Embedding Generative AI into Systems Analysis and Design Curriculum: Framework, Case Study, and Cross-Campus Empirical Evidence

Most students can learn critical judgment about AI, but need structured training: 84% of the 18 student groups across four Australian universities moved beyond passively accepting AI suggestions, demonstrating that with proper pedagogy like SAGE (Structured AI-Guided Education), students can develop selective judgment about when to accept, modify, or reject AI contributions.

There are significant blind spots even among trained students: Despite training, 55% of groups failed to identify when AI misclassified system boundaries, 45% missed data management errors, and 55% overlooked missing exception handling—suggesting that critical thinking about AI has limits and students need additional support identifying technical gaps that both humans and AI miss.

Domain expertise and communication skills matter for responsible AI use: Students with deep domain understanding consistently considered accessibility considerations, and those strong at explaining their decisions also performed well at integrating multiple sources, indicating that responsible AI orchestration depends on foundational knowledge and reasoning skills beyond AI literacy alone.

Accessibility awareness is fragile and requires ongoing reinforcement: While 85% of groups explicitly considered elderly users and cultural needs when writing requirements, the paper notes that "accessibility awareness proved fragile," suggesting that responsible AI practices around inclusive design need continuous emphasis rather than one-time instruction.