Transformation STEM Education in The Age of Artificial Intelligence: Generative Technologies, Adaptive Learning, Digital Assessment and New STEM Competencies
Abstract
The rapid development of artificial intelligence (AI), generative models, adaptive educational systems, and digital assessment tools has begun to significantly change the content and organization of STEM education. While previously the key issue was the creation of interdisciplinary STEM tasks integrating natural sciences, technology, engineering, and mathematics, the current era is characterized by a transition to intelligently supported and personalized educational environments.
The purpose of this analytical review is to identify the main areas of transformation in STEM education under the influence of artificial intelligence and to define new requirements for the educational process and STEM competencies. This review analyzes scientific publications on the use of AI in science teaching, generative AI in STEM, personalized and adaptive learning, intelligent tutoring systems, digital assessment, and the development of teacher and student competencies. It demonstrates that AI can enhance personalization, provide dynamic feedback, and support modeling and complex problem solving. However, the educational impact depends significantly on instructional design.
Recent meta-analytic data confirm the positive effects of AI-supported instruction and GenAI, but also demonstrate high heterogeneity in the results. The changing nature of assessment is particularly significant: traditional checking of the final answer is no longer sufficient, as generative models are capable of independently generating texts, program code, mathematical solutions, and explanations. The need for a shift to assessing the process of reasoning, design, verification, critical evaluation of AI results, and the student's ability to meaningfully use AI is substantiated. A conclusion is drawn regarding the emergence of a new model of STEM education, in which artificial intelligence is not a substitute for teachers or students, but an intelligent tool for collaborative problem solving, and AI literacy, critical thinking, verification, data management, and the ethical use of technology become integral elements of modern STEM competence.
The scientific novelty of this review lies in its approach to the transformation of STEM education, which is not viewed as a standalone implementation of AI technologies, but rather as a change in the entire architecture of STEM activities—from task setting and personalization of learning to assessment and competency structure. The article proposes a conceptual model of Human-AI Integrated STEM, in which artificial intelligence is not a substitute for students or teachers, but an intellectual component of interdisciplinary problem solving. It is further substantiated that, in today's environment, independent verification, validation, and critical assessment of AI results should be considered independent components of a new STEM competency.
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References
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