enrollment research team aacrao-sem nov. 2013 chicago compton, forbes, ralston, wohlgemuth, 2013...

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Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in Time to Degree and Debt at Graduation Jonathan Compton, Greg Forbes, Kate Ralston, Darin Wohlgemuth Enrollment Research Team Iowa State University November 11, 2013 AACRAO - SEM Chicago, IL

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Page 1: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Dissecting the End: Factors that Explain Differences in Time to

Degree and Debt at Graduation

Jonathan Compton, Greg Forbes,Kate Ralston, Darin Wohlgemuth

Enrollment Research TeamIowa State University

November 11, 2013AACRAO - SEM

Chicago, IL

Page 2: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Enrollment Research Team @ ISU

• Darin Wohlgemuth, Interim Director of Admissions,

& Director of Enrollment Research

• Jonathan Compton, Registrar’s Office

• Greg Forbes, Student Financial Aid

• Kate Ralston, Office of Admissions

• Julia Sullivan, Student Financial Aid

Page 3: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Enrollment Research Team @ ISU

Vice President for Student Affairs

Registrar

Associate VP for Student Affairs

Admissions & New Student Programs

Student Financial Aid

Financial Aid Research

Admissions Research

Registrar Research

Director of Enrollment Research

Page 4: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

• Established 1858 • Land grant, research-intensive institution with extension

service• Seven colleges with undergraduate, graduate and

professional programs• Fall 2012 - 8,780 FTE Employees

– 1,694 Faculty, 2,515 P&S, 1,408 Merit, 2,934 Students• FY2013 Budget - $1,214M Total Revenues

– $580M General Fund– $318M Tuition Revenue and $222M State Appropriations

A little bit about Iowa State…

Page 5: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Enrollment at Iowa State University

• Records set this year! Fall 2013 Fall 2012

– Total Enrollment 33,241 31,040

– Undergraduates 27,659 25,553

– New Direct from High School 6,089 5,366

– New Transfers 2,014 1,851

– Minority + International 7,486 6,765

– Record FAFSAs received

– Record Financial Aid dollars disbursed

Page 6: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Freshman Admissions Requirements

• Regent Admissions Index (≥ 245 Guaranteed)5 x Core Courses +

2 x ACT +

HS Percentile Rank +

20 x HS GPA

• 15,204 Domestic Freshman Apps• 90% Offered Admission• 42% Yield

Page 7: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Overview

• Graduation Rates and Time to Degree• Methodology• Factors & Data• Cross Tabs & Analysis of Variance• Regression Analysis• Path Analysis• Implications

Page 8: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Survey

What is your 4-yr Graduation Rate?

What is your 6-yr Grad Rate?

What is your 5-yr Grad Rate?

Page 9: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Time to Degree

• National & local interest in increasing 4-year graduation rates

• President’s College Affordability Plan– U.S. Dept. of Education proposes using indicators

to rate colleges (e.g. FTFT graduation rates)

• Performance based state funding• Rankings: U.S. News & World Report

Page 10: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Retention & Graduation Rates

Page 11: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Research Questions• What factors drive time to degree at Iowa

State?

• Do the same factors impact debt upon graduation?

• Does increased time to degree lead to higher loan debt upon graduation?

Page 12: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

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AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Methodology

• Define the Population

• Data set up & gathering

• Analysis

• Implications

Page 13: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

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AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

What is the population?

• Retention– Entry cohort looking forward

• Graduation– Entry cohort looking forward

• Time to Degree Analysis– Graduates looking backwards (Survivors)

Page 14: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

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AACRAO-SEM

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What is the population?

• Undergraduate

• First Time Freshman

• Admitted between 2000 and 2005

• Graduated within 8 years

Page 15: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

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AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Factors• What factors cause students to extend their

time to graduation? Debt? • Demographic, Academic, Experiential, FinancialDemographics Academic Experiential Financial

Gender HS Class Rank Study Abroad Borrowing

Minority ACT/SAT Internships Financial Need

Residency Early Credits Minor Pell Eligibility

1st Term GPA Learning Community

Scholars Award Program

1st Term Credits STEM Major High Ability Scholarship

Changing Major College Choice

Failed Courses Double Major

Dropped Courses Double Degree

5 Yr Programs

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AACRAO-SEM

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What data do you need?And, where do you get it?

• Graduation record• Grades & Courses• Enrollment behavior• Demographics• Academic characteristics• Experiential• Soci-economic status• Financial aid package

Registrar Registrar Registrar Registrar / Admissions Admissions Program coordinators Fin Aid / Admissions Financial Aid

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AACRAO-SEM

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Death by Cross tabs

It appears that Debt is impacted by Time to Degree, but what impacts Time to Degree?

