The Evidence Base

The AI in Education Strategy is grounded in a growing body of evidence on how generative AI is reshaping learning and professional practice.

Students benefit from deliberate guidance on AI use

Generative AI is already part of how students study. In Singapore, recent findings show widespread student use of AI for learning-related tasks, and local higher education research points to disciplinary differences in how students understand and engage with generative AI. _1,2 This makes it important for programmes to guide AI use deliberately, rather than leaving students to navigate appropriate practice on their own.
 

Core competencies require protected space

Students need opportunities to build disciplinary knowledge and practise core skills without AI assistance. Without this foundation, they may find it harder to evaluate AI outputs, recognise hallucinations, or identify weak reasoning. Research also cautions that generative AI can improve task performance without improving knowledge gain, transfer, or students’ ability to assess their own understanding — a distinction that has direct implications for how programmes design assessments and sequence learning. _3,4
 

AI capability needs to be developed progressively

Future-ready AI use involves more than basic tool operation. Students need to learn how to use AI responsibly, effectively, and fluently: formulating better prompts, evaluating outputs critically, recognising bias, protecting data, and exercising ethical judgement. AI literacy frameworks developed for higher education increasingly treat these capabilities as integral to both academic preparation and professional readiness. _5,6
 

Graduates need to demonstrate their human value-add

As generative AI reshapes the workplace, employers are placing greater emphasis on the capabilities that complement AI: judgement, creativity, communication, collaboration, critical thinking, and ethical decision-making. _7,8 Programme-level redesign makes these priorities visible across the curriculum, by clarifying where students develop competencies independently of AI, where they learn to work with AI, and where they demonstrate what they contribute beyond it.