Activating Engagement and Cognition with Student-Generated Historical Images and Artifacts

Balazs Szelenyi
Course Subject:Sociology of Boston
Student Level:First-year
Number of Students:20 students per class, 2 sections
Developed by:Balazs Szelenyi, International Programs, College of Professional Studies

What Students Did

Students used generative AI to create images of fictional historical characters and their artifacts in the classroom exercise. Following the creation of these images, they critically analyzed the output produced by the AI.

In a recent classroom activity, students employed DALL-E, a generative AI tool, to visualize the topic of Irish Immigration to Boston in the 1850s. Dall-E produced an image depicted a young immigrant girl in the 1850s, seated at a pier with the Custom House clock tower in the background. We used this as a teaching moment to highlight that the clock tower hadn’t been built at that time. This exercise served as a practical introduction to media literacy, emphasizing the importance of critically assessing and understanding historical contexts in images.

Learning Goals and Purpose

We were building content knowledge related to the topic, which during that portion of the class was Irish immigration, but also the capacity for critical consumption of media. Digital media literacy skills combined with lessons on prompt engineering skills are important, and they will be even more important as images and videos are increasingly being generated with AI.

Assessment

These assignments are usually done in class. Images, artifacts, and reflections are uploaded to Canvas as part of their participation grade.

By creating this visual discussion I had to slow down the class, but the cognition level rose. It’s really important to know that when you are creating these images, you are checking the student’s ability to spot the mistakes.

Faculty Reflections

I wanted to have a student-centered pedagogy where students were engaged in the materials. It created a personalized learning experience because students were involved in the creation of the letters, the images, etc. Students’ prompt engineering skills noticeably improved. Some students took it to a level where they were creating 5-6 minute videos. I started to lecture less, and the students started to produce more, and then we had conversations around the products that they were producing. This is really working for me right now.

Step-by-Step Student Instructions
Module: Immigration

Step 1Develop background knowledge: Students are assigned background readings on Irish immigration and watch a documentary from the Irish in America series.
Step 2In two groups, work with a given character to do the following:

  • 16-year old Irish immigrant girl, arriving in Boston 1850
    • Using DALL-E 3, generate a picture of the girl at age 16
    • Using ChatGPT, generate a reflection written by the person at age 50 in which she recounts her life as a young girl and what happened when she came to the United States
  • 16-year-old boy, arriving in Boston 1850
    • Using DALL-E 3, generate a picture of the boy at age 16
    • Using ChatGPT, generate a letter that the boy wrote to his mother back in Ireland, telling her about his experiences.
Step 3Project the character images and their artifacts on screen in class, drawing on their background knowledge from readings and video to discuss the following questions: What is accurate? What is a hallucination? How do you know?
Step 4Complete follow-on exercise using Chat-GPT to generate a play about the experience of Irish immigrant Mill Girls in Lowell, Massachusetts.
Step 5Complete written assignment: Drawing on their background work and in-class experience, students wrote and submitted essays about immigration to Boston in the mid 1800s.

Module: Gentrification

Step 1Develop background knowledge: Read excerpts from People’s History of Boston by Jim Vrabel
Step 2Use DALL-E 3 to generate images of slums and slum lords in the South End
Step 3Projected on screen, do a close reading of the images that were generated, for example asking “what do you see?” and “who’s in the windows?”

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