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AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Death by Cross tabs

Student success in individual courses appears to have an impact on Time to Degree

Page 19: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Death by Cross tabs

Student success in individual courses appears to have an impact on Time to Degree

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AACRAO-SEM

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Death by Cross tabs

Major Choice and Major Changes appear to have an impact on Time to Degree

Page 21: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Death by Cross tabs

Major Choice and Major Changes appear to have an impact on Time to Degree

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Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Death by Cross tabs

Does Financial Need have an impact on Time to Degree? How do you know? Analysis of Variance (ANOVA)

Page 23: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

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Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Analysis of Variance(One Way ANOVA)

Need Group Mean Time to Deg Significance*$0 4.479 -$1 - $4,999 4.485 0.99$5,000 - $9,999 4.494 0.98$10,000 or more 4.515 0.62

Enrolled College Mean Time to Deg Significance*College 1 4.435 -College 2 4.303 0.00College 3 4.626 0.00College 4 4.698 0.00College 5 4.253 0.00College 6 4.352 0.98

*Significance between groups calculated on graduating within four years using oneway anova with the Scheffe adjustment.

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Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Factors that Extend Time to Degree

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Influence of Multiple Variables

Internship participation and majoring in a STEM field impact time to degree.How much influence does each of these have individually?Lets take this to the next level, Regression

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Multiple Regression AnalysisTime to degree

• Determine influence of each variable

• Holds other factors constant

• Shows what is and is not important

• Useful in predicting time to degree

Page 27: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

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Regression Analysis – Time to degree (Demographics)

  Coef. P>|t| BETAFemale -0.1646 0 -0.11387Nonresident -0.0232 0.04 -0.01359Minority 0.0316 0.23 0.011332International -0.0652 0.44 -0.00437Constant 3.9672

What does this mean for a Domestic Female Non-minority student from Out of State?

𝑅2=0.482

𝑇𝑖𝑚𝑒𝑡𝑜𝐷𝑒𝑔𝑟𝑒𝑒=𝟑 .𝟗𝟔𝟕𝟐+ (−𝟎 .𝟏𝟔𝟒𝟔∗𝟏 )+(𝟎 .𝟎𝟑𝟏𝟔∗𝟎 )+(−𝟎 .𝟎𝟐𝟑𝟐∗𝟏 )+(−𝟎 .𝟎𝟔𝟓𝟐∗𝟎 )+…𝑇𝑖𝑚𝑒𝑡𝑜𝐷𝑒𝑔𝑟𝑒𝑒=𝟑 .𝟕𝟕𝟗𝟒+…

𝑻𝒊𝒎𝒆𝒕𝒐 𝑫𝒆𝒈𝒓𝒆𝒆=𝑪𝒐𝒏𝒔𝒕𝒂𝒏𝒕+(−𝟎 .𝟏𝟔𝟒𝟔 ) 𝑭𝒆𝒎𝒂𝒍𝒆+ (𝟎 .𝟎𝟑𝟏𝟔 ) 𝑴𝒊𝒏𝒐𝒓𝒊𝒕𝒚 + (−𝟎 .𝟎𝟐𝟑𝟐 )𝑵𝒐𝒏𝒓𝒆𝒔𝒊𝒅𝒆𝒏𝒕+ (−𝟎 .𝟎𝟔𝟓𝟐 ) 𝑰𝒏𝒕𝒆𝒓𝒏𝒂𝒕𝒊𝒐𝒏𝒂𝒍+…

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Regression Analysis – Time to degree (Academics)

  Coef. P>|t| BETA

F grades 0.1684 0 0.453044

Dropped Classes 0.0644 0 0.149557

Early Credits -0.0131 0 -0.14743

HS Rank -0.0061 0 -0.13987

Major Change 0.0854 0 0.107271

First term Credits -0.0258 0 -0.06452

First term GPA 0.0039 0.63 0.003698

ACT score 0.0007 0.64 0.003669

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Regression Analysis – Time to degree (Experiences)

  Coef. P>|t| BETA

Co-op / Internship 0.2517 0 0.196777

140+ Credit Program 0.8392 0 0.179233

Double Degree 0.4686 0 0.103345

STEM 0.1062 0 0.073636

Double Major 0.1432 0 0.063713

Study Abroad 0.1067 0 0.050735

Minor 0.0698 0 0.042752

Learning Community 0.0187 0.04 0.012923

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Regression Analysis – Time to degree (College Choice)

  Coef. P>|t| BETA

College 1 Held Out

College 2 -0.0357 0.03 -0.01529

College 3 0.1199 0 0.05077

College 4 0.2421 0 0.150463

College 5 -0.1118 0 -0.04281

College 6 0.0291 0.06 0.012934

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Regression Analysis – Time to degree (Financial)

