Due Date: December 18, 2025 by 11:59 PM PST
Submission via GitHub in your Final Project repository.
Technical Growth Synthesis - Final Project¶
Name: [Your Name]
Date: [Submission Date]
Weight: 5% of your final course grade (Pass/Fail)
Submission: Save as LASTNAME_growth_synthesis.md (or PDF) in your Final Project repository.
Length: Aim for ~2–3 pages (≈800–1200 words), but depth matters more than word count.
Format: Paragraphs, bullet points, or mixed formats are all fine — choose whatever helps you think clearly.
Grading¶
This is Pass/Fail. A passing reflection:
Engages with all of the required sections below
Is honest and thoughtful, not performative
Shows evidence of connecting your experiences to the course structure (projects, AI phases, glass-box design)
Before You Begin¶
Take 15-20 minutes to re-read your Growth Memos from Projects 1-5. Glance through your old project code too — not just Project 1, but flip through Projects 2, 3, 4, and 5 to see how your coding evolved over time. This isn’t busywork — it’s how you’ll remember struggles and breakthroughs you’ve already forgotten. You’ll be surprised how much you’ve grown.
This synthesis is an informal reflection on your entire ASTR 596 journey — a chance to step back and see the full arc of your learning. Like the Growth Memos, there’s no “right” answer. Honest, thoughtful reflection earns full credit. I’m not grading grammar or typos; I care about your thinking. (Should take ~1 hour after re-reading your memos).
The Big Picture¶
Looking back at your five growth memos and your semester as a whole: What’s the story of your computational growth? What themes or patterns do you notice across your memos? What connections emerged between projects that you didn’t expect? Was there a moment when you realized “oh, THIS is why we did that earlier”?
Try to ground this in 2–3 concrete moments or projects, not just general feelings.
Code Evolution¶
Now that you’ve glanced through your projects: How has your code changed over the semester? Think about: organization, readability, debugging strategies, documentation habits, testing approaches, how you structure functions and classes. You don’t need to include code samples — just discuss what you notice about your evolution as a programmer. You might reference specific projects or files (e.g., “my Project 1 star.py vs. my Project 5 JAX N-body”).
Computational Thinking Development¶
How has your approach to thinking about computational problems changed? When you encounter a new problem now, what’s different about how you break it down, plan your attack, or debug compared to Week 1? If it helps, compare how you would approach “build an N-body integrator” back then versus now.
The “Glass Box” Experience¶
Did building algorithms from scratch before using libraries change how you understand them? Any specific examples where implementing something yourself revealed insights that just using a library wouldn’t have given you? For example, think about your own implementations of: integrators, samplers, GP kernels, or neural nets.
Student-Led Explorations¶
If you pursued extensions beyond the base requirements: What drove you to explore? What did you gain from going further? How did these explorations shape your interests or research thinking? (Extensions that didn’t fully work still count — failed rabbit holes are often the most informative.)
If you didn’t pursue many extensions: What would you explore if you had more time? What rabbit holes are still calling to you?
Mindset Shift¶
Did you notice any change in how you approach being stuck or confused? Any shift from “this is impossible” to “this is hard but figure-out-able”? Did your relationship with “productive stupidity” or feeling lost change over the semester? Did you find yourself exploring beyond requirements out of genuine curiosity rather than obligation?
Collaboration & Community¶
How did working with classmates (in class or on Slack) shape your learning? Did your approach to asking for help, offering help, or pair programming change over the semester? Any specific moments where a peer interaction shifted how you understood a problem?
AI Scaffolding Reflection¶
This section helps me improve the course for future students — your honest feedback is valuable.
Your AI Journey
How did your use of AI tools evolve across the three phases? In Phase 1 (Projects 1-3), how did the restricted use and 30-minute struggle rule affect your learning? In Phase 2 (Projects 4-5), how did your relationship with AI change when you could use it more strategically? By Phase 3 (Final Project), could you catch AI errors you wouldn’t have noticed in Week 1? Be honest about both the benefits and the frustrations — I’m using this to improve the design, not to judge you.
Assessment of the Approach
Did the three-phase scaffolding approach work for you? What would you change about it? What advice would you give future students about navigating the AI policy? If you bent or broke the rules at any point, what did you learn from that (about AI, yourself, or the policy)?
Key Moments¶
What were the 2-3 most significant moments of your semester? These could be breakthroughs, frustrations that led to learning, “aha” moments, or times when something finally clicked. What made these moments important? Roughly when did they happen (which project/month)?
What You’d Tell Week-1 You¶
If you could send a message back to yourself at the start of the semester, what would you want past-you to know?
Preparation for Research¶
Do you feel this course has given you skills relevant to astronomy research? How do you expect the project-based learning approach, modular coding practices, and package design skills to impact your future research or career? What feels most transferable to thesis work, independent projects, or industry? Consider things like: version control, debugging, package design, modular code, test-writing, working with incomplete specs, or critiquing AI outputs.
Looking Ahead¶
What questions are you leaving the course with? What do you want to explore next (topics, tools, or projects)?
How do you feel about your growth this semester, and what are you most proud of?
Optional: Feedback on the Course¶
Any feedback on the course structure, projects, or pedagogy? What worked well? What would you change? This won’t affect your grade — I genuinely want to know. Specific examples are more helpful than general comments (e.g., “In Project 3, the X structure helped / hurt...”).
Thank you for your thoughtful engagement with this course. Your reflections help me understand what’s working and how to improve. More importantly, I hope this synthesis helps you recognize and own your growth as a computational scientist — that’s the part that lasts beyond this course.