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Growth Memo Guide

ASTR 596: Modeling the Universe

San Diego State University

What is a Growth Memo?

A Growth Memo is your personal reflection on each project - a brief, informal journal entry about what you learned, struggled with, and discovered. Think of it as documenting your journey from confusion to understanding, creating a record you’ll actually want to read later.

This isn’t a formal report or performance for grading. It’s an honest conversation with yourself about your learning process.

Why We Do This (The Science Behind It)

Research in cognitive science shows that reflection dramatically improves retention and skill transfer. Here’s what happens in your brain when you write these memos:

Memory Consolidation: Explaining what you learned forces your brain to reorganize information from working memory into long-term storage. You literally remember more by writing about it.

Pattern Recognition: By documenting your struggles across projects, you’ll start noticing patterns - “I always forget to check array dimensions” or “drawing diagrams helps me understand recursion.” These insights accelerate future learning.

Metacognitive Development: This is the ability to think about your own thinking. It’s what separates experts from novices. Experts don’t just know more; they know HOW they know, recognize when they’re confused, and have strategies to get unstuck.

What’s In It For You?

Immediate Benefits:

Long-term Benefits

How This Works

After completing each project, you’ll spend 30-45 minutes reflecting using our template. Write informally - like explaining to a friend or future-you. Include:

Submission Details

Format: Markdown (.md) preferred, PDF acceptable
Filename: growth_memo.md in your project repository root
Template: Use the provided growth_memo_template.md as your starting point
Length: ~400-800 words (30-45 minutes of writing)
Due: With project submission (Monday 11:59 PM)

The Three-Phase AI Connection

Your memos will document your evolution through our AI scaffolding phases:

Phase 1 (Weeks 1-7): Document struggles before using AI, what finally led to breakthrough Phase 2 (Weeks 8-13): Reflect on strategic AI use after baseline implementation
Phase 3 (Week 13-Finals): Analyze how AI amplified your capabilities

This creates a portfolio showing your growth from AI-dependent to AI-empowered.

Assessment Philosophy

You earn full credit for thoughtful, honest reflection.

There’s no “right” answer. I’m not grading the quality of your code through your growth memo - I’m recognizing your engagement with the learning process. Documenting mistakes and confusion demonstrates deeper learning than presenting only successes.

If you struggled for hours then had a breakthrough - that’s valuable data. If everything clicked immediately - that’s equally valuable. Both experiences matter.

Common Concerns

“What if I didn’t struggle?” Great! Reflect on what made it straightforward. What prior knowledge helped? What patterns are you recognizing? This self-awareness is just as valuable.

“What if I’m still confused?” Perfect reflection material. Document what you tried, what specific concepts are fuzzy, and your plan to clarify them. Identifying precise points of confusion is a crucial scientific skill.

“Will admitting mistakes hurt my grade?” The opposite. Honest documentation of mistakes shows engagement and growth. I only deduct points if you don’t submit a memo or submit something clearly thoughtless (like two sentences).

“I’m not a good writer” This isn’t about writing quality. Bullet points, informal language, and stream-of-consciousness are all fine. I care about your thinking, not your prose.

Example: Surface-Level vs. Meaningful Reflection

Surface-level: “I had trouble with the code but figured it out. I learned about Python arrays and how to debug.”

Meaningful: “I spent 2 hours convinced my force calculation was wrong because particles kept flying apart. After checking the physics three times, I discovered I was updating positions before calculating all forces - a classic integration order bug. This taught me that debugging isn’t just about syntax; it’s about understanding the algorithm’s logic flow. Next time I’ll diagram the update sequence before coding.”

The Bottom Line

These memos transform struggling through projects into building self-awareness about your learning. By Project 5, you’ll have a documented journey showing not just what you learned, but HOW you learn - a skill that extends far beyond this course.

Taking these seriously now directly feeds into your Technical Growth Synthesis Portfolio at semester’s end. Rather than scrambling to reconstruct your learning journey in December, you’ll have five detailed memos documenting your evolution from Phase 1 struggles to Phase 3 mastery. Your portfolio practically writes itself when you’ve been thoughtfully documenting all along. You’ll thank your past self for every specific detail you captured while memories were fresh.

Your future self (during thesis defense, job interviews, or research) will thank you for creating this record of your computational thinking development.


Remember: I’m assessing your reflection, not your struggles. Full credit comes from thoughtful engagement with your learning process, regardless of whether that process was smooth or challenging.