Integrating generative artificial intelligence in the design of scientific inquiry for middle school students
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GenAI is employed to support student engagement with challenging topics such as quantum theory, interdisciplinary knowledge transfer, and experimental design and hypothesis formulation.
“GenAI is employed to address these goals by supporting student engagement with challenging topics such as quantum theory, interdisciplinary knowledge transfer, and experimental design and hypothesis formulation-areas often limited by insufficient teacher resources and the lack of personalized instruction [91-94].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [93]
AI provides strong scaffolds for core practices, markedly improving the quality and conventionality of learner outputs-for example, enhancing grammatical accuracy and argumentative coherence in writing, and supporting problem-solving and experimental design in science and mathematics-thereby helping learners meet baseline practice demands more efficiently.
“First, AI provides strong scaffolds for core practices, markedly improving the quality and conventionality of learner outputs-for example, enhancing grammatical accuracy and argumentative coherence in writing [86,87,145], and supporting problem-solving and experimental design in science and mathematics [77,88,93,103,147]-thereby helping learners meet baseline practice demands more efficiently.”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [93]
Some studies document confusion, frustration, and other negative emotions driven by mistrust, technical limits, or unmet expectations, and even declines in self-efficacy.
“Some studies document confusion, frustration, and other negative emotions driven by mistrust, technical limits, or unmet expectations [78,87,93,98], and even declines in self-efficacy [140].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [93]
Analyzing student traces with GenAI systems is not new, especially for research purposes.
“Analyzing the student traces with GenAI systems is not something new, especially for research purposes (e.g., [1,12]).”
From GenAI Analytics and Pedagogical Configurations: Featuring New Generative AI Systems in Education (2026) · cites this paper as [12]
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Lin, X., & Tan, H. (2025) · Systems · doi:10.3390/systems13100840 · Cited by 22 · see citing works
GenAI Analytics and Pedagogical Configurations: Featuring New Generative AI Systems in Education
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- Authors
- Min, T., Lee, B., & Jho, H.
- Affiliations
- Dankook University (KR)
- Corresponding author
- Lee, Bongwoo
- Venue
- Education and Information Technologies
- Published
- 2025-02-10
- Volume
- 30
- Issue
- 11
- Pages
- 15329-15360
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4407342213
- Cited by
- 26
- References
- 57
- Citations by year
- 2026: 20 · 2025: 6
- FWCI
- 27.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Education and Information Technologies (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Education › Science Education and Pedagogy
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- generative AI, scientific inquiry, junior high school students, physics experiments, open-ended experiments, student-AI interaction, AI assistants, student perceptions of AI, experimental design, high school science education
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