Pre-service science teachers’ anxiety levels about artificial intelligence applications

The objective of this study is to ascertain the levels of anxiety experienced by pre-service science teachers in relation to the utilization of artificial intelligence applications. A mixed research method was employed in the study. One of the mixed research method designs, the sequential explanatory design, was employed in the study. In the quantitative section of the study, a survey design was employed, while a case study design was utilized in the qualitative component. The population of the quantitative component, which constitutes the participants of the study, consists of 208 pre-service teachers enrolled in the science department of the faculty of education at a state university. The study sample consisted of 162 pre-service science teachers. The sample was selected through the use of simple random sampling. In the qualitative component of the study, eight prospective science educators, selected for their maximum diversity, were the subjects of investigation. In the course of data collection for the study, the scale was administered to 162 pre-service science teachers. Subsequently, semi-structured interviews were conducted with eight pre-service science teachers. In the data analysis phase of the study, quantitative and qualitative data were analyzed separately. Descriptive statistics and inferential statistics were employed to analyze the quantitative data, while content analysis was utilized to analyze the qualitative data. The findings revealed that the level of artificial intelligence anxiety among the pre-service science teachers was moderate, as indicated by the scale administered to this group. The interviews revealed that pre-service teachers with high and low levels of artificial intelligence anxiety had similar responses. Both groups agreed that artificial intelligence cannot replace the teaching profession. Based on these findings, the research team proposed two recommendations: first, to provide pre-service teachers with the necessary training on artificial intelligence, and second, to offer an artificial intelligence course to all pre-service teachers.