Students in eighth grade Social Studies recently participated in a mini-unit on “computational thinking” in partnership with Dr. Tom Hammond and Dr. Julie Oltman from Lehigh University. Computational thinking is a system of problem-solving skills used to find patterns and rules in data. This is a well-established concept in quantitative fields such as Mathematics and Computer Science, but it also has great potential to be applied to other disciplines such as Social Studies, English, and Global Languages.
One tool to help students apply computational thinking strategies is ArcGIS. ArcGIS is an online geographic information tool used to compile geographic datasets into maps, which can then be manipulated and analyzed for patterns. This data can include a wide range of topics such as employment and other economic data, water poverty, tracking rates of disease, climate data, etc. For our mini-lesson, we selected the topic of terrorism. For our purposes, terrorism is an act of violence by a non-state (non-government) person or group with the intention to achieve a political goal.
Our day one discussion began with defining our key terms, terrorism and computational thinking, and then jumping right into our data set on ArcGIS. An ArcGIS map represents information in points or dots, where each dot can represent an instance of a certain type of item or event, including specific information about that item or event. In our example, each dot represents a specific act of terrorism. However, although the data for each event is relatively detailed, it is still devoid of contextual information in terms of motivations and possible larger patterns. Basically, why is terrorism happening in a particular time and place? For example, anti-war terrorism in the U.S. during the Vietnam War era has different goals and patterns than anti-government terrorism in the U.S. after that period. But on the ArcGIS map, they all look the same. This is where computational thinking can help.
By applying additional ArcGIS tools such as a timeline slider to see changes over time, cluster mapping to see grouping trends by geographic area, and filters to control the types of terrorist attacks or groups visible at one time, students can act as detectives to find patterns in the data, even with little or no contextual knowledge about global events in those regions or time periods. Our sample model to illustrate this concept was separatist violence in North Ireland by groups such as the Irish Republican Army, which is very distinctive and easy to spot on the ArcGIS map. By the end of day one, students had the tools and skills they needed to conduct independent computational thinking analysis.
For the second day of the activity, students were tasked with analyzing the ArcGIS terrorism data in the continent of Africa, as that was the current region of study in our Social Studies class. Their goal was to find one or more patterns (e.g., clusters, change over time, types of attacks, key groups, etc.), and then conduct additional internet research to learn more. Examples of patterns that students discovered on their own included groups and events such as Boko Haram in Nigeria, Al-Shabab in Eastern Africa, violent anti-Apartheid protest in South Africa, the Rwandan genocide, and more. For several students, these discovered patterns became topics for their final research paper.
Overall, this was a great experience for the students as well as for myself, Dr. Hammond and Dr. Oltman, and we are already considering our next steps to incorporate additional computational thinking activities into the Social Studies curriculum next year. Stay tuned!
Here are some of our students’ reflections on the activity:
- It was interesting to actually learn how to do cool stuff with a computer and learn at the same time.
- It was interesting to have all the data in front of us and manipulate it.
- I like being able to find and narrow down the information to help me to draw certain conclusions and viewpoints.
- It was very different than the activities we have done before, and let us work and investigate independently
- I loved being able to apply different filters and visualization-techniques to the data!! One of my favorite activities!