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Bringing Computational Thinking into A Freshman History Class

December 20, 2017

I’ve long been interested in the notion of teaching computational thinking—helping students to recognize the power of computers to help them to understand data, gain insights and solve problems in fields outside of the traditional realm of computer science. You can read https://quantumprogress.wordpress.com/computational-modeling/, when I was working to introduce computational modeling to my freshman physics classes.

Ten years later, there are even more examples and evidence that students need to be learning to see the computer as a powerful thinking tool that can allow them to ask new questions, and open up entirely new fields of study. Here are just a few projects that have caught my eye recently

  • What is a Computational Essay? by Stephen Wolfram. This is a pretty amazing essay from the inventor of Mathematica, Wolfram Alpha and now the Wolfram One Computational Platform. Wolfram shows how students can use this platform to easily analyze differences between languages, the color range used by Van Gough, the history of the English Civil war and more. Still, every time I read Wolfram’s essays, I get super excited about the possibility, but when I start playing with the actual Wolfram Language I find myself struggling to find the right command to know what I need to do. I guess this shows how awesome it would be if I’d written my very own programming language, or maybe it just shows I really am getting old.

 

  • Gender roles with Text Mining and N-Grams by Julia Silge. In this post, Dr. Silge describes how she was able to use text mining to find all of the verbs following the pronouns he and she in Jane Austen’s works. From that, she was able to graph the words that show the largest differences in appearing after “she” compared to “he”, and the results showed thinking words like “remembered”, “read” “felt” and “resolved” are far more likely to follow “she”, while action words like “stopped”, “takes”, “replied” and “comes” are more likely to follow “he.” I think this could be a seed of a great collaboration with an English teacher.

 

I’ve been thinking about this last project on and off for a few years now, and have discovered a number of similar efforts by historians to create and study archives of fugitive slave ads, including Freedom on the Move, and this small collection of ads from Brandywine, Maryland, a small town in Prince George’s County, Maryland. All of this got me thinking that there must be a way to teach a small version of this lesson to students in our 9th grade US History class that would help them to see the ways in which historians make use of computational tools to gain new and important insights into their work, the utility of big data as a primary source, and the ways in which it can be used to add context to the typical narratives students already encounter.

This fall, a new US History teacher, Giselle Furlong, and I began to plan how we might teach a two day lesson using the Brandywine archive of fugitive slave ads, and I’d like to share what we came up with here as an example of how we tried to integrate computational thinking into a history class to give students a richer understanding of slavery and slave narratives.

Students in the class use a fantastic collection of primary sources as their textbook, which has been thoughtfully assembled over many years by our history department. In this course, they learn to do the work of historians, closely reading primary sources, carefully annotating each one, putting sources into conversation with each other in Harkness style discussions. Before our unit, students had completed reading significant excerpts from the Narrative of the Life of Frederick Douglas.

We began our lesson by asking students to simply look at the website Brandywine Slave Ads, after orienting them to the location of Prince George’s county, very close to the Eastern Shore of Maryland described in Douglass’s narrative, and barely a two hour drive from our school. Even though the web table isn’t a very useful data structure, I was impressed by the insights students were quickly able to find just by doing simple searches within the webpage with command + F, and looking for terms like “Gender : F” to discover that there were only 15 females in the dataset.

We then showed them how to copy and paste this web table to a Google sheet, which then allowed you to more easily process and sort the data by column. Still, however, the important data of gender, age, and date of escape were merged into fields with other data that made it difficult to answer many of our most typical questions, so I showed them how you can use the Regular Expressions and the REGEXTRACT function. For example, using the function REGEXTRACT(B3,” [MF] “) would pull out the occurrence of M or F when surrounded by spaces from the text block that describes gender, date of birth, and age. The key lesson I wanted students to see appreciate is when they should recognize a task that should be automated, and then how to go about figuring out how to automate it.

At this point, we divided the class into five groups and gave them the lesson we’d written in Canvas that gave each group a specific topic to focus on. (I’ve pasted the actual lesson below for those who are curious. Each group had to take our spreadsheet of structured data, and focus on one specific aspect, gender, reward offered, age, date of escape or location.

We gave the students 30 minutes to look at this data, and I was deeply impressed by both the questions they were asking and some of the things they were able to do. One student realized that numbers pulled out of the text by REGEXTRACT were still treated by Google sheets as strings, but this could be remedied by adding a 0 to each number, allowing you to then calculate averages and other statistics from numerical data.

At the same time, most students were completely unfamiliar with spreadsheets, not knowing how cells are addressed, how to do even simple calculations, enter formulas or how to copy formulas from cell to cell by dragging, or make graphs. And it’s infinitely harder to make a graph of data when you have a big pile of data and aren’t quite sure of what to graph. None of this really surprised me—I know spreadsheets have fallen out of favor in my own physics classes, but at the same time, I think they are a very powerful tool used across nearly every industry and subject that is a gateway toward seeing the utility of computational thinking, and this is the kind of work students are going to need to do in the “real world” regardless of what job they end up having.

