Comparing Accuracy, Language, and Pedagogy in AI-Generated Exponential Equation Solutions
DOI:
https://doi.org/10.17509/j-mer.v7i1.959Keywords:
ChatGPT, MathGPT, DeepSeek, Gemini, Generative AI, Exponential EquationAbstract
The growth of generative AI has transformed how mathematics is learned by providing instant solutions to a wide range of problems. This study evaluates four popular AI models, namely MathGPT, ChatGPT, DeepSeek, and Gemini AI, on three exponential equation problems. The assessment is based on three aspects: accuracy, language, and pedagogy. Accuracy ensures the answers are correct, consistent, and directly verified. Language assesses the narrative style in procedural steps, the use of appropriate notation, and the use of formal terminology. Pedagogy examines the scaffolding components, how they are communicated, and their suitability for different types of learners. The results show that all four AI models can provide correct answers, although their explanations vary. DeepSeek explains in detail. MathGPT excels at using formal notation and terminology; ChatGPT offers concise solutions with step-by-step guidance, while Gemini AI constructs intelligent narrative scaffolding. These findings indicate that AI answer quality depends not only on correctness but also on how the explanations are delivered and their suitability for learners' needs. Educators and developers can leverage each AI's strengths to create more adaptive and targeted learning tools.
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