Teacher Reference Guide - Examples of High-Quality Student Work
These completed examples demonstrate what thorough, thoughtful student work looks like for each template in Lesson 8. Use these to:
Important: These are composite examples based on typical high school student work. They represent "proficient" level (B/A- work), not perfection. Students should aim for this quality while bringing their own unique perspectives and interests.
11th grade student interested in healthcare careers, specifically nursing or health informatics
Top 3 Skills I'm Proud Of:
Skills I Want to Develop:
How I'll Address These Gaps: Take Computer Science Principles next year, complete Google Data Analytics certificate over summer, and join hackathons focused on healthcare challenges to practice creative problem-solving with real constraints.
12th grade student interested in data science and machine learning careers
Daily Responsibilities:
Types of Problems They Solve: Customer behavior prediction, fraud detection, recommendation systems, process optimization, risk assessment, personalization algorithms, forecasting, anomaly detection.
AI Tools Data Scientists Use:
What AI Enhances vs. What Humans Still Do: AI accelerates routine tasks like data cleaning, initial model selection, and code writing. But humans still define which problems to solve, interpret results in business context, ensure ethical use of data, communicate insights persuasively, and make strategic decisions about data usage. AI is a powerful assistant, not a replacement for human judgment.
Next 5-10 Years:
Tasks That Might Be Automated: Basic data cleaning, routine reporting, simple model selection, code debugging, creating standard visualizations.
New Responsibilities That Might Emerge: AI ethics auditing, model interpretability specialist, data storytelling, AI literacy training for business teams, privacy compliance expert, "AI translator" between technical and non-technical teams.
Traditional Path:
Alternative Paths:
Key Skills Needed:
AI Literacy Required: Deep understanding of machine learning concepts, ability to evaluate AI model performance, awareness of AI limitations and biases, staying current with new techniques and tools.
Salary Data (U.S., varies by location and industry):
Geographic Variation: Highest salaries in San Francisco Bay Area, Seattle, New York City, Boston. Remote positions increasingly common with competitive pay.
Benefits: Most roles include health insurance, retirement matching, flexible work arrangements, professional development budgets, and stock options at tech companies.
Sources: Bureau of Labor Statistics Occupational Outlook Handbook, Glassdoor salary data, LinkedIn salary insights
Bureau of Labor Statistics Projection (2023-2033): Data scientists fall under "Computer and Information Research Scientists" category with 26% growth rate - MUCH faster than average (7% for all occupations).
Why This Field Is Growing:
Job Security Considerations: While AI automates some tasks, the field is expanding faster than automation can replace humans. New AI tools create more demand for skilled data scientists who can deploy and customize them. However, competition is increasing as more people enter the field - strong skills and continuous learning are essential.
I found an interview with Sarah Martinez, data scientist at a healthcare tech company in Austin, Texas. She described a typical day:
"I start mornings reviewing dashboards to see if anything looks unusual in our patient engagement data. Then I meet with our product team to discuss a new feature idea - they want to predict which patients are at risk of missing appointments so we can send reminders. I spend a few hours cleaning and exploring data, which is honestly the least glamorous but most important part of the job.
After lunch, I work on building a machine learning model using historical appointment data. I test different algorithms to see what gives the best predictions. When something looks promising, I create visualizations showing how accurate the model is and what factors most influence appointment attendance.
Late afternoon, I present findings to stakeholders who don't have technical backgrounds - this means translating 'precision-recall curves' into 'here's how many patients we can successfully reach.' I love this part because good data science only matters if people use it to make better decisions.
I spend the last hour of my day reading papers about new techniques, responding to questions from the engineering team about how to deploy my model, and planning tomorrow's work. The job is part math, part coding, part storytelling, and part business strategy - never boring!"
Why This Career Interests Me: I love finding patterns in data and solving problems with logic. I'm good at math and programming, and I enjoy the satisfaction of building something that works. The combination of technical skills and creative problem-solving appeals to me. I also like that data science applies to so many industries - I could work in healthcare, environmental science, sports analytics, or tech, depending on what interests me most as I learn more.
How My Skills Align:
Concerns or Questions: Is this field becoming too competitive as more people enter? Will AI eventually automate most of what data scientists do? How do I stand out among thousands of other people with data science degrees? Do I need a master's degree or can I break in with a bachelor's and good portfolio?
10th grade student interested in graphic design and creative fields
Intended Direction: Bachelor's degree in Graphic Design, Digital Media, or Human-Computer Interaction at a school that integrates AI/tech into curriculum
Top School Choices to Research:
Alternative Paths I'm Considering:
Career Vision (5-10 Years Out): Work as UX/UI designer or creative technologist at tech company, design agency, or as freelancer. Specialize in human-AI interaction design - creating interfaces that make AI tools accessible and intuitive for everyday people. Want to be someone who bridges art and technology, not just someone who uses AI tools but doesn't understand them.
Backup Plans: If full-time design proves too competitive, can combine design skills with marketing, education, or nonprofit work where visual communication is valuable. Or teach design while freelancing on the side. Having both creative and technical skills provides flexibility.
How I'll Build AI Understanding Alongside Design Skills:
Specific: I will complete the 8-hour "AI for Everyone" course on Coursera and create one design project using DALL-E or Midjourney to understand generative AI firsthand.
Measurable: Course completion certificate + one completed design project with process documentation.
Achievable: 8 hours of coursework = 2 hours per week for 4 weeks, easily fits my schedule. Design project can be 3-4 hours over a weekend.
Relevant: Directly builds AI literacy for my creative career interests. Understanding AI tools is becoming essential for graphic designers.
Time-Bound: Complete course by November 22, design project by November 29. Total deadline: November 29.
Accountability Partner: My friend Marcus (also in class) is learning Python for game design. We'll check in weekly about our progress on our 30-day goals and troubleshoot challenges together.
I used to think AI would make human artists obsolete, which scared me since art is my passion. But after this lesson, I realize AI is a tool - incredibly powerful, but still a tool. The future belongs to designers who can combine technical skills with uniquely human creativity, storytelling, and understanding of what makes designs emotionally resonant.
My plan focuses on becoming that kind of designer: someone who understands both the art AND the technology. I don't want to be a designer who resists AI and falls behind, or someone who just prompts AI and calls it creativity. I want to use AI strategically to enhance my work while developing skills AI can't replicate - like understanding client psychology, creating original concepts, and making designs that connect with human experiences.
I'm excited and a little nervous, but mostly I feel empowered. I have a roadmap now, not just vague hopes. Even if the creative field changes dramatically, I'll be prepared because I'm building both artistic vision and technological literacy. That combination makes me valuable in whatever the future holds.
Using These Samples in Your Classroom:
Common Student Shortfalls and How to Address Them: