP s mission to ensure the widest possible access to all students from the region, and to focus on serving the El Paso area Institution has made efforts to ensure success at all levels of the pipeline, with impressive results K-12 Admissibility/ Affordability Student engagement

5 UTEP Demographics Enrollment by Race/Ethnicity N % White Non-Hispanic % Black Non-Hispanic % Hispanic % Asian/Pacific Islander % Am. Indian or Alaskan % International* % *includes Mexican Nat l. students Total Enrollment by Residence N % El Paso County % New Mexico % Mexico % Other Int l % Percent of financial aid awardees with family income of $20,000 or less: 43% Percent of UTEP students with reported family income of $20,000 or less: 33% Nationally: % of students with family income of less than $20,000 at large public research (doctoral) universities: 10% 1 % of students with family income of less than $20,000 at small &mid-sized private colleges and universities: 12% 1 % of students with family income less than $20,000 at community colleges: 29% 2 1 Council of Independent Colleges: 2 Lumina Foundation Focus, Fall 2005, p.5

6 El Paso Collaborative for Academic Excellence Founded in 1991; partners include the National Science Foundation, the U.S. Department of Education and The Pew Charitable Trusts, in addition to businesses and organizations in the community and throughout Texas Goals of the Collaborative Ensure academic success for all students, K-16 Ensure that all students graduate from high school prepared to succeed in a fouryear college or university Close achievement gaps among different groups of students

7 Completion of Recommended High School Program or Higher, El Paso Districts & Statewide Class of % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 91% 72% 90% 72% 93% 73% 91% 65% All Students Hispanic White African American El Paso Urban Districts Statewide Source: Texas Education Agency,

8 Affordability UT System Full-time Undergraduate Students with Need-Based Grant Aid, AY UT System Institution Average In-State Total Academic Cost, Fall Spring 2006 combined w/ fees % Students Receiving Need- Based Grant Aid Average % Discount Arlington $ % 71.6% Austin $ % 80.8% Brownsville $ % 65.1% Dallas $ % 61.5% El Paso $ % % Pan American $ % % Permian Basin $ % 54.3% San Antonio $ % 64.3% Tyler $ % 89.1% Average $ % 76.9% Source: UT System Fast Facts, 2007

UTEP s Institutional Successes The National Survey of Student Engagement and the American Association for Higher Education identified UTEP as one of 20 colleges and universities that was unusually

9 UTEP s Institutional Successes The National Survey of Student Engagement and the American Association for Higher Education identified UTEP as one of 20 colleges and universities that was unusually effective in promoting student success. 1 UTEP is identified as only one of six Model Institutions for Excellence in the nation by the National Science Foundation for its success in creating educational opportunities for non-traditional students. UTEP s College of Engineering was identified as the top engineering school for Hispanics by Hispanic Business Magazine. The magazine says UTEP is changing the face of engineering and producing highly trained graduates heavily recruited by the industry s leading companies UTEP Alumnus Danny Olivas, NASA astronaut scheduled for flight on the shuttle Atlantis in June NSSE Institute for Effective Educational Practice, Project DEEP Final Report, p. 4 2 Hispanic Business, September 2006

10 Despite All the Success, UTEP has More Work to Do Same Institution Gradation Rate 35% 30% 25% 20% 15% 10% 5% 0% 2.50% 4yr Fall % 4yr Fall % 16.70% 5yr Fall 5yr Fall Entering Cohort 25.10% 6yr Fall % 6yr Fall 1999

Goals of the UTEP Student Success Project Funded by Lumina Foundation Identify factors that affect students success timely progress toward a degree.

11 Goals of the UTEP Student Success Project Funded by Lumina Foundation Identify factors that affect students success timely progress toward a degree. Identify & implement strategies to improve the success of students at UTEP. At this preliminary stage, there were two study questions and quantitative approaches.

12 Research Questions 1. Predictors of Success What factors explain graduation within 6 years at the University of Texas at El Paso? 2. Predictors of Risk What factors explain why students fail to graduate within 6 years?

