Data Science for Global Applications

Course materials for Data Science for Global Applications, by Dr. Anna Haensch and Dr. Karin Knudson

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Journal Prompts and List of Readings

The prompt for the reading journal entries in the first and third section of the course is as follows:

Please submit a journal entry reflecting on the reading

  • Your reflection should be a 250-300 word narrative.
  • Be sure to tie the reading back into your own studies, experiences, and areas of interest.
  • As part of your reflection, state 1-2 discussion questions based on the concepts discussed in the readings. This can be a curiosity question, where you’re interested in finding out more, a critical question, where you challenge the author’s assumptions or decisions, or an application question, where you think about how concepts from the reading would apply to a particular context you are interested in exploring.

The prompt for the reading journal entries in the data visualization section of the course is as follows:

Your reflection should be a 250-300 word narrative. Be sure to tie the reading back into your own studies, experiences, and areas of interest. As part of your reflection, find a chart or visualization from the news, a research article, or some source relevant to your educational/professional interests, and discuss how some aspect(s) of the chart relate to an idea or ideas from the reading. (Please include an image of the visualization as a file upload alongside your reflection, and cite the source). Reflections are to be submitted before class meets on the day the assignment is due.

The reading list for the course is as follows:

  • Critical Questions for Big Data by Danah Boyd and Kate Crawford.
  • Data Feminism: The Power Chapter by Catherine D’Ignazio and Lauren Klein.
  • Data Feminism: Collect, Analyze, Imagine, Teach by Catherine D’Ignazio and Lauren Klein.
  • Fundamentals of Data Visualization (Part I) by Claus Wilke.
  • Fundamentals of Data Visualization (Part II and Part III) by Claus Wilke.
  • How Charts Lie (Chapters 1 and 2) by Alberto Cairo.
  • Weapons of Math Desctruction (Chapter 1) by Cathy O’Neil.
  • Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification by Joy Buolamwini and Timnit Gebru.