Date
Publisher
arXiv
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.
Study at a glance
- Question: How confident and prepared are ICT teachers in Sri Lanka to teach artificial intelligence?
- Setting and data: Over 1,300 ICT teachers in public schools in Sri Lanka.
- Method: Teacher survey (PLS-SEM analysis).
Why it matters
Understanding ICT teachers' readiness to teach artificial intelligence in public schools requires examining their self-efficacy. Measuring teacher self-efficacy helps identify whether educators feel prepared to deliver AI instruction.
Key findings
- Across over 1,300 public school ICT teachers in Sri Lanka, educators reported low confidence in their readiness to teach artificial intelligence.
- Teachers' confidence was primarily influenced by their emotional and physical states alongside their imagined experiences with artificial intelligence instruction.
- Prior mastery experiences had little impact on confidence, while observing others and verbal encouragement showed no significant effect.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
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