  Coef. P>|t| BETA

Debt at graduation ($1,000’s) 0.0030 0 0.094343

Financial Need ($1,000’s) -0.0054 0 -0.04443

Pell Elig 0.0525 0 0.02906

Merit Award -0.0271 0.04 -0.0183

Award Program G -0.0246 0.51 -0.0053

Award Program M 0.0045 0.92 0.000915

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Regression Analysis – Debt Upon Graduation

Factor Variable Coef. P>|t|

Experiential

140+ Credit Program 8925.488 0

Learning Community -2244.05 0

Double Degree 4793.96 0

Study Abroad 1817.34 0

Co-op/Internship 975.77 0

STEM 577.87 0.26

Double Major 518.30 0.30

Minor 229.80 0.53

Financial

Financial Need 1.61 0

Pell Elig -7914.45 0

Award Program G -9306.05 0

Award Program M -9272.89 0

Merit Award -89.14 0.85

Factor Variable Coef. P>|t|

Demographics

Female 1598.47 0

Intl -16215.75 0

Nonresident -1253.81 0.00

Minority -33.56 0.97

Academics

HS Rank 283.91 0

F grades 1997.81 0

Dropped Classes 1187.77 0

First term GPA -2773.99 0

ACT score -310.73 0

Early Credits -103.50 0

First term Credits -382.24 0

Major Change 154.13 0.42

Enrolled

College

College 1 Held Out

College 2 -2657.77 0

College 3 2034.61 0.00

College 4 2650.36 0

College 5 -1419.74 0.03

College 6 -755.43 0.19

𝑅2=0.231

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Regression Analysis – Time 2 Degree v. Debt Time to

DegreeStudent Debt

Factor Variable P>|t| P>|t|

Demographics

Female 0 0Minority 0.23 0.97Nonresident 0.04 0.00International 0.44 0

Academics

HS Rank 0.00 0ACT score 0.64 0Early Credits 0 0First term GPA 0.63 0First term Credits 0 0F grades 0 0Dropped Classes 0 0Major Change 0 0.42

Enrolled

College

College 1  Held OutCollege 2 0.03 0College 3 0 0.00College 4 0 0College 5 0 0.03

College 6 0.06 0.19

  

Time to Degree

Student Debt

R squared statistic 0.482 0.241

Factor Variable P>|t| P>|t|

Experiential

140+ Credit Program 0 0STEM 0 0.26Co-op/Internship 0 0.00Study Abroad 0 0Learning Community 0.04 0Minor 0 0.53Double Degree 0 0Double Major 0 0.30

Financial

Debt at graduation 0 Financial Need 0 0Pell Elig 0 0Award Program G 0.51 0Award Program M 0.91 0Merit Award 0.03 0.85

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Interaction of Independent Variables

Both variables impact Time to Degree, but is their a relationship between the variables that may impact the analysis?

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Interaction of Independent Variables

A relationship appears to exist, how do we account for this influence?Path Analysis

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Path Model

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Model Fit

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Meaningful coefficients

Page 39: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

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Meaningful coefficients

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Meaningful coefficients

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Meaningful coefficients

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So now what?

• Value added as part of education…

• Balance between time to degree and value

added opportunities

• Performance based funding

• Curriculum construction

• Student advising

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Data on placement rates by coop-internships

Internship Participation Placement at Graduation

Co-op (2 internships with same company) 80%

Fall/Spring term internship 75%

Summer internship 70%

No experiential education 53%

Overall placement6 months after graduation 95%

Data based on ECS review of 7,000 engineering graduates

“Graduates that don’t have an experiential work experience on their resume have fewer employment opportunities and have to work a lot harder to connect with an employer willing to give them a chance.” – ISU Engineering Career Services

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Taking This Home

• How might you use the results?

• Who on your campus has the necessary data?

• Who has the skills and tools?

• Who on your campus is interested?

• Who needs to be interested?

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Comments & QuestionsContact Information

Jonathan: [email protected]

Greg: [email protected]

Kate: [email protected]

Darin: [email protected]

Thank you for attending this morning!

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Additional Slides

-Regression Detail (T2D)

Other?

