Beyond the Prompt

Aligning AI Lesson Plan Tools with Educational Values

MONITORING AI IN EDUCATION

How to cite this learning scenario

Arantes, J. (2025). Aligning AI Tools with Educational Values. www.AI4education.org. Licensed under a Creative Commons Attribution 4.0 International License.
abstract
This case study explores the tension between efficiency-driven AI educational tools and the deeper pedagogical values that underpin contemporary teaching—particularly student agency and classroom dialogue. Drawing on Chen et al. (2025), the scenario positions educators in a decision-making role where they must evaluate AI-generated lesson plans for alignment with school values. Participants engage in analysis, reflection, and redesign activities that foster ethical, values-led adoption of educational AI, supporting critical digital pedagogy. The case is designed for use in teacher education, educational leadership programs, and professional learning contexts to prompt consideration of governance, design ethics, and pedagogical integrity in AI adoption.

“AI does not just reflect pedagogy—it enacts it. What we automate, we legitimise.” — Inspired by Chen et al. (2025)

Beyond the Prompt

You are a curriculum coordinator at a future-focused middle school known for its commitment to student-led learning, inquiry-based pedagogies, and inclusive classroom dialogue. With rising workload concerns, the school board has introduced a suite of AI-powered lesson planning tools (including GPT-based platforms like MagicSchool and School AI) to support teachers. Initial feedback is positive—teachers save time and appreciate the structured outputs. However, when you review the lesson plans more closely, you notice troubling patterns. Many plans emphasize content recall over critical thinking, limit student voice, and rely heavily on teacher exposition. The AI appears to reinforce outdated models of schooling that prioritize control, compliance, and cognitive outcomes over collaboration, curiosity, and creativity. You are tasked with leading a professional development session to evaluate the pedagogical values embedded in these tools and propose strategies to realign AI use with the school's ethos. Your challenge is to ensure these technologies serve, rather than shape, your community’s educational vision. As you prepare, you explore the findings from Chen et al. (2025), which document how popular lesson plan generators often marginalize student agency and dialogue, but also how prompt engineering can reclaim these values. Your task now is to translate these insights into practice—and into policy.
Prompting paper: Chen, B., Cheng, J., Wang, C., & Leung, V. (2025, April 2). Pedagogical Biases in AI-Powered Educational Tools: The Case of Lesson Plan Generators. https://doi.org/10.31219/osf.io/zqjw5_v1

research topics

research questions

What assumptions about teaching and learning are embedded in AI-generated lesson plans? How do tools that prioritize efficiency impact deeper educational goals such as student agency or dialogue? Where do responsibility and accountability lie when AI reproduces outdated pedagogical models? What strategies can educators use to steer AI toward better pedagogical alignment? How should schools govern the use of AI tools to ensure they reflect institutional values?
Critically assess AI-generated lesson plans for implicit pedagogical values and biases. Define the dimensions of student agency and classroom dialogue using established frameworks. Design alternative prompts or review protocols to better align AI outputs with educational goals. Reflect on the ethical and professional responsibilities of educators in evaluating and adapting AI tools.

data collection

Bias Mapping Workshop (1.2, 2.1, 3.6, 5.4) Participants are given sample AI-generated lesson plans from MagicSchool or ChatGPT. Identify which elements are over- or under-represented in the lesson plans, and which theory underpins their development, then share findings. Prompt Re-engineering Challenge (2.6, 3.3, 3.4, 6.3) Using the same original prompt (e.g., “Create a lesson plan on the water cycle for Year 8”), participants craft new prompts that intentionally embed values such as collaboration, inquiry, and student choice. They compare the results and analyze how small changes affect AI outputs. Role-Play: The Ethics Panel (4.1, 6.3, 7.1, 7.4) Participants role-play as different stakeholders (principal, parent, student, AI developer, teacher union rep) debating whether the AI tool should be scaled up or redesigned. This activity helps surface tensions between innovation, equity, and educational philosophy. Design a Policy Brief (6.4, 7.2, 7.3, 7.4) In groups, participants write a short policy memo with guidelines for AI use in lesson planning. This includes criteria for pedagogical alignment, teacher training needs, and example prompts to include in staff AI literacy guides.

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Acknowledgement of CountryWe acknowledge the Ancestors, Elders, and families of the Kulin Nation, who are the Traditional Owners of the land where this work has been predominantly completed. As we share our own knowledge practices, we pay respect to the deep knowledge embedded within the Aboriginal community and recognise their custodianship of Country. We acknowledge that the land on which we meet, learn, and share knowledge is a place of age-old ceremonies of celebration, initiation, and renewal, and that the Traditional Owners’ living culture and practices continue to have a unique role in the life of this region.
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