Module 9 – What is Critical Data Storytelling?

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  Posted by Sara Vogel, PhD. (she/her) on June 14, 2023 at 2:24 pm

  After completing the Module “What is Critical Data Storytelling?“, respond to the following prompts with your reflections:

  • What did you learn from your data investigation above? What lingering questions do you have?
  • What are some datasets or visualizations that your students (and/or their students) are likely to interact with?
  • What are some tensions your students (and/or their students) are likely to encounter when reviewing large-scale datasets or data analyses?
  • What data sources (student stories, news articles, photography, historical analysis, etc.) are common in your classroom? How can these data sources enrich, and be enriched by, data explorations?

• Maria Jerskey (she/her)

  Member

  July 5, 2023 at 5:31 pm

  What did you learn from your data investigation above? What lingering questions do you have?

  I learned that I have a lot to learn about framing questions for data sets. For example, I wanted to see the distribution of ELL’s on the NYC DOE CODAP data launchpad, but wasn’t successful. 

  What are some datasets or visualizations that your students (and/or their students) are likely to interact with?

  For the students in my Intro to Bilingualism course, I’m really not sure. 

  What are some tensions your students (and/or their students) are likely to encounter when reviewing large-scale datasets or data analyses?

  I think the tensions can be around: 1. Unfamiliarity with working with data sets to begin with! Taking the time to transition from “what do I need to do and how fast can I do it” to “where am I (or my peers, my students, my family) in this data set? Where can I begin to play to get a sense of what it is showing me? How can I start asking questions?” 

   What data sources (student stories, news articles, photography, historical analysis, etc.) are common in your classroom? How can these data sources enrich, and be enriched by, data explorations?

  In terms of data sources: yes: student stories, news articles, photography, historical analysis, but also videos. I would say all of them can be enriched by data explorations because they take something that appears static (analyzed, concluded, “truth”) and makes it dynamic (what’s the context? Who created the data source? When was it created? Who is included? Who is excluded.) 
  Dr. Atasi Das (She/her/hers)

  Member

  July 11, 2023 at 6:39 pm

   

  • What did you learn from your data investigation above? What lingering questions do you have?

  I learned various ways to play around with visualizations and allow for various understanding of all this information. I think it is interesting to consider how historical understanding needs extra intentional efforts to make it visible.  I loved seeing the mapping function.

  • What are some datasets or visualizations that your students (and/or their students) are likely to interact with?

  I’m not quite sure what data sets my students will be looking into.

  • What are some tensions your students (and/or their students) are likely to encounter when reviewing large-scale datasets or data analyses?

  I think that my students, particularly in their introductory course in a graduate program, have very dichotomous experiences with mathematics and data. Either students love seeing data and thinking of the connections and question or they are very tentative and question their own abilities of sense-making (which seems to produce overwhelming power of data acceptance, IMO).

  • What data sources (student stories, news articles, photography, historical analysis, etc.) are common in your classroom? How can these data sources enrich, and be enriched by, data explorations?

  I think student observations (of students, communities, schools) and commonplace narratives are data sources that are often referenced and drawn upon.