Curriculum is no longer a stable sequence of knowledge to be delivered, it is becoming a contested design space where knowledge, capability, and identity are continuously redefined. In an era where AI systems generate, apply, and restructure knowledge in real time, we ask what it means to design curriculum that remains meaningful, adaptive, and consequential. We invite work that challenges inherited assumptions about curriculum design and explores new models that are co-constructed with industry, responsive to uncertainty, and capable of evolving alongside technological and societal change.
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The foundations of expertise are shifting. As AI systems increasingly generate analysis, reasoning, and decision support, long-standing assumptions about knowledge ownership and professional competence are breaking down. Expertise is no longer defined by what one knows, but by how one acts when knowledge is distributed, uncertain, and machine mediated. This theme invites critical and empirical work on what expertise becomes when intelligence is no longer exclusively human.
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Professions are being reassembled in real time. Roles such as doctor, lawyer, architect, and designer are no longer defined by stable task boundaries, but by shifting relationships between humans, systems, and automation. This raises profound questions about responsibility, legitimacy, and trust. We invite work that interrogates not only how professions change, but what it means to be a professional at all.
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Assessment systems were designed for a world in which performance was human, observable, and separable from tools. That world no longer exists. As AI reshapes what it means to perform, learn, and produce value, assessment itself must be rethought. This theme explores how education systems can move beyond proxy measures of achievement toward authentic evaluation of capability in real-world contexts.
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