AI-Driven Insights from the Class of 2025 Senior Exit Survey

In late June 2025, I led my nonprofit organization, Student Echo, in a collaboration with Redmond High School to analyze responses from the Class of 2025 Senior Exit Survey. This annual survey, organized by the school’s College & Career Center, collects information on seniors’ post-graduation plans.

While the survey covers multiple areas, our focus was on one key free-response question:
“What additional support do you need before you graduate?”

The College & Career Center team had limited tools to process and interpret open-ended responses at scale. That’s where we came in. Using Student Echo’s AI tools, we analyzed the free-text answers and uncovered themes that could help the school offer more effective and timely support for graduating seniors.


Recommendations:

  • Maintain a master checklist of graduation tasks.
  • Schedule quick counselor check-ins with all seniors.
  • Offer transcript and scholarship submission workshops.
  • Watch for students who indicate confusion passively (“I think I’m good?”).
  • Continue mental health messaging and support for burnout or senioritis.

These recommendations aim to make senior-year support more targeted, equitable, and proactive. We were especially excited to hear that the College & Career Center plans to share our findings with the Counseling Department Chair to explore ways to improve their processes based on our analysis.

The full report is available below.

— Andrew

Using LLMs to Hear What Students Are Really Saying

Earlier this year, I had the opportunity to lead my nonprofit, Student Echo (student-echo.org), in a collaboration with the Lake Washington School District to analyze student survey data using Large Language Models (LLMs).

With support from Dr. Tim Krieger (Director of Data and Research) and my high school principal, Ms. VanderVeer, we focused on extracting insights from open-ended responses—comments that often get overlooked because they’re hard to analyze at scale.

Our goal was simple: use LLMs to help educators better understand what students are actually saying—what they care about, where they’re struggling, and what they wish could be different.

The analysis has since been shared with district educators to help inform future improvements in the student experience. I’m excited to share the full report below, which walks through the methods, findings, and a few key takeaways from the project.

Stay tuned—more student voices coming soon.

— Andrew

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