Abstract
Generative
artificial intelligence (AI) can produce detailed career advice, yet a
persuasive plan offers limited educational value when students cannot explain
its assumptions or test it through experience. The pathway developed here
connects career exploration, learning guidance, and labor education in Chinese
higher education. It draws on research concerning AI career support and
self-regulated learning, together with international educational guidance and
China’s labor education framework. The pathway begins with students identifying
a career question from their own experience. They then examine AI suggestions
against verified occupational information, translate an unresolved question
into a learning task, and complete practical work that produces evidence for
revising their plans. Teachers intervene when information, student
expectations, and practical feedback conflict. Assessment centers on the reasons
for a choice, the quality of work evidence, and the justification for
subsequent revision. An illustrative community service task shows how online
guidance can inform practical activity and how experience can redirect further
inquiry. The article contributes an instructional arrangement in which career
planning develops through student-produced evidence. Its educational value
requires evaluation through implementation, particularly regarding access to
meaningful practice and the quality of student judgment.
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