An experimental evaluation of the effectiveness of integrating elements of medical physics into the school curriculum using artificial intelligence tools

Abstract

This article experimentally assessed the effectiveness of integrating elements of medical physics into school physics using artificial intelligence (AI) tools. The relevance of the study stems from the need to strengthen the role of physics in the career guidance of high school students in Kazakhstan and the lack of systematic introduction of the physical principles of medical devices and diagnostic methods into the subject. The study was conducted using a quasi-experimental design: a control group (without the use of AI, n=51) and an experimental group (with the use of AI, n=52). The educational intervention was delivered through the "Electromagnetic Field and Elements of Medical Physics" module, consisting of four topics: (i) properties of the electromagnetic field, (ii) physical principles of the magnetic field and MRI, (iii) physical principles of electromagnetic radiation and X-ray/CT, (iv) principles of tomography and ionizing/non-ionizing methods. The results were assessed using a questionnaire consisting of 12 statements on a Likert scale (1–5). According to the main results, the overall index was 4.26±0.23 in the experimental group and 2.54±0.16 in the control group, and the difference between the groups was statistically significant (p<0.001). A consistent advantage was also observed across all sections (all p<0.001), with the largest difference recorded in Section IV. In an internal analysis for grades 10 and 11, the advantage of the experimental group was maintained. In a practical sense, a high index (4–5 points) prevailed in the experimental group, indicating a level of “confident understanding,” and it was proven that the ability of AI to visualize, individually explain, model, and provide immediate feedback on elements of medical physics improves the assimilation of complex concepts.