Adapting to Educate: Conversational AI's Role in Mathematics Education Across Different Educational Contexts

This paper examines how conversational AI (LLM-based tools) supports K-12 mathematics educators during lesson preparation by analyzing educator-AI dialogues to assess AI's responsiveness to different educational contexts and instructional needs. Through qualitative content analysis, the study evaluates whether AI can accurately adapt responses to varied educational settings and provide actionable pedagogical guidance.

As educational settings increasingly integrate artificial intelligence (AI), understanding how AI tools identify -- and adapt their responses to -- varied educational contexts becomes paramount. This study examines conversational AI's effectiveness in supporting K-12 mathematics education across various educational contexts. Through qualitative content analysis, we identify educational contexts and key instructional needs present in educator prompts and assess AI's responsiveness. Our findings i

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