Using Data to Inform the National Dialogue on Education and the Economy

Center on Education and the Workforce

Using Data to Inform the National Dialogue on

Education and the Economy

Presentation by Nicole Smith

at the 2009 SHEEO/NCES NETWORK CONFERENCE AND IPEDS

WORKSHOP

May 22, 2009


H.R.1: 69-70

“For an additional amount for “Institute of Education Sciences” to carry out section 208 of the Education and Technical Assistance Act, $250m, which may be used for Statewide data systems that include postsecondary and workforce information, of which up to $5m, may be used for State data coordination and for awards to public or private organizations or agencies to improve data coordination”

American Recovery and Reinvestment Act of 2009


Summary Slide

Stimulus package provides funding for states to improve data coordination:

•K-12•Post-secondary•Workforce

This document presents a list of suggestions from a data-user and policy-making perspective for current data collection mechanisms to better connect education and employment systems


Individual level longitudinal data connecting K-12 to postsecondary attainment to workforce outcomes

•Data: {curricula, transcripts, SES, demographics, wages}

Licenses, certifications and employability by state

Information on transferability of licenses and certifications across state

Education supply. Stock of highest education level achieved

Vision


Data that weakly connects post-secondary Curricula to Employability

CIP-SOC crosswalk facilitates transitive links to:• CPS (socioeconomic characteristics of workers with CIP courses by SOC code)*

• NAICS (industries that typically hire workers by CIP code)

• O*NET (KSAs of occupation and CIP courses required by occupation)

*Usual way to connect socioeconomic characteristics of post-secondary Americans is through on Pell Grant Information.

Shortcomings:

Some CIPs and SOCs remain unmatched Information on differential enrollment by race and income, not SES

What we have


Data that better connects Secondary/Post-secondary education to Student

Characteristics

SES (socioeconomic status) of the student body

•Information by race and income level are currently available•Particularly relevant to affirmative action and college enrollment debate

What we would like

Data that better connects Secondary/Post-secondary education to

Student Characteristics

What we would like

Why?

Parental education, parental income, parental occupation for individual institutions, (since post-secondary institutions are highly selective by SES).

Need to provide access and choice throughout the income distribution, not just the upper tail. Center on Education and the Workforce

Data that better connects Secondary/Post-secondary education to employment outcomes

Connect graduates from all institutions (selective and proprietary) to wages

CIP/wages Transcript/wages Major/wages Are students working in their major?

Possible Vehicle?National Student Clearing House Improved


What we would like

Data that better connects Secondary/Post-secondary education to employment outcomes

Why? Information at the transcript level would allow us to

estimate the market value added per course. (Florida). Examine the value of “course clusters.”

Are students working in their major?

Information by major allows permits research into the transferability of skill and job market*value* of credentials.

A lot of evidence exists to show people working in major are likely to earn higher wages


What we would like


Data that connects Occupational and State Licensing Requirements to Employability

No known data system connects licenses and certifications to SOC. No known national data system/repository of state licensing requirements by SOC. Essential for market access to some occupations.

Why?Licenses for technical occupations differ across state. Can provide information on portability and flexibility of licenses across state.

What we would like


Data that better connects Curricula and Employability

Lessons from European tuning system•Non market-based strategy designed to understand curricula and to make them comparable.

Lumina Foundation has launched faculty-led process that links college degrees to workplace relevance and students’ mastery of agreed-upon learning objectives.

•Focused in scope by state and subject.

What we would like


Data that better connects Curricula and Employability

Lessons from European tuning system

Why?

Cohesive examination of knowledge, skills and ability requirements by curricula. Opportunity for collaboration across states in defining learning outcomes and employability.

What we would like


Data that better connects Training to Employability

We have O*NET•But it is cross-sectional and tells us nothing about how training requirements have changed over time•Problems of uniformity of O*Net categories within and across questions•Problems with statistical reliability of incumbent responses

Data that facilitates estimates of Education Supply

Not only degrees conferred, but for example total number of BAs where a BA is the highest education level of an individual. As it stands, using NCES data is subject to double counting.

What we would like


Avoid

Focus on the bottom. Instead, focus on the full distribution

E.g. NCLB which focused data on failed schools and failed students.

We should track annual yearly progress for all students.

Decisions on measurement questions should be taken away from the political vagaries of Congress and given to a nonpartisan independent technical advisory Board which understands data.


Adequate funding at the Federal and State level

Inclusion of a certificate question in national databases (ACS, CPS). We have a question in SIPP and NHES data, but not available annually.

Inclusion of a certification question in national data (ACS, CPS)

Collect wage information of 2 year and 4 year college graduates

How do we get there?

Using Data to Inform the National Dialogue on Education and the Economy

Documents

Transcript of Using Data to Inform the National Dialogue on Education and the Economy