13 Factors that Affect Student Success SOCIO-ECONOMIC STATUS EXTERNAL RESPONSIBILITIES OTHER THAN WORK (e.g., CHILDREN) QUALITY OF HIGH SCHOOL PREPARATION INTENTIONS (NOT ASPIRATIONS) WORK HOURS (FT/PT) NUMBER OF HIGHER ED INSTITUTIONS ATTENDED (TRANSFERS) FINANCIAL AID ADVISING QUALITY FACULTY INTEGRATION/HAPPINESS CLARITY OF DEGREE REQUIREMENTS READING/WRITING PLACEMENT MATH PLACEMENT INTEGRATION INTO UNIVERSITY ENVIRONMENT (EXTRA-CURRICULARS) INTEGRATION INTO UNIVERSITY ENVIRONMENT (FACULTY/STAFF) ENROLLMENT (FT/PT) NUMBER OF DROPS, WITHDRAWLS & INCOMPLETES PER SEM. MOTIVATION LOW GPA NUMBER OF CREDIT HRS EARNED PER SEM. G R A D U A T I O N R A T E External Factors Shared External/Institutional Factors Institutional Factors Student-Based Factors

14 Data and Sample Cohort Entering Students from Fall 1999 and Fall 2000 (Sample size = 2,065) Data provided clean, reliable set to examine the 6 yr. graduation rate Undergraduates only 1 st time (non-transfer) students Full-time students only

15 Research Approach: Development of a Model to Predict Graduation in 6 Years Logistic Regression Conducted with the binary prediction of Graduation-Yes (1) or Graduation-No (0)* within six years Conducted in five steps Variables entered sequentially, from demographics to college academic performance *Includes not yet graduated

16 23 Variables Considered as Predictors of Graduation: Age (standardized) Educational level of parents Hrs. per week spent working (anticipated for 1 st term, self-report) 1 Number of dependents (children & other family members) 1 ACT Scores (standardized) Math Placement Level (BANM) Reading Placement Level (BANR) Writing Placement Level (BANW) English Placement Level (BANE) High School Percentile Rank 1 st Term GPA standardized (GPA for which we have all students data; past behavior is a predictor of future behavior ) Number of classes failed in 1 st term 1 New Student Survey administered to all new students annually by UTEP-CIERP Personal perception that one will drop out before graduation 1 Personal perception that one will need to study harder at UTEP than in high school to get good grades 1 Personal perception that it is important to prepare for class 1 Personal perception that one will change majors at least once 1 Personal perception that it is important to prepare for class 1 Average number of credit hours attempted (standardized) Need (based on Household Income) Grant- Amount Paid Scholarship- Amount Paid Student Loan- Amount Paid Work-Study- Amount Paid

17 Understanding Logistic Regression Outputs Statistically Significant Predictors Odds Ratio P < Gender (Female) Educational level of parents* Both parents graduated from college Dependent (do not have dependent) * Reference group is Neither parent ever attended college. Note: Nagelkerke R Square is.040. Percentage correctly classified is Income and age did not qualify into the regression equation.

18 Modeling Factors that Explain At-Risk Group Membership Multinomial Logistic Regression is ideal for examining factors that help predict membership in a defined category when the outcome is more than binary (i.e. graduating or not). 7 Categories versus 2 Categories considered in the model. The model produced offers information about institutional interventions for particular groups. Objective: Resources can be more effectively targeted toward these at-risk groups.

19 Identifying At-Risk Students 1. 1 st Semester Leavers: Students who left UTEP in the first semester and never returned. These individuals are arguably a very high-risk group st Year Leavers: Students who left UTEP in the first year and never returned; arguably also a high-risk group nd Year Leavers: Students who left at some point in the second year and never returned to UTEP rd Year Leavers: Students who left at some point in the third year and never returned to UTEP. 5. Sporadic Leavers: Students who left at some point in their college career and returned, yet did not graduate. 6. Persisters: Students who were continually enrolled at UTEP between the Fall of 1999 and the Fall of 2005, yet did not graduate.

