Policy Impact Analysis - 117/S/3952

Bill Overview

Title: Student Right to Know Before You Go Act of 2022

Description: 2022 This bill requires the National Center for Education Statistics to establish and maintain a new higher education data system. The center must use the system to calculate metrics related to student education, debt, and earnings. These metrics include student graduation rates, transfer rates, rates of continuation to subsequent levels of education, dropout rates, loan debt amounts, loan repayment rates, and debt-to-earnings ratios for each institution of higher education (IHE) that participates in federal student-aid programs. The metrics must be disaggregated and separately provided on the basis of specified categories. The system must meet requirements for minimizing privacy and security risks. The bill provides for the transition from the existing Integrated Postsecondary Education Data System to the new higher education data system. The Department of Education must publish the metrics on its website. Within five years, an IHE that participates in federal student-aid programs must display links on its website to these metrics.

Sponsors: Sen. Wyden, Ron [D-OR]

Target Audience

Population: Postsecondary students globally in institutions participating in federal student-aid programs

Estimated Size: 18000000

Reasoning

Simulated Interviews

High school senior (New York, NY)

Age: 18 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 15/20

Statement of Opinion:

  • Knowing graduation and debt statistics helps me pick a college that won't leave me with huge debt.
  • I wish this information was available sooner.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 8 7
Year 3 8 7
Year 5 8 7
Year 10 9 8
Year 20 9 8

Community college student (Los Angeles, CA)

Age: 19 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 12/20

Statement of Opinion:

  • It's great to have access to information about earnings after graduation so I can pick the right major.
  • I hope the data is easy to understand.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 6 5
Year 3 6 5
Year 5 7 5
Year 10 7 6
Year 20 8 7

University student (Chicago, IL)

Age: 21 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 18/20

Statement of Opinion:

  • The debt-to-earnings ratio will help me plan my career better and choose internships.
  • I’m skeptical about the accuracy of the data initially.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 7 6
Year 3 7 6
Year 5 7 7
Year 10 8 7
Year 20 8 8

Graduate student (Dallas, TX)

Age: 24 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 4.0 years

Commonness: 10/20

Statement of Opinion:

  • Access to employment outcomes of graduates helps me prepare for the job market after my PhD.
  • It's important to have this detailed view available for my field.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 8 7
Year 3 8 7
Year 5 8 8
Year 10 9 8
Year 20 9 9

Higher education policy researcher (Seattle, WA)

Age: 30 | Gender: other

Wellbeing Before Policy: 8

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • This policy provides a data trove for analyzing education inequalities and outcomes.
  • I'm excited about the potential for improving education access and quality.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 9 8
Year 5 9 8
Year 10 9 9
Year 20 9 9

College dropout (Phoenix, AZ)

Age: 22 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 6.0 years

Commonness: 8/20

Statement of Opinion:

  • Knowing more about debt and earnings might help me choose whether to go back to school.
  • I hope this will lower the dropout rates.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 5
Year 2 6 5
Year 3 6 5
Year 5 6 5
Year 10 7 6
Year 20 7 6

Software engineer (San Francisco, CA)

Age: 27 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 3.0 years

Commonness: 15/20

Statement of Opinion:

  • This information might have prevented me from taking larger loans than necessary.
  • It's valuable for future students.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 8 7
Year 5 8 7
Year 10 8 8
Year 20 8 8

Parent (Miami, FL)

Age: 35 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 2.0 years

Commonness: 14/20

Statement of Opinion:

  • This data is crucial for helping my child make a better choice about college.
  • There should be more focus on student experiences too.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 6 6
Year 3 7 6
Year 5 7 6
Year 10 7 7
Year 20 7 7

High school counselor (Boston, MA)

Age: 45 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 10.0 years

Commonness: 20/20

Statement of Opinion:

  • Having detailed data from this policy is a game changer for counseling students on their future.
  • I hope the implementation goes smoothly.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 9 8
Year 3 9 8
Year 5 9 8
Year 10 9 9
Year 20 9 9

Education policy maker (Washington, DC)

Age: 60 | Gender: other

Wellbeing Before Policy: 9

Duration of Impact: 10.0 years

Commonness: 4/20

Statement of Opinion:

  • This data system is vital for making informed policy decisions.
  • It's about time we had access to such crucial data.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 9 9
Year 2 9 9
Year 3 9 9
Year 5 9 9
Year 10 9 9
Year 20 9 9

Cost Estimates

Year 1: $80000000 (Low: $60000000, High: $100000000)

Year 2: $70000000 (Low: $50000000, High: $90000000)

Year 3: $60000000 (Low: $40000000, High: $80000000)

Year 5: $50000000 (Low: $30000000, High: $70000000)

Year 10: $30000000 (Low: $20000000, High: $50000000)

Year 100: $10000000 (Low: $5000000, High: $20000000)

Key Considerations