Investigating the moderating effects of social good and confidence on teachers' intention to prepare school students for artificial intelligence education

Abstract

Artificial Intelligence (AI) has triggered profound reforms across industries, including education. These developments necessitate the inclusion of AI as a subject in K-12 classrooms. However, the need for students to learn AI demands that educators pay increasing attention, believe in its relevance and intend to promote it among their students and colleagues. This paper aimed to explore teachers' perceptions of and behavioral intention to teach AI. We specifically considered the association of AI anxiety, perceived usefulness, attitude towards AI, AI relevance, AI readiness, and behavioral intention factors. This research further aims to examine the moderator effect of AI for social good and confidence on the relationship in our hypothesized research model. To address this purpose, a quantitative methodology with the use of structural equation modeling was utilized. Data were retrieved through an online questionnaire from 320 lower and upper secondary school in-service teachers, mostly in STEM-related fields. Our findings reveal that teacher perceptions of AI for social good and confidence will affect most relationships in the model. Teacher professional programs should include the benefits and risks of AI and good practice sharing.