Civic education in the age of AI: Should we trust AI-generated lesson plans

Synthesis: An analysis of 310 AI-generated lesson plans (2,230 individual activities) produced by ChatGPT (GPT-4o), Gemini (1.5 Flash), and Copilot (GPT-4 based) for all 53 Massachusetts eighth-grade civics standards. Each standard received two prompts: a basic "write a lesson plan" and a "highly interactive" variant.

Large-scale empirical evaluation of AI-generated civics lesson plans reveals that without teacher revision, AI tools overwhelmingly produce lower-order thinking activities and monocultural content — fundamentally at odds with the goals of civic education.

The Study

Trust et al. (2025) analyzed 310 AI-generated lesson plans (2,230 individual activities) produced by ChatGPT (GPT-4o), Gemini (1.5 Flash), and Copilot (GPT-4 based) for all 53 Massachusetts eighth-grade civics standards. Each standard received two prompts: a basic "write a lesson plan" and a "highly interactive" variant.

Key Findings

Lower-Order Thinking Dominates

Using Bloom's Revised Taxonomy:

90% of activities demanded only recall, comprehension, or simple application. Activities like "write definitions," "list three facts," and "answer comprehension questions" were pervasive. Even prompting for "highly interactive" lessons made minimal difference.

Near-Total Absence of Multicultural Content

Using Banks' Four Levels of Integration of Multicultural Content:

• 94% of activities contained no discernible multicultural content (2,086 of 2,230).
• Of those that did, 137 were at the lowest "Additive" level (mentioning diverse figures without restructuring curriculum) and four reached the "Contributions" level.
• Only 1 activity reached "Transformation" (restructuring the curriculum to include diverse perspectives).
• Zero activities reached "Social Action" (empowering students to address social issues).

This is especially damning for civic education, where multicultural perspectives and critical engagement with power structures are essential learning goals.

Formulaic Outputs Across All Chatbots

All three chatbots produced structurally identical lesson plans: Introduction → Activities 1-4 → Conclusion → Assessment → Extension → Homework. This factory-line format was applied regardless of whether the standard addressed constitutional principles, civil rights, or local government — homogenization that strips away the disciplinary texture of civic education.

Open Questions

• Would fine-tuned educational LLMs (e.g., EduQwen) produce more cognitively demanding and multiculturally-aware lesson plans?
• How do these findings generalize to other subjects (math, science, language arts)?
• Can better prompt engineering (e.g., explicitly requesting higher-order thinking and multicultural integration) close the gap?
• What does the teacher revision process look like in practice — do teachers have the time and training to meaningfully redesign AI outputs?

What this means for practice

• Instructors. Audit the cognitive demand of any AI-generated plan before teaching it: 90% of the 2,230 activities produced across the 310 lesson plans sat at Remember, Understand, or Apply, with Analyze at 4% and Evaluate at 2%.
• Instructors. Rebuild for multicultural content rather than decorating an existing plan: 94% of activities (2,086 of 2,230) received no Banks code, 137 of the activities that received a Banks code stayed at the Additive level, four reached Contributions, one reached Transformation, and none reached Social Action.
• Instructors. Do not assume a better prompt closes the gap — the "highly interactive" prompt variant made minimal difference, and all three chatbots returned the same Introduction → Activities 1-4 → Conclusion → Assessment → Extension → Homework structure whatever the standard covered.
• Instructors. Treat the pattern of lower-order thinking bias as required AI literacy content: teachers need to recognize it, inject analysis, evaluation, and creation activities, and add the perspectives the model omits before teaching the plan.
• Administrators. Require disciplinary review before AI-generated plans enter a civics curriculum: even standards that explicitly named civil rights, Native American influences, or equality were handled at only the Additive level, and civic education depends on critical thinking about power and justice that the default outputs suppress.

Limitations

• The corpus covers one state and one grade level: 53 Massachusetts eighth-grade civics standards, so the pattern of lower-order and monocultural output is documented for a single disciplinary and jurisdictional context.
• Only three chatbots (ChatGPT, Gemini, and Copilot) and two prompt variants were tested, generated in a single round in August 2024, so the study cannot say whether newer models, fine-tuned educational models, or more explicit prompting would produce different plans.
• Coding applied Bloom's Revised Taxonomy and Banks' four levels to plan documents, which records what a plan asks students to do rather than what students learned or how teachers actually revised the plans.
• The study stops at the output: it provides no evidence about whether teachers have the time or training to redesign the plans it critiques, which is the step its own recommendation depends on.

Citation

Trust, T., Maloy, R., Xu, C., & Pelletier, K. (2025). Civic education in the age of AI: Should we trust AI-generated lesson plans. Contemporary Issues in Technology and Teacher Education