Use this working research document to investigate how AI assistance may shape computer programming, develop a focused evidence-based argument, and plan your final paper. Follow the checkpoints, adapt the pathway to your experience, and follow your teacher’s requirements for length, citations, and AI use.
Choose one research lane from Step 2, or name your own. What focused research question will you investigate?
Create an initial source plan for your question. Name at least three kinds of sources or search leads you will pursue, and explain how you will check credibility, find more than one perspective, and verify claims. You may revise the plan as you research.
Investigate how AI assistance may change the work of computer programmers. Your job is not to predict the future with certainty or simply list AI tools. Build an evidence-based answer to a focused question, consider more than one perspective, and explain what your evidence suggests about the skills and choices people may need.
This project is designed for a mixed-age, mixed-grade 9–12 group. Choose a manageable path: everyone completes the core checkpoints; if you want a stretch challenge, add the extension prompts. You do not need prior programming experience. If you do have experience, use it to ask sharper questions—not to replace research.
A research paper that answers your own focused research question. Your teacher will set the expected length and citation style. A strong paper will:
State a clear, arguable answer (a thesis) to the research question.
Use several credible sources, including sources that show different perspectives.
Support claims with accurate evidence and explain how the evidence connects to the thesis.
Distinguish what sources demonstrate from what they predict or speculate.
Cite borrowed ideas, facts, quotations, and data using the class citation style.
End with a conclusion about what your findings mean for the future of programming.
Before researching, write a short “I think / I wonder” note. What tasks might AI help programmers do? What might still require people? What concerns or opportunities come to mind? Treat this as a starting point, not evidence.
Checkpoint: Keep this note. You will revisit it after your research and identify what changed.
Pick one angle, or propose another with your teacher:
Skills and learning: How could AI coding assistants change what new programmers need to learn?
Work and careers: Which programming tasks might change, and which human skills may remain important?
Quality and reliability: When does AI-generated code help or create risks such as bugs, security flaws, or hard-to-maintain software?
Access and opportunity: Could AI tools make programming more accessible? Who might still face barriers?
Responsibility and ownership: What responsibilities should programmers have when using AI-generated code?
Human–AI teamwork: Which tasks are best done by a programmer, an AI assistant, or both—and why?
Turn your lane into a focused, researchable question. Avoid questions that can be answered with only “yes” or “no,” or that ask you to know the future for certain. Useful frames include: “How might…?”, “Under what conditions…?”, and “What should… consider when…?”
Checkpoint: Your question is specific enough to guide searches, but open enough to allow a nuanced answer. Ask your teacher to approve it before you collect most of your evidence.
Start with search terms that combine your topic with terms such as AI coding assistant, software development, programming education, code quality, security, accessibility, workforce, or human oversight. Try different terms if results repeat the same viewpoint.
Look for a mix of source types, such as:
Research studies or papers, including work that explains its methods and limits.
Government, university, or professional organization reports.
Interviews or surveys with programmers, educators, or employers.
Documented tests or case studies of AI-assisted programming.
Carefully reported journalism that links to evidence and identifies its sources.
AI tools may help you brainstorm search terms or explain unfamiliar vocabulary. Do not treat an AI-generated answer or citation as a source. Open each source yourself, confirm that it exists, read the relevant parts, and verify important claims against the source. Do not enter private or sensitive information into an AI tool.
For every source, record who created it, when it was published or updated, what evidence it uses, and what its limitations might be. Ask:
Is the author or organization qualified to address this question?
Does the source show how it reached its conclusions, or link to evidence you can inspect?
Is it reporting observed results, making a prediction, or expressing an opinion?
Could the author or organization benefit from presenting one side? What does that mean for how you use it?
Is the information current enough for your question? Have you checked whether another reliable source agrees?
A source can still be useful even if it has a point of view; identify that point of view and corroborate its claims. Do not count search snippets as evidence.
Make one entry for each source. Record its full citation information as you go so you do not have to reconstruct it later. For each useful piece of evidence, note:
The claim, result, example, or quotation (use a short quotation only when the exact wording matters).
The page, section, table, or paragraph where you found it, if available.
Whether it is a finding, an expert interpretation, a prediction, or an opinion.
How it supports, complicates, or challenges a possible answer to your question.
A limitation, counterpoint, or question you still need to investigate.
Use your own words for notes. Clearly mark any exact quotation. Never copy notes into your paper without quotation marks and a citation when needed.
Group your evidence into two or three themes. Look for patterns, disagreements, conditions, and gaps. For example, a tool might speed up a task in one setting but need careful human review in another. Do not force your sources to agree.
Draft a thesis that directly answers your question and previews your reasoning. A useful working pattern is: “AI assistance may ___, especially when ___; however, ___, so programmers will need to ___.” Adapt it to your evidence rather than filling it mechanically. Revise your thesis if the sources do not support it.
Checkpoint: Can a reasonable person disagree with your thesis? Does each part have evidence? Does your answer make room for uncertainty or conditions where appropriate?
Use this flexible structure; adjust it to fit your question and teacher’s requirements:
Introduction: Introduce the issue, give just enough context, pose or restate your research question, and end with your thesis.
Body section 1: Explain your first reason or theme with evidence and your analysis.
Body section 2: Develop another reason or theme; compare evidence where useful.
Body section 3 (if needed): Address a counterargument, limitation, risk, or different perspective. Explain what it changes—and what it does not change—about your thesis.
Conclusion: Answer “What do the findings suggest?” Identify an implication for programmers, learners, employers, or society. Avoid presenting a guess as a certainty.
References / Works Cited: List sources in the format your teacher assigns.
In every body section, explain the evidence in your own reasoning. A quotation or statistic does not explain itself. Use AI only in ways your teacher permits; verify suggestions, preserve your own analysis, and disclose AI use if the assignment requires it.
Revise first for ideas and organization, then for sentence clarity, grammar, citations, and formatting. Check that each factual claim is supported, every source is cited, quotations are exact, and predictions are labeled as predictions. Ask a peer to identify the strongest evidence and one point that needs clarification.
Return to your Step 1 note. What changed in your thinking? What remains uncertain? What is one thing you would research next?
Core path: Use one focused question, gather evidence from several credible sources, compare at least two perspectives, and support a clear thesis with citations.
Build-confidence path: Choose a question from Step 2, use teacher-approved sources or databases, and organize evidence with a teacher-provided graphic organizer. Ask for a conference after your first source and thesis draft.
Stretch path: Compare evidence from different methods or time periods; examine how a source’s incentives affect its claims; explain a limitation in the available evidence; or propose what further study would help answer your question. More sources are not automatically better—use sources that add trustworthy, relevant evidence.
My research question is focused and approved.
My paper answers the question with a clear thesis.
My sources are credible for the claims I use, and I considered their limitations.
I included more than one perspective and explained the evidence.
I distinguished observed evidence from predictions and opinions.
I cited ideas, quotations, facts, and data that are not my own.
I followed my teacher’s requirements for length, citation style, and permitted AI use.
My conclusion explains what the evidence suggests without claiming certainty about the future.
After reviewing your evidence, draft a working thesis and a brief paper outline. Include two evidence-based themes, one counterpoint or limitation, and a note about what your conclusion can—and cannot—claim about the future.