Fall 2025 - Spring 2026
How can we help Fortyx80...
...collect relevant data for LAUNCH...
...to track engagement during the program?
...to gather relevant metrics for grant application?
...to track outcomes from alumni after the program?
...effectively store and organize data?
Gryphon Chong
Lily Kim, Tiffany Liu, Abigail Lo, Shreya Mahindroo, Maddy Ng, Mahee Shah, Nandini Tiwari, Sissi Zhen
Fortyx80
The Problem Space we focused on was data: tracking the relevant metrics needed to measure impact for grants.
More specifically, we looked at how we can help Fortyx80 to:
collect relevant data for LAUNCH to
track engagement during the program,
gather relevant metrics for grant application,
And track outcomes from alumni after the program;
And additionally, how we can help them to:
effectively store and organize data.
Fortyx80 is a non-profit branch of the Pittsburgh Tech Council for K-12 students
Main programs are LAUNCH and STEM Summit/TRETC
Helps connect high school students to local tech opportunities, encouraging them to pursue STEM
Summer STEM Program/Workshop targeted for rising juniors and seniors in high school
Students get industry tours, mentorship, career exploration, and more resources, and work on a project to accumulate them into STEM
Students are paid a small amount to attend; ~20 people per cohort
Goal: Introduce and inspire students to explore STEM Careers
We reached out to Fortyx80 and asked to access their current data, then examined their current surveys, testimonials, and applications. We found that they measure self-confidence, inspiration, and other qualitative personal growth as outcomes, which helped us build an initial list of metrics to track.
We spoke with other education outreach-based organizations including Chester Country Futures, Create Lab, LEAP Center for Architecture Explorations, and CMU College of Engineering. Through emails and interviews, we gathered information about their methods of measuring program impact.
We found that while these programs relied on regular communication and surveys, similar to Fortyx80, they leveraged the power to require responses in these surveys to gather more data. Additionally, some organizations used a logic model to guide their tracking.
Using an Affinity Diagram, we organized the information that we got from the expert interview and then labelled the responses to each question based on similarity, resulting in six main categories. From this process, we found that the biggest areas where TEP wanted to make a change included their marketing strategy, improving their website and search engine optimization, and meeting needs that they are currently unable to reach.
After conducting the comparative analysis, we developed a logic model which helped us ground the exact goals we wanted to achieve.
Inputs → Activities → Outputs → Outcomes
This model followed the order of inputs, activities, outputs, and outcomes:
Inputs: who and what goes into the program. This includes stakeholders like students, mentors, and alumni.
Activities: the actual things happening within LAUNCH, such as mentorship sessions and workshops.
Outputs: the immediate, measurable results. For example, the survey responses collected.
Outcomes: the long-term impacts. This includes things like interest in STEM.
This model helped us clearly define LAUNCH’s goals and success metrics, and it gave us a strong foundation as we moved into building our solution.
We began the ideation process by using the Crazy-8s method, where each team member rapidly generated at least 8 ideas in 8 minutes. Then, we grouped all similar ideas and considered the feasibility of each group: providing incentives to alumni for feedback, focus groups, and tracking alumni engagement.
These ideas were then evaluated using an Impact-Effort Matrix, which allowed us to visualize each solution and prioritize solutions that would provide the highest value while remaining the most feasible. The strongest ideas involved data collection through surveys given to students, mentors, and alumni.
We finalized 5 different ideas after our ideation stage: mentor surveys, one-time surveys, frequent surveys, alumni outreach, and data centralization.
Since mentors regularly met with their mentees, these mentor surveys were meant to provide feedback on LAUNCH participants, specifically on student growth and engagement.
One-time surveys were in the form of pre- and post- surveys; students would answer a short survey when they first join LAUNCH, and then complete a similar survey at the end of LAUNCH. This would measure overall growth and interest in STEM.
Frequent surveys would be given out to students after each session, which allows for detailed, real-time tracking of engagement and learning for all participants throughout the program.
Alumni outreach would focus on keeping alumni involved by sending them emails to ask about their current plans. This also measures long-term outcomes related to education and careers.
Data centralization would involve combining all of Fortyx80’s data into one centralized system in Google Drive so that all important metrics are easy to access and analyze, especially for grant applications.
We met with The Education Partnership staff to determine what categories would best work with their workflow. We ended up basing our flowchart off some internal documents that they were able to provide us.
After developing initial prototypes, we conducted user testing in two phases: first with Grace and Rafalene, and then with LAUNCH alumni and mentors for broader feedback.
We used interviews conducted via Zoom and email to understand user experiences and evaluate the clarity and effectiveness of our surveys.
Feedback indicated a need for more open-ended text boxes to allow participants to give more thoughts and more detailed responses.
Users also suggested adding more specific, tech-related fields and emphasized the importance of tracking portfolio skills as part of participant growth.
We learned that yearly follow-up emails to alumni are not feasible, and that a one-time survey is more practical. Additionally, users found the survey completion time to be appropriately short.
Our final solution for LAUNCH consists of pre-program and post-program surveys that students are able to complete at the start and end of the internship program. The surveys assess for soft skills along with previous STEM exposure and opportunities. For example, some of the questions assess confidence networking, career plans, and exposure to other STEM industries.
Students complete a short survey at the start and end of the LAUNCH program.
Student-by-Student
Compares pre-program to post-program skills confidence levels to measure growth
Brings out the relevant qualitative responses (e.g. ‘How did LAUNCH influence you?’)
Program Summary
Provides summary statistics and percentages in confidence and interest in STEM
Most relevant towards grant reports and similar documents that need overarching data
Ask mentors how LAUNCH is impacting students from their perspective
Questions on mentee interest & development asked after every meeting
Tracking outcomes, particularly outcomes into STEM careers
Different surveys for alumni who are in college versus in industry
Updatable for new cohorts
The data collected from these surveys is then fed into a results dashboard in Google Sheets that makes the insights easy to read and analyze. The dashboard can also be filtered by cohort year as well to track growth and engagement over multiple cohorts. Over multiple years, this data is especially useful for grant reports and similar documents requiring statistics of the program’s effectiveness.
We also created mentor and alumni surveys to gather additional insights about the students during and after LAUNCH. The mentor survey asks mentors how LAUNCH has shaped their mentee based on their perspective through questions about mentee interest in STEM and development after every meeting. The alumni survey is split into two different versions for both industry working professionals and higher education students, and tracks alumni outcomes, particularly of those who are pursuing STEM, and can be updated by cohort.
Some key learnings:
The process of refining solutions based on client feedback and user testing to ensure the final product is both user-friendly and meets the needs of the client.
How to apply human-centered design in real use cases and build long-lasting relationships with companies.