Article Abstract index5

The study was carried out to explain the role of Artificial Intelligence Technologies in the field of education and their impact on improving the role of the teacher and ensuring quality education. Because the use of these can be a precondition for their use, the study investigated the role of such factors in decisions to adopt and opened up predictors for teachers\' readiness to accept the use of AI-supported educational technologies. The study followed the technology acceptance model as its theoretical framework and identified the independent variables considered in the study: knowledge about AI, Digital Competence, Organizational Support, AI Training, perceived usefulness, and ease of use. The study used quantitative research method because it aimed to obtain the statistical data to gain better understanding of the problem of the study. In particular, the researchers investigated the factors predicting teacher readiness in this regard using secondary data obtained from the school teachers. The number of respondents to the study research questions was 250 who were sampled from both private and public institutions. The data properties were examined in the initial stages by descriptive statistics and reliability analysis to see if the basic properties of the data were present and if the research instrument was reliable. This was done through the use of Statistical Package for Social Sciences (SPSS). This study then went on to carry out a Pearson’s correlation and regression analysis to draw out a predictive relationship between the independent variables and the dependent variable. The study found that all the independent variables were significantly and positively related with the dependent variable. The analysis, however, showed the relative effect of each of the independent variables. Indeed, although all the factors had positive influences, perceived usefulness proved to be more strongly related with the inclination of school teachers to adopt AI-based learning technologies than the other factors. The research report offers several original aspects of the phenomenon studied, thus introducing new information into the existing knowledge about the phenomenon. In this context, the theoretical framework used in most studies on factors influencing teachers\' willingness to adopt technologies in education is TAM, which gave impetus to the study, although it is not the only one that identified other variables that significantly predicted teachers\' readiness to use artificial intelligence technologies. Secondly, the study gives another theoretical basis to study this area, which can be used in a similar study as another theoretical framework on top of TAM. Thirdly, the research paper gives the feasibility of the study as per the benefits to be obtained from the study findings. For instance, it could support educational policymakers and administrators to identify strategies for boosting teachers\' readiness to adopt AI, such as expanding their knowledge of AI to further support their digital competence. Finally, the findings of the study will help to support the effective use of AI in the field of education with empirical evidence to improve readiness to use the technologies.
Keywords: Artificial Intelligence (AI), Teachers\' Readiness, AI Integration, Digital Competency, Technology Acceptance Model (TAM), Perceived Usefulness, Educational Technology, Institutional Support.