Working in Groups

DATS 1001 — Final Project Collaboration Guide

Why Group Work Matters

Your final project is a cumulative demonstration of everything you’ve learned in DATS 1001:
cleaning, exploring, analyzing, modeling, and communicating with data in R.
Because data science rarely happens alone, this project is designed to help you learn how to collaborate effectively — sharing data, code, and ideas just as real data scientists do.

Group projects are an opportunity to:

  • Build confidence using the tools we’ve covered.
  • Practice team communication and organization.
  • Create something more ambitious than one person could complete alone.

1. Setting Up for Success

Meet Early and Make a Plan

Once groups are assigned, schedule your first meeting right away.
You’ll need to:

  • Choose a shared communication platform (Discord, GroupMe, Slack, whatsApp email, etc.).
  • Decide how you’ll divide responsibilities for each stage:
    • Data Proposal (find and clean datasets)
    • Poster and Presentation (summarize and visualize)
    • Final Report (synthesize and write up findings)
  • Set expectations for response times and deadlines.
  • Review the Data Proposal instructions together so everyone understands the goals.

Effective group work begins with structure, shared goals, and accountability.

2. Roles and Responsibilities

Groups of 3–4 people work best when everyone has a defined focus area but remains involved in the full project.
Assigning roles helps your team stay organized and ensures that all key tasks are covered without duplication.

You can rotate or share roles as the project evolves — the goal is coordination, not rigid separation.

Role Typical Responsibilities
Project Coordinator Keeps the group on schedule, organizes meetings, and handles submission to Gradescope.
Data Manager Finds and documents datasets, creates data dictionaries, and manages data cleaning.
Analysis & Modeling Lead Runs exploratory analyses, computes summary statistics, and develops models if applicable.
Visualization & Communication Lead Designs plots and figures, helps prepare the final poster, and ensures the written report is clear and visually polished.

If your group has three members, you can merge or share roles:

  • The Project Coordinator may also handle documentation.
  • The Analysis Lead may assist with data cleaning or visualization.

Everyone should contribute to all stages — from the Data Proposal through the Final Poster and Report — so that each person understands the full workflow.

3. Constructive Group Behaviors1

As a group, take 5 minutes to each write down and then discuss how you individually demonstrate constructive behaviors in a group.

Constructive Behavior Example in This Course Project
Cooperating Adjusts personal preferences to reach consensus on data or topic.
Clarifying Restates what’s decided: “So we’ll merge by country and year and visualize GDP vs CO₂.”
Inspiring Keeps energy high when things go wrong — “We can fix this error together.”
Harmonizing Smooths over tense discussions; uses humor to keep morale up.
Risk Taking Volunteers to learn something new (e.g., how to compute variance or make a faceted plot).
Process Checking Asks, “Are we on track for the proposal deadline?” or “Who’s finalizing the merge code?”

These behaviors help teams stay productive, kind, and on schedule.

4. Avoid Destructive Behaviors2

As a group, take 5 minutes to each write down and then discuss how you individually demonstrate destructive behaviors in a group.

Destructive Behavior How It Might Show Up in This Project
Dominating One person edits everyone’s sections without discussion or dismisses others’ code. Does the work designated for others, before others, and lets them know it.
Rushing Submits without checking that plots render or that code runs.
Withdrawing Stops replying in the shared chat or doesn’t open the Posit Cloud project.
Discounting Says “that idea won’t work” instead of exploring it.
Digressing Spends meetings off-topic, slowing progress.
Blocking Rejects all ideas without suggesting alternatives.

If you notice these patterns, pause and reset.
Ask: “What’s our main goal this week, and how can we divide it fairly?”
If your group encounters ongoing challenges, document your efforts to resolve them and note this in your reflection. I’ll review patterns in the teamwork surveys rather than individual disputes.

5. Communicate and Stay Accountable

Plan ahead to prevent confusion:

  • Keep one shared Posit Cloud project for code and writing.
  • Use colloborative tools like Google Sheets to keep track of your variables.
  • Create a simple schedule (e.g., “We’ll check in Sunday nights.”).
  • Set internal deadlines earlier than official due dates.
  • Share progress updates regularly: “Data dictionary done,” “Missing values fixed,” etc.

Short, regular check-ins prevent last-minute stress.

6. Making Progress Visible

Every group should be able to answer:

  • What have we finished?
  • What’s in progress?
  • What’s next?

Example workflow for the Data Proposal stage:

  • The Data Lead uploads a Google Sheet summarizing dataset details.
  • The Cleaning Lead adds R code chunks showing missing-value checks.
  • The Visualization Lead adds the first histogram or scatterplot.
  • The Documentation Lead writes captions and connects everything in Quarto.

Each person’s work is visible and reviewed by the team.

7. Handle Challenges Professionally

Conflicts are normal in group work. What matters is how you respond.

  1. Address concerns early and privately. Not in front of the whole group.
  2. Use “I” statements (“I’m confused about how we’re splitting the analysis”) instead of blame.
  3. Revisit your initial plan and clarify roles if needed.
  4. If problems persist, document what happened and reflect on it in your teamwork survey at the end of the project.

8. Reflection and Teamwork Evaluation

At the end of the project, you’ll complete an Individual Reflection and Teamwork Survey (10 points).
You’ll reflect on:

  • What you learned about working in a team.
  • How your group divided work and communicated.
  • What you would do differently next time.

This reflection is part of how you’ll demonstrate professional skills beyond coding.

9. Quick Group Checklist

Remember:
The final project isn’t just about data — it’s about collaboration.
Treat your teammates as partners, keep your process organized, and create something you’re proud to share at the poster session.

Footnotes

  1. Brunt (1993). Facilitation Skills for Quality Improvement. Quality Enhancement Strategies, 1008 Fish Hatchery Road, Madison, WI 53715.↩︎

  2. Brunt (1993). Facilitation Skills for Quality Improvement. Quality Enhancement Strategies, 1008 Fish Hatchery Road, Madison, WI 53715.↩︎