Innovative Artificial Intelligence-Based Technologies in Teaching Natural Sciences

Abstract

The article provides a theoretical and analytical review of how the latest developments based on artificial intelligence (AI) complement the methodological tools of a natural science teacher. Two facts testify to the relevance of the topic: generative and adaptive AI services have already firmly established themselves in the daily activities of educational institutions, while natural science subjects by their nature require visual representation, orientation to the individual needs of each student and the development of researcher skills in them – and classical methods do not achieve this to a full extent. Having processed an array of publications for 2023–2026, the author divided the educational capabilities of AI into four content blocks: adaptation of the educational process to an individual student, construction of digital visualization (simulations and virtual), generation and explanation of material for learning, and automatic grading together with analytics of the learning process. When the established work model was compared with the one enhanced by AI, according to several didactic features, the following became clear: the technology works most effectively in situations where the individual speed of assimilation, instant response to the student's actions, and visual disclosure of processes difficult to imagine come to the fore. A functional model of involving AI in science education was formed; its core is a methodically balanced choice of a tool in accordance with the specific goal of the lesson, rather than resorting to technology simply for the sake of its availability. Varieties of AI applications are systematized and supported by illustrations from biology, chemistry, physics, geography, and astronomy. The risks are separately highlighted – starting from the weakening of the ability to think independently and ending with factual errors inherent in generative systems – and ways to minimize them are also outlined. It is emphasized that the key to the result remains the digital awareness of the teacher himself. The acquired knowledge is fully available for direct implementation in designing lessons, developing professional development programs for teachers, and developing the educational institution's policy regarding the conscientious handling of AI.