Using artificial intelligence in the process of forming a teacher's deviantological competences

Abstract

The study examined the use of artificial intelligence (AI) to form teachers' deviantological competence. The primary objective of the study is to determine the effectiveness of the competency-based approach in preparing teachers for interaction with children with deviant behavior. The study adopted a mixed-methods research design. The purposive sampling technique was used to sample 100 educators from two different schools. It was an experimental study; 50 teachers in the experimental group participated in the training program while 50 teachers in the control group received no additional training.  The six-week program consisted of training, simulations, cases, mentoring, and the use of AI platforms (simulators, chatbots, adaptive systems, behavioral analytics tools, and gaming services). Data were collected using questionnaires, tests, and competency scales. Analysis of the results (t-test, MANOVA, correlation and regression analysis) revealed a significant increase in the level of professional readiness of teachers in the experimental group in the areas of knowledge, skills, and practices (p < 0.05), while changes in attitudes were insignificant. The program effectively improved teachers' readiness levels. Teachers demonstrated improved skills for addressing deviant behaviors, creating a supportive learning environment, and developing empathy. The study, therefore, provides experimental evidence that shows the effectiveness of a competency-based approach in preparing teachers for interaction with children with deviant behaviors.