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Credit: Martin Grandjean

Milestone 1: Group formation and initial questions

Benjamin Xie & Gregory L. Nelson

The first step of any software project is defining why the project is happening at all. What problem is it solving? Why have the specific people on a team come together to solve it? What makes them the right people to solve it? Do they have the skills to solve it? In this homework, you're going to answer these questions, designing your organization intentionally.

Step 1: Creating a team

Most teams come together around trust first and then choose a problem. This is because is trusting relationships are necessary for collaboration: they provide the psychological safety (Edmondson 1999) necessary for risk taking, feedback, and open communication. Because of this, we're going to form teams first, and then identify problems.

Your team must be 3 to 5 people. (We want the teams large enough that you encounter communication and coordination complexities that reflect real teams in practice). Because of the size of this class, you're not going to be able to form the exact team you might want. You're also going to have to interview each other to assess the potential for trusting relationships.

Here's the process to follow

Once you have a team, write your names down on the team registration sheet for credit for today.

Step 2: Create group infrastructure

Your team needs infrastructure to effectively communicate and collaborate.

Step 3: Identify 3 potential data science questions

Ideate questions you can answer within the scope of this quarter. Remember that questions are not solutions—they are characterization of an unknown.

We fully expect this step to take more time than we have in class. Discuss, debate, and deliberate outside of class to arrive at a problem you're all excited about solving this quarter.

Because we'll have limited time in this class to build, here are a few constraints on the questions you choose:

Create a page on your GitHub organization's wiki with your 3 potential data science questions. Title the wiki page "Potential Questions". On the page, write each research question and an accompanying paragraph for each question providing more information about this question. This additional information may include some of (but not necessarily all of) the following:

  1. Goals: What are you trying to use data science to do? What decision are you informing?
  2. Prior Knowledge: What do you know or assume beforehand? Why?
  3. Social Relationship: How may you interact with other stakeholders when conducting your analysis?
  4. Models: How may you represent your objects of analysis?
  5. Choices: What options exist for the decision you are informing?
  6. Outcomes: Given these choices, what are the outcomes of deciding on a given choice?

Grading Criteria

For activity credit, write your names down on the team registration sheet.

For homework credit, you will have updated your team GitHub repository's wiki as stated in Step 2.

Your shared GitHub space will be graded on the following scale:

Further reading

Ko, A. (2017). What makes a good research question?

Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative science quarterly, 44(2), 350-383.