1 1 sheeo policy conference august 9, 2012 @hcmstrat sandy baum, david wright, lee holcombe, kim...

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SHEEO Policy ConferenceAugust 9, 2012

@HCMStrat

Sandy Baum, David Wright, Lee Holcombe, Kim Hunter-

Reed

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Project background

Started in 2011 by HCM Strategists, with support from the Bill & Melinda Gates Foundation

Brought together researchers with different perspectives on higher education measurement

Asked research participants to think like policymakers and leaders

Asked policymakers and leaders to consider and respond to research

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Key questions

How should we account for different student populations when evaluating higher education outcomes?

What methods are available or in use for policymakers and leaders to account for variations in inputs?What are the best ways to do it and what are the practical limitations?Can research findings be translated into policy?

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Project components

Seven white papers Synopsis paper Literature review

Coming soon . . . Policy briefs Toolkit for states Outreach--sharing findings, including more voices, continuing to solicit input

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Some general lessons and conclusions Input adjustments make a big difference Policymakers should make an effort to adjust for inputs when institutional comparisons have stakes attached

Imperfect input adjustments are better than none

Need to be clear about outcomes

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Readers will find specific guidance on Important variables to include Examples of adjustment models and statistical techniques

Use of survey for input adjustments College learning assessments Strategies for working with messy administrative data

Strengths and weaknesses of U.S. News input adjustments

Many potential unintended consequences

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Where to find out more . . .

Context for Success website:

www.hcmstrategists.com/contextforsuccess

Questions? Comments?

http://www.hcmstrategists.com/contextforsuccess

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Advice for Moving Forward

Know the purpose, audience and questions to be answered

Consumers: Judging quality and value

Institutions: Improving

Accountability: Success and cost-effectiveness

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Advice for Moving Forward

Comparing outcomes: Focus on similar institutions

Differences in credentials Goals of students Role of transfer

Selecting variables Preparation Demographics Attitudes, goals, behaviors

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Context for Success White PapersCharles Clotfelter. "'Context for Success' Synopsis Paper."

Thomas Bailey and Di Xu. "Literature Review: Input Adjusted Graduation Rates and College Accountability."

Peter Riley Bahr. "Classifying Community Colleges Based on Students' Patterns of Usage."

Thomas Bailey. "Developing Input Adjusted Measures of Community College Performance."

Jesse M. Cunha and Darwin W. Miller. "Measuring Value-Added in Higher Education."

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Context for Success White Papers (cont.)Robert Kelchen and Douglas N. Harris. "Can 'Value Added' Methods Improve the Measurement of College Performance?"

Stephen M. Porter. "Using Student Learning as a Measure of Quality in Higher Education."

John Pryor and Sylvia Hurtado. "Using CIRP Student Level Data to Study Input Adjusted Degree Attainment."

David Wright, Matthew Murray, Bill Fox, Celeste Carruthers, Grant Thrall. "College Participation, Persistence, Graduation, and Labor Market Outcomes."

An Input-Adjusted Framework for Assessing the Effectiveness of Tennessee’s

Higher Education Institutions

Context for Success project

Celeste Carruthers,a William Fox,a Matthew Murray,a Grant Thrall,b

David L Wrightc

a University of Tennessee, Knoxville; b University of Florida; c Tennessee Higher Education Commission

Background

• Policy relevance:

– Complete College TN Act ties HEI funding to student outcomes.

• Assumption:

– Funding incentives must take into account student characteristics that are likely to be important determinants of postsecondary outcomes.

SHEEO, 08-09-2012Context for Success paper

Research questions

• Purposes:

1) We statistically test whether some TN institutions were more effective than others at advancing the outcomes of 2002 entering first-time freshmen.


Research questions

• Purposes:

2) We go on to test whether accounting for student inputs (ACT aptitude, age, low-income home neighborhood, LifeMode marketing profile) changes the ranking of institutions.

— Is model fit improved by supplementing or substituting our standard stock of administrative data with proprietary data on consumer tapestry profiles (called LifeModes) or with Census information?


