This study examines the content of lesson plans created by ChatGPT and Google Gemini, two advanced chatbots, for 7th-grade mathematics, science, literature, and social studies classes. The research uses a qualitative content analysis approach to evaluate the lesson plans generated by these chatbots, focusing on their adherence to learning theories and models. The study analyzes 18 lesson plans to identify patterns and variations in the content produced by both chatbots. Key findings include: - Both chatbots produce lesson plans that closely resemble human-written educational content, including sentence structures, activities, and assessments. - The lesson plans defined teachers as facilitators and offered partially constructive activities, but the technology-integrated activities were limited. - There are differences in the structure and content of the lesson plans, particularly in the activities and assessments. ChatGPT's lesson plans are broader and more systematic, while Gemini's plans are more focused on the main topic and less detailed. - The chatbots' lesson plans align with behaviorist and constructivist learning theories, with ChatGPT incorporating ARCS (Attention, Relevance, Confidence, and Satisfaction) strategies. - The chatbots' lesson plans lack detailed prompts and specific educational approaches, suggesting the need for human supervision to ensure quality and relevance. The study provides practical implications for teachers and educational policymakers, highlighting the potential benefits and challenges of integrating chatbots into lesson planning. Recommendations include educating teachers about chatbot literacy, training users on prompt engineering, and encouraging detailed prompts to generate more aligned lesson plans. The study also suggests further research to explore the use of chatbots in state standards, learning approaches, and grade levels.This study examines the content of lesson plans created by ChatGPT and Google Gemini, two advanced chatbots, for 7th-grade mathematics, science, literature, and social studies classes. The research uses a qualitative content analysis approach to evaluate the lesson plans generated by these chatbots, focusing on their adherence to learning theories and models. The study analyzes 18 lesson plans to identify patterns and variations in the content produced by both chatbots. Key findings include: - Both chatbots produce lesson plans that closely resemble human-written educational content, including sentence structures, activities, and assessments. - The lesson plans defined teachers as facilitators and offered partially constructive activities, but the technology-integrated activities were limited. - There are differences in the structure and content of the lesson plans, particularly in the activities and assessments. ChatGPT's lesson plans are broader and more systematic, while Gemini's plans are more focused on the main topic and less detailed. - The chatbots' lesson plans align with behaviorist and constructivist learning theories, with ChatGPT incorporating ARCS (Attention, Relevance, Confidence, and Satisfaction) strategies. - The chatbots' lesson plans lack detailed prompts and specific educational approaches, suggesting the need for human supervision to ensure quality and relevance. The study provides practical implications for teachers and educational policymakers, highlighting the potential benefits and challenges of integrating chatbots into lesson planning. Recommendations include educating teachers about chatbot literacy, training users on prompt engineering, and encouraging detailed prompts to generate more aligned lesson plans. The study also suggests further research to explore the use of chatbots in state standards, learning approaches, and grade levels.