Teaching – Instructional Materials

Takeaways

• AI-powered tools, particularly Large Language Models (LLMs), can significantly reduce teacher workload by automating time-intensive tasks such as generating practice problems, lesson plans, and assessments, with studies showing up to 4.67 times less time spent compared to manual creation by teaching assistants (Ma et al. (2024)).
• Teachers using AI to create differentiated materials report substantial productivity gains when they leverage AI not just for content creation but also to seek input on teaching strategies and approaches for diverse learners (Keppler et al. (2024), Ma et al. (2024)).
• Best practices for AI-assisted content creation include using a human-in-the-loop approach where educators review, edit, and refine AI-generated materials to ensure accuracy, relevance, and alignment with instructional goals (Caines et al. (2023), Bulut et al. (2024)).
• AI tools can enhance accessibility by providing multilingual content adaptation, supporting indigenous languages, and offering alternative explanations tailored to students with different language backgrounds or learning disabilities (Mogavi et al. (2023), Jin et al. (2024), Elstad & Eriksen (2024)).
• AI-generated educational content using Retrieval Augmented Generation (RAG) techniques demonstrates significantly higher accuracy (up to 92% compared to 67% without RAG) by grounding responses in verified educational materials and curriculum standards (Clark et al. (2025), Kloker et al. (2024)).