In the modern digital ecosystem, information security requirements are becoming increasingly complex, placing new demands on the professional preparation of future informatics teachers. The purpose of this study is to identify the pedagogical, methodological, and technological possibilities for integrating machine learning into the development and enhancement of information security skills. The research analyzes the use of ML methods in the educational process, including automatic threat detection, data classification, anomaly identification, and behavioral risk prediction. Additionally, a model is proposed to develop students’ practical competencies through smart devices and digital learning platforms. The findings demonstrate that integrating machine learning into the educational process significantly strengthens future informatics teachers’ professional competencies in information security, enabling a systematic understanding of threats and the development of effective prevention strategies.
Tleumagambetova et al. (Tue,) studied this question.