If you're like me, writing helps you really organize your thoughts, identify gaps in your thinking, fill in those gaps, and tie concepts together more coherently.

Following are some writing prompts for Data, Code, Ethics. It may be that, after reading some of the course resources or engaging the hands-on activities, your quill is ready to go! If not, the following prompts may help you get started on that next blog post, book chapter, academic paper, syllabus, policy proposal, letter to the editor, or tweet.

And since we communicate and synthesize our thoughts in different ways, these don't need to be writing per se. You could make a (short) video, an infographic, and hand-drawn mind map, anything that helps you gather your thoughts and communicate them to others.

This "writing" can be private or public, for posterity or ephemeral. But please share what you created with our cohort in Yellowdig. Though, if you find after writing that it's something you would like to keep between yourself and your journal, that's fine too. Though you may consider sharing a couple sentences in Yellowdig, to let us know where your mind is headed, and even why you want to keep it private. It's up to you.

All of these prompts are optional. If they help you think through, synthesize, or communicate what we're engaging with during DPL, awesome! If they help you sync with others who are engaging the same issues, great! If not, leave them be. These are just here to help get you started, if you need a little spark.

Each prompt is labeled with one or more categories: Data, Code, and/or Ethics. This will help you strike the right balance between the three, whatever the best balance is for you. (I.e., if you are trying to focus equally on each, or if there is one particular area you are keen to really "level up" on.)


Activity reflection (DATA | CODE | ETHICS)

After performing one of the activies provided in this course, reflect on what you did or learned in the course of that activity. Then write about what you learned, what you did or didn't find important in the activity, or perhaps craft a step-by-step tutorial for others (perhaps making some tweaks).

Coding tutorial (CODE | DATA)

Create a step-by-step tutorial for your students/faculty/staff that walks them through the first steps of learning how to code. What information do they need to start? How much do they need to install? Is where R for Data Science started the best starting point for your cohort? Do you have standard pedagogical practices in your own teaching that could improve the teaching of beginner coding?

Ethical gut-check (ETHICS)

In the past, we have interspersed ethical gut-check discussions into the in-person version of this course. These were opportunities to take a break from sometimes highly technical activities to slow down and make sure we had a chance to reflect on, and debate, the ethical ramifications of that activity.

Since those whole-group discussions are harder to come by in a mostly asynchronous, online course, we'll use writing as one way to engage that question. So for any activity, reading, discussion, keynote, workshop, etc. you've engaged this week, take some time to think through the ethical implications and write out your thoughts, no matter how preliminary or incomplete.

Some example ethical questions that could be applied are:

  • Who has access to the data behind this tool/practice/platform?
  • What are the data safeguards, including the retention/deletion practices?
  • What are the privacy, safety, and security risks introduced by the tool/practice/platform?
  • Who could misuse it?
  • Who is responsible for its misuse?
  • Who is the most vulnerable to its misuse?

And since no tool/practice/platform comes without risks of misuse:

  • Do the benefits outweigh the risks of harm?
  • Are there alternatives that accomplish similar goals with a better cost/benefit outcome?

Keynote reflection (DATA | CODE | ETHICS)

Reflect on an idea presented or issue raised by one of the keynotes this week. The specific topic is completely up to you.

Reading reflection (DATA | CODE | ETHICS)

Reflect on an idea presented or issue raised by one or more of the readings you engaged this week. Or, perhaps better, bring two or three of them into dialogue about an issue they differ on. Mediate, adjudicate, or synthesize that dialogue, as you find appropriate.

Thanks to Da Kraplak for making the header photo available freely on @unsplash.

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