Investigating Factors Influencing Teachers' Intention to Teach Artificial Intelligence in Schools

Abstract

The present study aimed to investigate the factors influencing teachers' intention to teach artificial intelligence (AI) in schools. This study is applied research in terms of its objective. Given that this study utilizes both library research methods and field methods such as questionnaires, it can be stated that the present study is a descriptive-survey research of the correlational type based on its nature and method. The statistical population of this research comprises all public school teachers in Tehran. Considering the unlimited number of these individuals, 384 teachers were selected as the sample using Cochran's formula. The sampling method in this study is cluster sampling. For gathering information related to the literature review and research background, library methods were used. To collect data to confirm or refute the research hypotheses, field methods were employed. In this study, the validity of the questionnaire was examined through face validity, content validity, convergent validity, shared reliability, and Cronbach's alpha coefficient, all of which were confirmed. The data analysis in this research was conducted at both descriptive and inferential levels. The examination and testing of the research hypotheses were carried out using structural equation modeling and SmartPLS software. The results indicated that AI anxiety, perceived usefulness, student readiness, and attitude are factors influencing teachers' behavioral intention to teach AI. The findings showed that all these factors could impact the formation of teaching intention among teachers. Overcoming the challenges can be achieved through specialized training, technical assistance, encouragement and support for teachers, and creating a safe environment for experimentation and learning from mistakes. These efforts can help teachers gain the confidence and skills necessary to teach technology to their students.