Empowering Social Studies Students as Ethical AI Users

Outline

The content that will be presented will be the findings from the research study. The presenter will connect and engage with the audience by introducing and explaining her goals with the study, providing sample lesson plans from the research study and in-course unit, and sharing the research paper with attendees. Then, there will be a time for questioning or assistance in how to implement this in other classroom settings or across curricula. Given that it is a poster session where attendees will be circulating and going to different posters, the introduction and background will be brief, with a larger focus being on the goals of the study and what implementation looked like in the course of the unit, and time for questions by attendees for the last few minutes. A pamphlet or handout will be provided to any attendees or people who walk by.

Outcomes

Attendees will learn about the presenter's research on teaching ethical AI usage. During this presentation, participants will engage in an interactive discussion on integrating ethical AI usage into secondary education, specifically through social studies instruction. The session will begin with an overview of the study conducted with sixth-grade students. Attendees will have access to student survey data and teacher-facilitated discussions using AI. The intended outcome is for participants to gain insight into how AI ethics instruction impacts students' perceptions and to acquire practical strategies for fostering critical thinking about AI in their own classrooms. Additionally, participants will understand how AI ethics instruction prepares students to be informed, critical-thinking citizens in a democracy where misinformation and ethical technology use are increasingly relevant.

Supporting research

1. Justin, Jenna D. (2025) "Teaching AI Ethics and Skepticism: The Impact of Instruction on Ethical Usage on Students’ Perceptions," Journal of Practitioner Research: Vol. 10 : Iss. 1 , Article 2. Available at: https://digitalcommons.usf.edu/jpr/vol10/iss1/2

2. Adepoju, O. D., Tijani, B., & Karera, S. (2024). Artificial intelligence skepticism in career domains. International Journal for Digital Society, 15(1), 1880–1888.

3. Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431-440.

4. Hopfenbeck, T. N., Zhang, Z., Sun, S. Z., Robertson, P., & McGrane, J. A. (2023). Challenges and opportunities for classroom-based formative assessment and AI: a perspective article. Frontiers in Education, 8.

5. Kim, K., Kwon, K., Ottenbreit-Leftwich, A., Bae, H., & Glazewski, K. (2023). Exploring middle school students’ common naive conceptions of Artificial Intelligence concepts, and the evolution of these ideas. Education and Information Technologies, 28(8), 9827-9854.

6. Lindell, T. L., & Utterberg Modén, M. (2025). Conflicting motives: Challenges of generative AI in education. Learning, Media and Technology, 1–14.

7. Luckin, R. (2025). Nurturing human intelligence in the age of AI: rethinking education for the future. Development and Learning in Organizations: An International Journal, 39(1), 1-4.

8. Mertler, C. A. (2021). Action research as teacher inquiry: A viable strategy for resolving problems of practice. Practical Assessment, Research & Evaluation, 26(1), 19.