20 Understanding Multinomial Logistic Regression Outputs Significant Predictors Odds Ratio P < Failing one or more classes Working more hours Lower High school percentile Higher Likelihood of Sporadic Leaving Lower Likelihood of Sporadic Leaving Higher Math Placement Score Average Credits Attempted Increasing 1 st Term GPA _

21 Descriptive Stats College Graduation within 6 Years by High School Rank Percentile 60 Percent of Students who Graduated from UTEP within Six Years Percentage graduated top 25% 75% to 50% less than 50% High School Rank Percentile

22 Descriptive Stats College Graduation within 6 Years by Math Placement Level Percent of Students who Graduated from UTEP within Six Years Percentage graduated 23.3 Level 1-- Two Semesters Below College 37.1 Level 2-- One Semester Below College 52.5 Level 3--College 75 Level 4--College Math Placement Level

23 Descriptive Stats College Graduation within 6 Years by Hours Worked per Week Percent of Students who Graduated from UTEP within Six Years Not Employed hours per week hours per week percentage graduated hours per week hours per week Anticipated Hours of Employment per Week indicated on the UTEP New Student Survey

24 Descriptive Stats College Graduation within 6 Years by Household Income Pecent of Students who Graduated from UTEP within Six Years percentage graduated k or less 20 to 35k 35 to 50k 50 to 65k 65k or more Houshold Income

25 Descriptive Stats College Graduation within 6 Years by Classes Failed-1 st Semester Percentage of Students who Graduated within Six Years percentage graduated No failed classes failed one class failed two or more classes Number of classes failed

26 Graduated Graduation Indication Not Graduated Distribution of GPA First term GPA Frequency

27 Graduated Graduation Indication Not Graduated Distribution of ACT ACT ACT Frequency

28 Distribution of ACT for different Income groups ACT 18

29 Descriptive Statistics of ACT Scores by Income Group Income group N Mean Median Std. Deviation Less than 20k k to 35k k to 50k k to 65k k or more Total 1,

30 Step 1: Demographics In this step, only demographic variables were considered: Gender Income Educational level of parents Having a dependent Age

31 Step 1: Logistic Regression Statistically Significant Predictors Odds Ratio P < Gender (Female) Educational level of parents* Both parents graduated from college Dependent (do not have dependent) * Reference group is Neither parent ever attended college. Note: Nagelkerke R Square is.040. Percentage correctly classified is Income and age did not qualify into the regression equation.

32 Step 2: High School Preparation Variables considered in this step: High school class rank Math Placement score ACT /SAT score Writing Placement score Reading Placement score English Placement score

33 Step 2: Logistic Regression Statistically Significant Predictors Odds Ratio P < Math Placement Score* Level Level Level Gender (Female) High school percentile** Between 75 and (2.82).001 Less than (6.29).001 * Reference group is level 1. ** Reference group is top 25. Note: Nagelkerke R Square is.216. Percentage correctly classified is Educational level of parents and dependent did not qualify for inclusion in the regression equation.

34 Step 3: Student Commitment Variables considered in this step are personal perceptions 1 that: One will drop out before graduation One will need to study harder at UTEP than in high school to get good grades It is important to prepare for class One will change majors at least once One will need more than four years to graduate Confident one will graduate 1 Data were collected from the UTEP New Student Survey

35 Step 3: Logistic Regression Statistically Significant Predictors Odds Ratio P < Math Placement Score* Level Level Level Gender (Female) Do not need more than 4 years to graduate Disagree it is important to prepare for class 0.729(1.37).05 High school percentile** Between 75 and (2.77).001 Less than (6.94).001 * Reference group is level 1. ** Reference group is top 25. Note: Nagelkerke R Square is.229. Percentage correctly classified is The rest of the variables considered in step 3 did not qualify to the regression equation.

