A Self-Efficacy Theory-based Study on the Teachers Readiness to Teach Artificial Intelligence in Public Schools in Sri Lanka
This addresses the problem of teacher preparedness for AI education in Sri Lankan public schools, which is incremental as it applies an existing theory to a new context.
The study investigated Sri Lankan ICT teachers' readiness to teach AI in schools, finding that their self-efficacy was low, primarily influenced by emotional and physiological states, with mastery experiences having a lesser impact and other factors showing no significant effect.
This study investigates Sri Lankan ICT teachers' readiness to teach AI in schools, focusing on self-efficacy. A survey of over 1,300 teachers assessed their self-efficacy using a scale developed based on Bandura's theory. PLS-SEM analysis revealed that teachers' self-efficacy was low, primarily influenced by emotional and physiological states and imaginary experiences related to AI instruction. Mastery experiences had a lesser impact, and vicarious experiences and verbal persuasion showed no significant effect. The study highlights the need for a systemic approach to teacher professional development, considering the limitations in teachers' AI expertise and social capital. Further research is recommended to explore a socio-technical systems perspective for effective AI teacher training.