Use AI inside real work.
Students inspect sources, test an AI-supported position and produce work for a named workplace audience.
STEP Campus is the original StepSim pathway: ten realistic assignments that place students inside AI-assisted work where they must inspect evidence, handle ambiguity, communicate responsibly and remain accountable for what they produce.
For universities, educators, employability teams and career-readiness programmes. STEP Campus is a separate education pathway within the StepSim umbrella.
AI can explain concepts and produce fluent answers in seconds. Students still need practice deciding what matters, what evidence is sufficient, how people may be affected, what should change and what they are prepared to own.
Students inspect sources, test an AI-supported position and produce work for a named workplace audience.
Students balance uncertainty, ethics, empathy, authority and consequences that cannot be delegated to a tool.
Educators can debrief decisions and artifacts without treating one simulation as automatic proof of general competence.
STEP Campus is designed in alignment with the direction represented by Singapore's Four Learns framework. It is not MOE-certified, accredited or endorsed.
The assignments remain available as the established Campus pathway. Each focuses on a different workplace tension and work product.
Clarify an unclear manager request before AI turns ambiguity into confident but misdirected work.
Audit a fluent research summary and separate source-backed claims from unsupported confidence.
Notice the stakeholder missing from an apparently efficient workplace decision.
Protect personal information when speed and convenience push toward an unsafe shortcut.
Turn AI-supported material into a defensible recommendation for decision-makers.
Recognise when generic AI output lacks the local context required for action.
Prioritise competing requests while preserving quality, communication and ownership.
Respond to a live client-delivery problem without hiding uncertainty or overpromising.
Challenge an aggregate result that hides the pattern decision-makers actually need to see.
Decide what AI may run alone and where human review and accountability must remain.
The pathway is most useful when an educator connects each assignment to teaching, reviews the resulting work and gives students a fresh situation in which to apply the same quality standard.
Campus work can show what a student did in a controlled assignment. Broader claims about competence, employability, prediction or institutional impact require separate governance and evidence.
Read the shared StepSim method →Try the public student sample or discuss how the ten assignments could fit an existing employability or capstone programme.