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Regression Analysis – Time to Degree

𝑅2=0.482

Factor Variable Coef. P>|t|

Demographics

Female -0.1646 0Minority 0.0316 0.23NonRes -0.0232 0.04Intl -0.0652 0.44

Academics

HS Rank -0.0061 0.00ACT score 0.0007 0.64Early Credits -0.0131 0First term GPA 0.0039 0.63First term Credits -0.0258 0F grades 0.1684 0Dropped Classes 0.0644 0Major Change 0.0854 0

Enrolled

College

College 1 Held OutCollege 2 -0.0357 0.03College 3 0.1199 0College 4 0.2421 0College 5 -0.1118 0College 6 0.0291 0.06

Factor Variable Coef. P>|t|

Experiential

140+ Credit Program 0.8392 0

STEM 0.1062 0

Coop/Internship 0.2517 0

Study Abroad 0.1067 0

Learning Community 0.0187 0.04

Minor 0.0698 0

Double Degree 0.4686 0

Double Major 0.1432 0

Financial

Debt at graduation 0.0000 0

Financial Need 0.0000 0

Pell Elig 0.0525 0

Award Program G -0.0246 0.51

Award Program M 0.0045 0.91

Strategic Award -0.0271 0.03

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Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Regression Analysis – Time to degree (Demographics)

  Coef. Std. Err. t P>|t| BetaFemale -0.1646 0.0096 -17.22 0 -0.1139Minority 0.0316 0.0263 1.2 0.229 0.0113Nonresident -0.0232 0.0113 -2.05 0.04 -0.0136Intl -0.0652 0.0848 -0.77 0.442 -0.0044

Page 49: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Regression Analysis – Time to degree (Academics)

  Coef. Std. Err. t P>|t| BetaHS Rank -0.0061 0.0019 -3.22 0.001 -0.1399ACT score 0.0007 0.0014 0.47 0.637 0.0037Early Credits -0.0131 0.0005 -24.66 0 -0.1474First term GPA 0.0039 0.0081 0.48 0.633 0.0037First term Credits -0.0258 0.0024 -10.57 0 -0.0645F grades 0.1684 0.0032 51.93 0 0.4530Dropped Classes 0.0644 0.0028 22.74 0 0.1496Major Change 0.0854 0.0051 16.89 0 0.1073

Page 50: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Regression Analysis – Time to degree (Experiences)

  Coef. Std. Err. t P>|t| Beta140+ Credit Program 0.8392 0.0300 27.96 0 0.1792STEM 0.1062 0.0134 7.9 0 0.0736Coop / Internship 0.2517 0.0077 32.83 0 0.1968Study Abroad 0.1067 0.0128 8.35 0 0.0507Learning Community 0.0187 0.0091 2.04 0.041 0.0129Minor 0.0698 0.0096 7.29 0 0.0428Double Degree 0.4686 0.0261 17.97 0 0.1033Double Major 0.1432 0.0132 10.83 0 0.0637

Page 51: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Regression Analysis – Time to degree (College Choice)

  Coef. Std. Err. t P>|t| BetaLiberal Arts & Sciences

Held Out

Ag & Life Sciences -0.0357 0.0167 -2.14 0.033 -0.0153Design 0.1199 0.0169 7.08 0 0.0508Engineering 0.2421 0.0145 16.73 0 0.1505Human Sciences -0.1118 0.0171 -6.55 0 -0.0428Business 0.0291 0.0153 1.9 0.057 0.0129

Page 52: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Regression Analysis – Time to degree (Financial)

  Coef. Std. Err. t P>|t| BetaDebt at graduation 0.0000 0.0000 14.63 0 0.0943Financial Need 0.0000 0.0000 -5.13 0 -0.0444Pell Elig 0.0525 0.0149 3.53 0 0.0291Award Program G -0.0246 0.0375 -0.66 0.512 -0.0053Award Program M 0.0045 0.0380 0.12 0.905 0.0009Strategic Award -0.0271 0.0121 -2.24 0.025 -0.0183

Page 53: Enrollment Research Team AACRAO-SEM Nov. 2013 Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013 Dissecting the End: Factors that Explain Differences in

Enrollment Research Team

AACRAO-SEM

Nov. 2013Chicago Compton, Forbes, Ralston, Wohlgemuth, 2013

Regression Analysis – Time to degree (Demographics)

  Coef. P>|t|Female -0.1646 0Minority 0.0316 0.23Nonresident -0.0232 0.04International -0.0652 0.44Constant 3.9672

What does this mean for a Domestic Female Non-minority student from Out of State?

𝑇𝑖𝑚𝑒𝑡𝑜𝐷𝑒𝑔𝑟𝑒𝑒=𝐶𝑜𝑛𝑠𝑡𝑎𝑛𝑡+ (−0.1646 )𝐹𝑒𝑚𝑎𝑙𝑒+ (0.0316 ) 𝑀𝑖𝑛𝑜𝑟𝑖𝑡𝑦+ (−0.0232 ) 𝑁𝑜𝑛𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡+(−0.0652 ) 𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑡𝑖𝑜𝑛𝑎𝑙=3.9672+(−0.1646∗1 )+ (0.0316∗0 )+(−0.0232∗1 )+(−0.0652∗0 )=3.7794𝑅2=0.482