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Report Utah Opportunity Chain · Part 9 of 9 Mobility

The Utah Opportunity Chain: A Pathway Comparison

Capstone comparison across inputs, throughput, outputs, and mobility using metrics from the full series.

Key finding

No single Utah pathway wins on every column in the capstone table — USHE technical colleges sacrifice earnings ceiling for low cost and high completion; USHE four-year institutions lead public earnings medians ($46K) at higher net price and debt. Concurrent enrollment (Part 1) and apprenticeship (Part 6) sit outside Scorecard rows.

No single Utah pathway wins on every metric. USHE technical colleges combine low net price and high completion; USHE four-year institutions lead public earnings medians; apprenticeship trains thousands outside Scorecard. This capstone places pathway medians from Parts 1–8 on one comparison frame — a tradeoff matrix, not a leaderboard.

The assumption we tested
Assumption
One best postsecondary pathway exists for Utah students.
Question
When cost, completion, earnings, and debt are compared side by side, what tradeoffs emerge across pathway types?
Evidence
Synthesis of College Scorecard pathway medians · 63 Utah institutions · Parts 1–8 sources
Finding
The evidence suggests each pathway sacrifices something others provide: USHE technical ($3K net price, 79.0% completion); USHE four-year leads earnings ($46K); apprenticeship remains a parallel earn-while-you-learn track (Part 6).
Limits
Pathway medians, not prescriptions; datasets are not linked at the student level; no causal ranking.
The analytical lens
  • This capstone is a tradeoff matrix — net price, completion, six-year earnings, and median debt by pathway type. No single row wins every column.
  • Concurrent enrollment (Part 1) and apprenticeship (Part 6) shape who enters which pathway but sit outside Scorecard rows.
  • Supplemental briefs add field-level ROI, USHE spending, graduates-per-job alignment, and stopout scale. Strada's statewide positive-ROI share (65.0% Utah vs. 70.0% U.S.) adds a financial-return dimension beyond the Scorecard medians in the capstone table.
At a glance
  1. No single pathway wins on every metric. USHE technical colleges remain a high-completion, low-cost subset within broader certificate/technical providers (Part 2); USHE four-year schools lead on early earnings medians among public options.
  2. K–12 preparation varies by district (+0.02 statewide vs. national on SEDA); concurrent enrollment remains the largest postsecondary attainment gap (Parts 1 and 9).
  3. Private and for-profit medians are included for comparison. Sector labels are not destiny; institution and program matter.
  4. USHE R5 reports the widest attainment gap among input pathways between CE participants and non-participants (Part 1); apprenticeship now has sponsor, DWS, and federal participant throughput data (Part 6) but still lacks Scorecard earnings comparables.

This capstone synthesizes Parts 1–8 using one comparison frame across all 63 Utah institutions in the College Scorecard subset. We do not prescribe a single “best” pathway. Families, counselors, and policymakers need different weights on cost, completion, earnings, and mobility.

Where this fits

Part 9 places pathway medians from Parts 1–8 in one table — net price, completion, six-year earnings, and median debt for each major pathway type. No single row leads on every column; the whitepaper walks through the same numbers with sector-by-sector interpretation.

Unified pathway comparison

PathwayNet price (low inc.)CompletionEarn. 6 yrMedian debt
USHE four-year $10K 52.7% $46K $9K
USHE community $7K 45.8% $38K $4K
Certificate & technical (all) $17K 83.8% $25K N/A
USHE technical (subset) $3K 79.0% $38K N/A
Concurrent enrollment bridge N/A 77.0% N/A N/A
Private nonprofit $12K 46.2% $53K $8K
For-profit $19K 49.7% $25K $8K
Apprenticeship N/A N/A N/A N/A

The apprenticeship row shows N/A because College Scorecard does not track earn-while-you-learn pathways. Throughput evidence instead: 326 active sponsors, 4,731 active apprentices (DWS 2024), 51,243 federal participant records (DOL 10264). See Part 6.

