Examining the relationship between teachers' individual innovativeness levels and their attitudes towards artificial intelligence

This study examines the relationship between teachers' individual innovativeness levels and their attitudes towards artificial intelligence. The research aims to reveal the relationship between these two variables by analyzing teachers' individual innovativeness and their attitudes towards artificial intelligence. In this study, a convergent parallel mixed method, in which quantitative and qualitative research methods are used together, is adopted. The quantitative part of the research is designed with relational survey model and the qualitative part is designed with phenomenology. The study groups of the research consist of 550 volunteer teachers working in public schools in Edirne province center and districts, which were determined by random sampling technique in the quantitative research design. The qualitative research design consists of 22 teachers who include various demographic characteristics and voluntarily participated according to maximum diversity sampling, one of the purposeful sampling methods. Quantitative data were collected using the " General Attitudes to Artificial Intelligence Scale" and " Individual Innovativeness". Qualitative data were collected using a semi-structured interview form prepared by the researcher. Descriptive statistics, independent groups t-test, ANOVA tests, Pearson product-moment correlation and multiple regression analysis were used to analyze the quantitative data. In the analysis of qualitative viii data, the data were evaluated with descriptive analysis technique. The data were categorized according to the thematic framework structured around 4 main themes and 11 sub-themes. Within the scope of the findings obtained from the research, when the analysis of the sub-dimensions of teachers' individual innovativeness traits is considered, it is determined that the highest average is in the "Openness to Experience" factor and the lowest average is in the "Risk Taking" factor. According to the findings obtained within the scope of the analysis of individual innovativeness categories, it was seen that most of the teachers were in the "Early Majority" category, followed by "Early Adopter", "Innovator", "Late Majority" and "Laggards" categories respectively. In the study, it was seen that teachers' attitudes towards artificial intelligence were affected by demographic factors. While it was determined that variables such as gender, branch, education level and school level made a significant difference on teachers' attitudes towards artificial intelligence, no significant difference was found in terms of professional seniority variable. Within the scope of the findings obtained in the study, it was also seen that male teachers had higher positive attitudes towards artificial intelligence and that secondary school teachers had more positive attitudes towards artificial intelligence than primary school teachers and teachers with postgraduate education had more positive attitudes than teachers with undergraduate education. When the relationship between teachers' individual innovativeness categories and their attitudes towards artificial intelligence was examined, it was found that there was a significant relationship between individual innovativeness categories and positive and negative attitudes towards artificial intelligence. Innovators teachers' positive attitude scores towards artificial intelligence were higher than other teacher groups (early adopters, early majority, late majority). The negative attitudes of innovator teachers were significantly lower than the other groups. According to the results of the research, teachers' positive attitudes towards artificial intelligence show significant differences according to their individual innovativeness levels. High level innovative teachers have more positive attitudes towards artificial intelligence than medium and low level innovative teachers. In addition, teachers' negative attitudes towards artificial intelligence also differ depending on the level of individual innovativeness. ix The negative attitudes of high level innovative teachers are lower than low level innovative teachers. However, the effect size for both attitudes is low. The general findings of the study reveal that teachers' positive attitudes towards artificial intelligence show a significant relationship with their individual innovativeness levels. This result shows that teachers, as individuals who exhibit an innovative and open attitude towards development, tend to have a more positive attitude towards artificial intelligence.