arXiv:2606.14718v1 Announce Type: cross Abstract: As Artificial Intelligence (AI) literacy initiatives expand in K-12 settings, understanding how gender shapes student baseline perceptions, tool-use, and responsiveness to interventions is essential for equitable curriculum design. This study examines gender differences in AI literacy, safety awareness, and STEM career aspirations among Australian secondary students (Years 7, 8, and 10; N(pre) = 199, n(post) = 136) from two co-educational government schools who participated in a one-day AI literacy workshop. Using statistical regression methods
As AI integration continues across society, understanding fundamental human factors like gender in AI literacy and engagement, especially regarding emerging threats like deepfakes, becomes increasingly critical.
This research provides actionable insights for educators, policymakers, and AI developers to design more equitable and effective AI literacy programs, addressing potential biases and optimizing engagement.
The study highlights observed gender-based differences in AI perceptions and deepfake engagement, suggesting a need for tailored educational approaches to ensure broad and balanced AI literacy across demographics.
- · AI curriculum developers
- · K-12 educators
- · Students in STEM
- · AI ethicists
- · One-size-fits-all AI education approaches
- · AI systems with unaddressed biases
More refined AI literacy curricula will be developed, incorporating gender-sensitive teaching strategies.
Improved AI education could lead to a more diverse talent pipeline in AI development, potentially reducing algorithmic bias in future systems.
Enhanced public understanding of AI's societal implications, including deepfakes, could foster greater trust and more informed regulation of AI technologies.
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Read at arXiv cs.AI