Method

• Cohort: 2002 first-time freshmen in TN public universities and community colleges

• Design:

– Multivariate OLS regression

– Used fixed effects to isolate institutional effectiveness


Method• Compared models with four different sets of

predictor variables: 1) naïve model2) standard state agency administrative data3) Census neighborhood data4) proprietary LifeModes profiles

• Outcomes considered: student progression, transfer, graduation, and near-term labor market success


Selected findings

• Timely completion:

– Females, higher entrance exam scores, and adult status were associated with more timely degree completion.

– Low-income status delayed completion.

– Additional semesters in college reduced earnings later on.


Selected findings

• Earnings:

– Females and higher entrance exam score were associated with higher earnings in the years immediately following college.

– A significant black-white earnings gap favored white students.


Six-year graduation rates (bachelor’s) across 4-year schools, relative to one omitted institution, unadjusted (blue) or adjusted for student and home characteristics

4-Year Institution


Four-year graduation rates (associate’s) across 2-year schools, relative to one omitted institution, unadjusted (blue) or adjusted for student and home characteristics

2-Year Institution


Observations and open questions• Institutions do matter: even after controlling

for all observed student inputs, some institutions are significantly more effective than others.– Also see Cunha and Miller in this series.

• Student inputs also matter: institutions’ apparent effectiveness changes when we account for student aptitude and background.

• The gains from more data are not always high.


• Why are some institutions more effective than others? Institutional effects are a black box.

• Student goals and objectives may not align with traditionally tracked student outcomes.– Especially in community colleges!

• Assessing and comparing student growth across fields and campuses is challenging but not insurmountable.


Observations and open questions

• Outcomes and institutional best practices should be included in performance-based funding. (p.6)

• Incentivizing colleges for student progression and completion relative to expectations is an improvement over unadjusted rewards…

• … but, be aware that outcomes will vary according to which students inputs are factored into expectations for colleges and universities. (p.32)


Conclusions

A Project of the Texas Higher Education Coordinating Board

Input Adjusted Output Measures

Presented By: Lee Holcombe, Director, Higher Education Policy Institute

Analysis: Jesse Cunha, of the Naval Postgraduate School and Trey Miller of the RAND Corporation

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Goals

Develop and implement a methodology that generates quantitative metrics of institutional performance.

Come as close as possible to causal estimates of an institution’s impact on a particular outcome.

Demonstrate benefits of collecting additional data.

Develop a set of concrete and actionable policy recommendations for practitioners and policymakers.

Higher Education Policy Institute

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Outcomes

Persistence into 2nd year of college: Attain 30 credit hours at any public or private

four-year college in Texas by the end of the 6th academic year after graduating high school

Graduation: Receive a Bachelor’s degree at any public or

private four-year college in Texas by the end of the 6th academic year after graduating high school

Earnings: Sum of 4 quarterly earnings in the 8th calendar

year after high school graduation.


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Data

Higher education Demographic variables, application and

acceptance data, credits attempted, degree completion

K12 (Secondary) Demographic variables, test scores, courses taken

Unemployment Insurance earnings

From College Board: SAT scores and survey info


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Sample

Graduates of Texas public high schools in 5 cohorts (1998-2002)

Include those Texas public high school graduates who ever enrolled in a Texas public university (up to 2010).

217,723 enrollees, 169,239 of whom had earnings greater than $2,000


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Findings

Large differences in unconditional outcomes across colleges diminish as each set of controls is added to the model.

Adding high school indicators and courses changes results much more than adding race and gender.

Different results across outcomes.

Measures are highly variable over time.


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Policy Recommendations of Report

Assessment of institutional quality should involve a broad set of outcomes representing multiple dimensions of institutional performance.

Researchers should work with state policymakers to develop models that reflect state priorities.

Do not assume that results are causal.

Create broad classifications of institutional performance as opposed to explicit rankings.


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Policy Response

Elusive quest for causality.

Excludes many non-traditional students.

Consider improvements within-institution

Dig inside the higher education black box.

Provide higher levels of information and support.

Use of more nimble data systems.

Consider learning outcomes.


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Where to find out more . . .

COMING SOON

Context for Success website:

www.hcmstrategists.com/contextforsuccess

Questions? Comments?

1 1 sheeo policy conference august 9, 2012 @hcmstrat sandy baum, david wright, lee holcombe, kim...

Documents

research slide

costeffectiveness slide

news input adjustments

imperfect input adjustments

conclusions input adjustments

inputadjusted framework

higher education outcomes

kim hunterreed slide