Within about 30 minutes, each group was able to put together a small paper describing their finds, and we still had enough time left over for a short discussion where groups shared their most interesting finding or remaining question.

On the following day, we asked students to again split into small groups and answer the following questions based on their work with the fugitive slave ads:

  • What do we know?
  • What don’t we know?
  • What surprises you?
  • What is the connection between slave narratives and the fugitive ads?
  • What structures are in place to limit escape

You can see some of the responses that came up in our discussion on this whiteboard.
NewImage

Overall, it felt like we could have continued this discussion for at least another class or two. Students seemed to enjoy collaborating in small teams, uncovering insights about data and trying to find connections between this work and the previous work they had done researching slave narratives.

Here are a few takeaways I had about how students understood the value of computational thinking in this work:

  • Students aren’t digital natives, but they do know some handy tricks that make them seem that way. I was impressed with how quickly they could find details simply by searching a webpage with Command+F, but beyond these tricks, students were challenged to find ways to use the computer to discern more meaning from the data
  • Students are mostly befuddled by spreadsheets. No student recognized how putting data in a spreadsheet would make it easier to search, sort and organize, and all were befuddled by the arcane ways in which you address cells, manipulate data and make charts, but they were able to make progress with clear instructions, some guidance, and Google. While it doesn’t fit within the confines of a history class, I do think students would benefit from seeing the power of spreadsheets as a fundamental computing tool and would love to see this incorporated into a math curriculum that spent some time working with large sets of data.

It was also clear that this project added some context to students’ understanding of the institution of slavery. By researching these advertisements, students were better able to understand some of the institutions that were in place to prevent enslaved people from escaping, and also the large monetary enslaved people held for slave owners. Together, these narratives and fugitive ad data paint a more complete and complex picture of slavery, one that highlights the the many ways in which enslaved peoples struggled against the institution, but also shows the ways in which so much of society was built upon slavery, well beyond just evil slave owners, keeping slaves in bondage was written into laws, customs and contracts innumerable ways, and so it isn’t surprising we have so few stories of escape.

IN-CLASS PROJECT – Maryland Fugitive Slave Ads

In this mini-project we will explore primary source evidence in the form of Fugitive Slave Ads from 1781-1861 from Prince George’s County, MD. Here is a link to the website with all source material: http://brandywinemd.com/history/runaway-slave-ads/

Here is a link to the spreadsheet whose data you will be manipulating

We will break into 5 groups, each with a different task of exploring the data. Questions to consider:

  • What does this evidence tell us about fugitive slave ads in this region?
  • What does this evidence tell us about rates of escape among enslaved men and women in this region?
  • What does this evidence tell us about the geography of this region and the proximity to freedom for enslaved people?

Group 1

Task: What is the average age of escaped men? escaped women? 

Group 2

Task: What was the reward in 1850 (year Fugitive Slave Act was passed) what is the value of that reward in 2017 dollars? Who was the most “valuable”? Why? Choose three other years to calculate reward value.

You have find this information with this inflation calculator: http://www.in2013dollars.com/1860-dollars-in-2015?amount=1

Group 3

Task: What was the gender breakdown of escaped men and women?

Group 4

Task: Create a scatterplot plotting the number of escaped slaves and the year of escape. What patterns do you notice? What are the most significant dates/date range? X axis = year of escape; Y axis =  number of escaped enslaved peopleConsult this resource to help you make the scatter plot: 

Group 5

Task: Investigate the locations for each fugitive slave advertisement. Use this interactive historic map to aid your search: http://slavery.msa.maryland.gov/html/mapped_images/mapsindex.html

– What is the distance to freedom? 

– Compare the historic maps to current Google Earth/Maps. 

 Final Task:

Each group must write a brief summary of their findings – the SIGNIFICANCE (who, what, why, where). Submit your paragraph to this post. Put this data and your findings in conversation with what we have discussed about Douglass and Jacobs – What did resistance look like in Prince George’s County at this time? Are these numbers higher or lower than you might expect? Why? 

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2 Comments leave one →
  1. Jim McNinch permalink
    January 19, 2018 11:37 am

    John,
    I have used the spreadsheet skills I learned in your Honors Physics class in ‘04-‘05 in many aspects of my life — in personal finance, organizing large events, and my graduate education. It was unfortunate that students in the non-honors track did not get this exposure, and later in my education, there was an obvious gap between those with and without a similar foundation, not only in science courses. The emergence of GoogleDrive and similar tools has made wonderfully useful collaboration both very convenient and essential in the workplace. I think a ‘crash course’ in spreadsheets belongs in the curriculum early on for all students.

    • January 19, 2018 2:34 pm

      Jim!
      It’s always great to hear from former students. Thanks so much for responding. I’m really amazed by the power of Google sheets compared to what we used to do back in the olden days of honors physics, and will try to find more ways to get students thinking about these skills in our classes.

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