36 Step 4: First Semester Performance Variables considered in this step: GPA Credits attempted Hours worked per week Number of classes failed

37 Step 4: Logistic Regression Statistically Significant Predictors Odds Ratio P < GPA Math Placement Score* Level Level Level Gender (Female) Do not need more than 4 years to graduate Credits attempted Disagree it is important to prepare for class 0.698(1.43).05 High school percentile** Between 50 and (1.56).05 Less than (2.64).001 Hours worked per week*** Working hours per week.448(2.23).05 Number of classes failed**** Failing one class.530(1.89).001 Failing two or more classes.105(9.52).001 * Reference group is level 1. ** Reference group is top 25. *** Reference group is not working. **** Reference group is not failing a class. Note: Nagelkerke R Square is.40. Percentage correctly classified is 76.6.

38 Significant Predictors (in Bold) Gender Income Educational level of parents Having a dependent Age High school class rank Math Placement score ACT /SAT score Writing Placement score Reading Placement score English Placement score Will drop out before graduation Will need to study harder at UTEP than in high school to get good grades It is important to prepare for class Will change majors at least once Do not need more than four years to graduate Confident that one will graduate GPA Credits attempted Hours worked per week Number of classes failed

39 Identifying At-Risk Students (cont.) Fall 1999 & Fall 2000 Cohort N % Graduated in </= 6 Years Left UTEP in the 1 st Semester Left UTEP in the 1 st Year Left UTEP in the 2 nd Year Left UTEP in the 3 rd Year Sporadically Left UTEP Persisters Total %

40 Variable Summary of the Multinomial First Term Model First Yr. Second Yr. Third Yr. Sporadic Persisters GPA SCH Failing class Working Math Need No dependent Disagree it is important to prepare for class High School rank Not needing more than four years Loan Paid 1.39 Grant Paid

41 Institutional Responsibility Vs Student Responsibility Student responsibility (the intersection of choice with opportunity) is a major theme... some recommendations for students, who are partners in their own education fate, who shouldn t wait around for someone else to do something for them, and who are rarely addressed in studies of attainment, Toolbox Revisited, p. xxvi. Students are explicit, rather than implicit... They are respected adults playing large roles in their own destinies... While we trust that school and college actions will not leave them behind, they have equal responsibilities. Source: Adelman, C. The Toolbox Revisited: Paths to Degree Completion from High School Through College. Washington, D.C.: U.S. Department of Education, February 2006

Implications from the UTEP Student All students can be successful Family/ household Income is not a predictor of student success Ethnicity is not a predictor of success ACT (SAT) score is not a

42 Implications from the UTEP Student All students can be successful Family/ household Income is not a predictor of student success Ethnicity is not a predictor of success ACT (SAT) score is not a predictor of success Success Project But, student s choices are important in ensuring success The challenge is to create institutional structures to shape student choices that will ensure success.

43 Next Phase of Study Refine at-risk and explore alternative models Latent growth models Markov models Explore major issues more closely (advising, role of faculty, working, financial aid, course failure) Develop interventions

44 Contact Information Roy Mathew, Ph.D. Director Center for Institutional Evaluation, Research and Planning The University of Texas at El Paso Administration Building, Room 318 (915) Denise Carrejo, Ph.D. Assistant Director Center for Institutional Evaluation, Research and Planning The University of Texas at El Paso Administration Building, Room 318 (915) Thomas J. Taylor Doctoral Student Center for Institutional Evaluation, Research and Planning The University of Texas at El Paso Administration Building, Room 318 (915) This AIR 2007 Presentation is available at:

An Empirical Analysis of the Effects of Mexican American Studies Participation on Student Achievement within Tucson Unified School District

An Empirical Analysis of the Effects of Mexican American Studies Participation on Student Achievement within Tucson Unified School District Report Submitted June 20, 2012, to Willis D. Hawley, Ph.D., Special