Girls code program Impact Report

Girls code program Impact Report

Building confidence, skills, and career momentum through hands-on learning.

Survey insights across Pre, Mid, and Post stages show measurable gains in coding skills, project completion, and interview traction—especially at Mid stage.

What this report does

  • Parse and aggregate Pre, Mid, Post survey responses
  • Quantify skills, projects, and confidence trends by stage
  • Surface representative testimonials for each stage
  • Highlight resume workshop outcomes (interviews)
  • Flag data gaps and sample-size caveats clearly
+7.8
Avg coding test increase (Pre 56.7 ➜ Mid 64.5)
67%
Built a web app by Mid (4/6)
+33
NPS at Mid stage (n=6)

Key Program Insights

Rapid Skills Growth

Average test scores rose +7.8 points from Pre to Mid.

Portfolio Development

67% of respondents built a web app by Mid (0% at Pre).

Resume Workshop Impact

At Mid, 100% attended; 50% explicitly reported more interviews.

Confidence Momentum

“Confident/Very confident” grew from 0% (Pre) to 33% (Mid).

Community & Belonging

Participants cite motivation, support, and friendships as key drivers of persistence (Mid).

Participant Experience

Positives

  • Mid“The program changed everything for me. I've never been this confident in my knowledge and intelligence.” — Rosura
  • Mid“It's been a place where I feel motivated and confident… I built friendships with girls that share my interests.” — Triana
  • Mid“This program has been a turning point for me… I never thought this could be a potential career path.” — Ying
  • Post“Thanks to the resume workshop, I landed my first tech job and have since received promotions.” — Rosura

Challenges

  • PreLow starting confidence (“coding seems complicated,” “full of difficult math,” “confusing”).
  • MidInconsistent attendance for some participants led to missed sessions and feeling overwhelmed (Pravalika).
  • MidDebugging remains a pain point; some still need frequent help (Ying).

Improvements in Confidence & Skills

Average Coding Test

Pre ➜ Mid
56.7 ➜ 64.5

Change: +7.8 points (n=6 ➜ 6)

Built a Web App

Pre ➜ Mid
0% ➜ 67%

0/6 to 4/6 respondents

Confidence Levels (Mid)

Distribution
Confident/Very confident33%
Somewhat confident50%
Not confident17%

Pre baseline: 0% confident, 80% not confident, 20% anxious/neutral.

Resume Workshop

Mid
100%

Attendance (6/6). 50% explicitly reported increased interview calls.

Net Promoter Score

Mid
+33

Promoters: 50% (9–10), Detractors: 16.7% (0–6), Passives: 33.3% (7–8). n=6

“The workshop gave me a real edge. Landed several interviews because of my new resume.” — Rosura Mid
“Absolutely devastating if it stops. It's a great program for girls like me and my friends.” — Ying Mid

Data caveats

  • No reliable NPS at Pre; sample too small/incomplete at Post (n=1).
  • Some responses contain blanks (“-”); metrics reflect only valid answers.
  • Post-program outcomes are based on a single respondent and should be treated as directional.

Opportunities to Improve

Scaffold Debugging Support

Add guided debugging clinics and “stuck” playbooks to reduce reliance on mentors (Mid pain point).

Flexible Pathways

Offer catch-up tracks and async modules to help learners who miss sessions maintain momentum (Mid).

Early Confidence Wins

Use low-barrier projects and myth-busting around “hard math” to uplift Pre confidence quickly.

Personalized Project Tracks

Align project difficulty with skills to help all learners ship a web app by Mid.

Alumni Mentorship Loop

Leverage Post alumni (e.g., Rosura) for mock interviews and career support.

Outcome Tracking

Improve Post follow-up rates to robustly measure jobs, promotions, and persistence.

Need to Know

How were metrics calculated?

We aggregated valid responses by stage (Pre, Mid, Post). Averages and percentages exclude blanks (“-”).

What is NPS here?

Net Promoter Score at Mid only: Promoters% − Detractors%. Result: +33 (n=6).

How representative is Post data?

Very limited. Only one Post respondent (Rosura). Treat job outcomes as illustrative, not definitive.

What counts as “built a web app”?

Participants self-reported shipping a functional web app (front-end and/or simple back-end). Four did so by Mid.

How are blanks handled?

Responses marked “-” are excluded from numeric aggregations and clearly noted in caveats.

Overall Summary

The program demonstrates meaningful impact by the Mid stage: higher test scores (+7.8), strong project completion (67% built a web app), universal resume workshop participation (100%), and a healthy learner sentiment (NPS +33). Confidence trends shift from predominantly “not confident” at Pre to one-third “confident/very confident” at Mid. Post-program outcomes are promising but under-sampled; strengthening follow-up will clarify long-term career gains.