Hybrid intelligence and educational agency: Towards an ecology of human-AI collaboration
Abstract The emergence of generative artificial intelligence has revived an enduring question in educational technology: Should artificial intelligence (AI) supplant teachers or support them? The evidence does not sustain either pole. This article advances hybrid intelligence, an integrated mode of human-AI collaboration in which agency, judgment, and accountability are shared rather than lodged in just one side, as a more useful lens for understanding AI in education. Using a theoretical and argumentative method, the paper defines the concept. It separates hybrid intelligence from adjacent ideas, including blended learning and educational AI, and links its philosophical lineage to extended mind theory, man-computer symbiosis, and actor-network theory. The article then examines three major conceptual frameworks: Molenaar’s six-level automation model, Cukurova’s AIED-HCD taxonomy, and Holstein, Aleven, and Rummel’s hybrid adaptivity model. These are brought together in a five-level architecture for hybrid learning ecosystems: people and roles, hybrid space, data, models, and governance. In addition, it sketches three scenarios for the gradual incorporation of AI into university teaching, together with the nine persistent challenges (the “elephants in the room”). The discussion highlights shared patterns across the frameworks and the teaching competencies required for hybrid intelligence. The article ends by arguing that, in education, hybrid intelligence can realise its potential only through a human-centred orientation: technology must adapt to education, not education to the technology.
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