👤 Individual Contribution to Group Project (10%)

2025/26 Autumn Term

Author

Dr Jon Cardoso-Silva

Published

17 December 2025

Modified

17 December 2025

The individual contribution component (worth 10% of your final grade) assesses your personal involvement in the 📦 Final Project. This assessment focuses on the quality of your contributions and how you’ve integrated feedback from earlier in the course.

⏳	Deadline	Same as Final Project (Winter Term W03, February 2026, 8 pm UK time)
💎	Weight	10% of final grade
📤	Format	Markdown file in `reflections/` folder

📁 Submission Requirements

Each team member must submit a personal reflection as a Markdown file in your project repository:

your-team-repo/
└── reflections/
    ├── <github-username-1>.md
    ├── <github-username-2>.md
    └── <github-username-3>.md

✍️ Required Content

Your reflection must include two main sections:

Section 1: Personal Contributions (60%)

Document your specific contributions to the project with evidence. For each major contribution, include:

## My Major Contributions

**Most significant commits:** 
- [abc1234](link-to-commit) - Description of what this commit did
- [def5678](link-to-commit) - Description of what this commit did

**What I implemented:**
[Detailed description of what you built or created]

**Technical decisions:**
[Explain choices you made and why. For example: "I chose to use a dictionary 
to store the API responses because..." or "I designed the database schema 
with separate tables for X and Y because..."]

**Challenges and solutions:**
[Describe problems you encountered and how you solved them]

That is, include:

Links to specific commits/issues/pull requests that most significantly show how you contributed to the project (don’t over-do it, just pick what’s more meaningful and substantial)
Clear descriptions of what you implemented and why you did it that way
Explanation of technical decisions and reasoning
Honest discussion of challenges you faced

Section 2: Learning Integration (40%)

Write up to two paragraphs demonstrating how your learning throughout the course influenced your contributions in the final project:

Reflect on how feedback from earlier assessments shaped your approach in this project. Consider:

Critical feedback or praise you received in the 📝 W04 Practice, ✍️ Mini Project 1 or ✍️ Mini Project 2 and how you improved your approach as a result
Comments from formative exercises or practice activities and how you used them to improve your approach
Insights from office hours, labs, or Slack discussions and how you used them to improve your approach

Be specific. Include actual feedback excerpts and explain how you changed your behaviour in response.

📋 Assessment Criteria

Component	Weight	What We’re Looking For
Personal Contributions	60%	Quality and significance of your contributions, evidence quality (commit links, file references), technical decision-making, problem-solving approach
Learning Integration	40%	Specific feedback examples with behavioural changes, connection between course learning and project practice, authentic reflection in your own voice

Marking Standards

To achieve a mark of 70/100 or above, you must:

Provide substantial contributions with clear evidence (commit links, specific file references)
Demonstrate genuine learning integration with specific feedback examples
Show behavioural changes based on that feedback
Write in an authentic personal voice (try to avoid using AI here or it will come across as inauthentic even if you mean what is written)
Connect your contributions meaningfully to the overall project

Common Pitfalls to Avoid

Things we spotted in previous years that made reflections weaker:

Vague descriptions: “I helped with the data analysis” is insufficient. Specify exactly what you did with commit links and file references.
Missing evidence links: Every contribution claim should have links to commits or specific file locations.
Generic feedback reflection: “I learned to write better code” doesn’t show learning. Quote specific feedback and explain exactly what you changed.
Not connecting feedback to behaviour: Mentioning feedback without explaining how it changed your approach misses the point of this section.
AI-generated reflections: Your learning journey should be personal and authentic. AI-generated text is often generic and lacks your unique perspective. We can tell.

📮 Need Help?

Post questions in the #help Slack channel
Check the ✋ Contact Hours page for support times
Book office hours via StudentHub to discuss your reflection approach

The goal is to demonstrate genuine engagement with the course material and your own growth as a data scientist. Focus on authentic reflection rather than trying to sound impressive.