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Good practice Imported

OtterBot — Washington State's AI-Assisted FAFSA and Financial-Aid Navigation Chatbot for Low-Income Seniors

United States of America · Olympia · See the United States of America profile

Evidence: Observational / pre–post Top 73% 40/100 · Ask Evidence Copilot about this practice

Washington's state financial-aid agency runs a two-way AI texting chatbot that nudges low-income high-school seniors through FAFSA and College Bound Scholarship steps; among students who asked 5+ questions, over 86% graduated high school and over 60% completed the FAFSA in the fi

~10,000
College Bound Scholarship seniors who interacted with OtterBot (first year) (2019–2020)
86%+
Graduated high school (among students who asked 5+ questions)
60%+
Completed the FAFSA (among students who asked 5+ questions)
100+ languages
Languages supported
OtterBot — Washington State's AI-Assisted FAFSA and Financial-Aid Navigation Chatbot for Low-Income Seniors

Details

Maturity
Established
Promoter
Washington Student Achievement Council (WSAC)
Period
2019–2021
Keywords
financial aid, FAFSA guidance, chatbot, government agency, low-income students

Context

OtterBot is a two-way, AI-informed text-messaging chatbot built by the Washington Student Achievement Council (WSAC), the state's higher-education financial-aid and outreach agency. Launched in 2019, it messages Washington high-school seniors enrolled in the state's College Bound Scholarship — a tuition-support promise for eligible low-income students — in more than 100 languages, with a human advisor stepping in whenever the bot cannot resolve a question.

Objectives

The tool aims to nudge low-income, first-generation-leaning seniors through each step of the FAFSA and financial-aid application process, reducing drop-off among the students least likely to have a family member who has navigated college financial aid before.

Activities

Roughly 10,000 College Bound Scholarship seniors interacted with OtterBot in the programme's first year, receiving stepwise prompts and reminders through the FAFSA process, with escalation to a human advisor when needed.

Results

Among students who asked the bot five or more questions, over 86% went on to graduate high school and over 60% completed the FAFSA — outcomes the Harvard Advanced Leadership Initiative's review of the programme highlights as showing the students most in need of support engaging most deeply with the tool.

Conclusions

The evidence is observational rather than causal: WSAC and the Harvard review both note that more-engaged students may simply have been more motivated to begin with, and no control group of similarly eligible non-users was tracked. WSAC continued running OtterBot through subsequent senior classes, but this submission verifies only the first-cohort figures against independent sources.

Implementation
Indicative cost
Low (< €50k)
Time to results
Medium (1–3 years)
Staffing & skills
Washington Student Achievement Council (WSAC) chatbot/product team, Human advisors who step in when the bot cannot resolve a query

Conditions for success

  • Existing College Bound Scholarship enrolment list to identify and target eligible seniors
  • Multilingual text-messaging infrastructure (100+ languages)
  • Human-in-the-loop escalation pathway for unresolved questions

Common failure modes

  • Correlational engagement-outcome link — more-motivated students may self-select into higher engagement
  • No control group of similarly eligible non-users was tracked

Commonly funded by

National / regional programmes

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Data sources

Where this practice's information was retrieved from, and when.

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