Exploring the Scientific Validity of ChatGPT’s Responses in Elementary Science for Sustainable Education

As AI integration in education increases, it is crucial to evaluate its effectiveness in elementary science learning, particularly in promoting sustainable education through equitable access to knowledge. This study aims to assess the validity and applicability of ChatGPT3.5 (free version) responses in elementary Earth and Space science. A document analysis of 1200 AI-generated responses was conducted to evaluate scientific validity, explanatory clarity, and pedagogical relevance. The analysis employed quantitative methods to assess accuracy and alignment with elementary curricula, while qualitative insights identified linguistic and conceptual challenges. The findings indicate that 94.2% of responses were scientifically valid, 70.6% were clear, but only 12.8% aligned with elementary curricula. While ChatGPT provides accurate information, many responses included complex terminology unsuitable for young learners. Additionally, 87.2% of responses lacked alignment with curricula, posing challenges for effective classroom integration. Despite these limitations, ChatGPT shows potential in simplifying scientific concepts and expanding access to educational resources. Refining AI-generated content through curriculum-based filtering, adaptive language processing, and teacher mediation is necessary. Strengthening AI-driven educational strategies with a sustainability focus can ensure long-term improvements in equitable science learning. This study highlights the need for further research on optimizing AI tools for elementary education.

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Publication Details

Journal
Sustainability
Published
2025-03-27
DOI
https://doi.org/10.3390/su17072962
Citations
5
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.27
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article

Exploring the Scientific Validity of ChatGPT’s Responses in Elementary Science for Sustainable Education

Yoonsung Choi
5 citations
Sustainability
Artificial Intelligence in Healthcare and Education
3.27
article

Exploring the Scientific Validity of ChatGPT’s Responses in Elementary Science for Sustainable Education

Yoonsung Choi
article en
5 citations

Abstract

As AI integration in education increases, it is crucial to evaluate its effectiveness in elementary science learning, particularly in promoting sustainable education through equitable access to knowledge. This study aims to assess the validity and applicability of ChatGPT3.5 (free version) responses in elementary Earth and Space science. A document analysis of 1200 AI-generated responses was conducted to evaluate scientific validity, explanatory clarity, and pedagogical relevance. The analysis employed quantitative methods to assess accuracy and alignment with elementary curricula, while qualitative insights identified linguistic and conceptual challenges. The findings indicate that 94.2% of responses were scientifically valid, 70.6% were clear, but only 12.8% aligned with elementary curricula. While ChatGPT provides accurate information, many responses included complex terminology unsuitable for young learners. Additionally, 87.2% of responses lacked alignment with curricula, posing challenges for effective classroom integration. Despite these limitations, ChatGPT shows potential in simplifying scientific concepts and expanding access to educational resources. Refining AI-generated content through curriculum-based filtering, adaptive language processing, and teacher mediation is necessary. Strengthening AI-driven educational strategies with a sustainability focus can ensure long-term improvements in equitable science learning. This study highlights the need for further research on optimizing AI tools for elementary education.

SustainabilityVol. 17(7)
Cheongju National University of Education (KR)
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
3.27
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Exploring the Scientific Validity of ChatGPT’s Responses in Elementary Science for Sustainable Education — Yoonsung Choi · Sustainability (2025) | TGRS Research Map | TGRS