Science and Artificial Intelligence Tools: Opportunities, Evidence, and Responsible Integration
DOI:
https://doi.org/10.65336/WJMS.2026.3904Keywords:
Artificial intelligence, generative AI, science education, STEM, scientific research, machine learning, geoinformatics, digital pedagogy, academic integrity, AI ethics, personalized learning, and scientific literacy.Abstract
Background: The use of artificial intelligence (AI) tools is on the rise in both scientific research and education. Such tools comprise generative AI systems, automated data-analysis platforms, geospatial technologies, intelligent tutoring systems, digital storytelling applications, scientific visualization tools, machine-learning models, and AI-supported language technologies.
Objective: The review looks at the recent literature concerning the use of AI tools in science and in education related to science, focusing on research support, STEM learning, digital language teaching, geoinformatics, scientific communication, and ethical governance.
Methods: A narrative integrative review was carried out by means of recent peer-reviewed and institutional sources. The evidence was thematically arranged according to the functions of AI, its educational applications, its research applications, the benefits, the risks, and the requirements for implementation.
The evidence shows that AI tools can assist scientific research by means of literature discovery, coding, simulation, data classification, geospatial analysis, visualization, translation, and the provision of automated feedback. In the context of science education, generative AI might enhance conceptual understanding, academic achievement, scientific literacy, motivation, and personalized learning, provided that it is incorporated using carefully designed teaching methods. Yet, performance with AI differs greatly from task to task and can involve the creation of false references, incorrect explanations, biased responses, or plausible yet invalid scientific reasoning.
In conclusion, AI tools ought to be seen as assistants for the purposes of research and learning rather than as independent authorities. Their worth is based on human verification, clear documentation, scientific reasoning, data protection, and both teachers' and researchers' awareness of AI technology, as well as equitable access.
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