How to use this report

Start with your constraint: cost-sensitive → Parts 5 and certificate/technical rows; completion risk → Parts 1 and 7; earnings floor → Part 3; debt ceiling → Part 8. For the full narrative, see the whitepaper.

What stood out
  • No pathway row in the capstone table leads on net price, completion, earnings, and debt simultaneously.
  • Education produces the steepest graduate-to-job ratio in our alignment brief (194 per 1,000 mapped jobs) — a labor-market dimension Scorecard medians do not capture.
  • Strada rates Utah Advanced on employer alignment while trailing the U.S. positive-ROI share — coordination and financial return are different capstone questions.

Key takeaway: Read the capstone table as a tradeoff matrix, then use supplemental briefs for program pay, USHE spending, workforce alignment, and stopout scale.

Technical note: Synthesis of Parts 1–8 pathway medians plus links to field-level briefs. No student-level linkage across datasets.

Mobility: stopouts and re-engagement

National Student Clearinghouse reports 432,319 Utah adults in the “some college, no credential” population (2025 SCNC report, all ages). The under-65 count grew by 13,894 (3.8% year over year). Re-enrollment and stacked-credential pathways are the mobility hinge between Parts 1 and 7; this edition uses public NSC and Census tables rather than state longitudinal microdata.

Future research

We have drafted a UDRC dataset request for aggregate stopout→completion tables. That work would extend this capstone; it is not required to interpret the public data in Parts 1–8. See the stopout brief.

What this means

Read the capstone table as a tradeoff matrix. USHE technical colleges sacrifice earnings ceiling for low cost and high completion; USHE four-year institutions lead public earnings medians at higher net price and debt; for-profit and certificate aggregates blend providers with sharply different outcomes (Part 2). Concurrent enrollment (Part 1) and apprenticeship (Part 6) sit outside Scorecard rows but shape who enters which pathway.

What this means for you

Find yourself below. Each bullet turns this report's evidence into a practical next step — not a prescription.

  • Students Pick your main constraint — cost, finishing, pay, or debt — then read the matching part in this series.
  • Families Start with your student's constraint: cost-sensitive → Parts 5 and certificate rows; completion risk → Parts 1 and 7; earnings floor → Part 3; debt ceiling → Part 8.
  • School counselors Use this capstone table as a handout index — each column points to a dedicated brief with institution-level detail.
  • Policymakers Sector labels are not destiny; the supplemental briefs on program ROI, USHE spend, credential–labor alignment, and stopout add field-level and mobility context beyond these medians.

Supplemental briefs: Program ROI · USHE spend vs. outcomes · Credential–labor alignment · Stopout & re-engagement

Read next
  • Part 5 — Net price spread in the capstone table (USHE technical $3K vs for-profit $19K).
  • Part 1 — R5 concurrent enrollment attainment (77.0% with CE vs 34.0% without), the input metric absent from Scorecard rows.
  • Whitepaper — Pathway-by-pathway synthesis using the same numbers as the capstone table.
Sources & methodology
  • Synthesis of College Scorecard Utah subset
  • Stanford SEDA 2025.1 (K–12 district achievement)
  • USHE R5 concurrent enrollment narrative
  • Apprenticeship.gov + DOL dataset 10264 + Utah DWS (Part 6)
  • NSC SCNC state appendix
  • Series Parts 1–8 sources

Full methodology

Cite this research

Pathways & Outcomes original analysis; cite the report and link to the primary URL. Data vintage: College Scorecard Utah subset · see part sources.

APA: Pathways and Outcomes. (2026). The Utah Opportunity Chain: A Pathway Comparison. https://pathwaysandoutcomes.org/utah/research/utah-opportunity-chain-report/

Methodology · Republishing policy

How this was produced

Pathways & Outcomes uses AI tools to help draft reports and data briefs from verified public data and analysis. A human editor reviews every publication for accuracy, data consistency, clarity, methodology alignment, and discrepancies before release. AI does not determine what we investigate, what we publish, or what conclusions we reach. Editorial policy · About our team