Determination of prospective science teachers' views on artificial intelligence applications

This study aims to examine pre-service science teachers' attitudes and opinions towards artificial intelligence (AI) applications. The main purpose of the study is to understand pre-service science teachers' attitudes towards AI technologies and to determine how these attitudes differ according to gender, grade level and region variables. Mixed method was used in the study. Quantitative data were collected with the Artificial Intelligence Applications Attitude Scale (AIAAS) administered to 245 pre-service science teachers. Qualitative data were obtained through the answers given to 10 semi-structured interview questions directed to pre-service science teachers. The participants were randomly selected from 7 different regions of Türkiye. The AIAAS used for quantitative data is a 5-point Likert-type scale consisting of 20 items. Qualitative data were collected by analyzing the responses to the interview questions into themes, sub-themes and categories. The interview questions covered topics such as potential benefits of AI applications in education, effects on teacher roles, level of competence, ethical concerns, and integration plans. The quantitative data were analyzed using descriptive statistics and inferential statistics. Independent samples t-test and one-way ANOVA were used to determine significant differences according to gender, grade level and region variables. Qualitative data were analyzed into themes, sub-themes and categories using content analysis. The results of the study show that pre-service teachers have a positive attitude towards AI technologies in general. However, significant differences were found according to gender, grade level and region variables. While female participants had more positive attitudes than male participants, 3rd grade students had more positive attitudes than other grade levels. Participants in the Black Sea region showed the most positive attitude towards AI applications. In line with these results, it is recommended that education programs should be restructured in a way to increase pre-service teachers' knowledge and competencies in AI technologies. It is also important to ensure equal access and support to reduce regional differences. It is emphasized that educational strategies should be differentiated according to gender and grade level to improve pre-service teachers' attitudes towards AI technologies.