
This article argues that AI literacy in education must move beyond technical skills, prompt engineering, and ethical awareness alone. In the age of generative AI, the central educational challenge is not only whether learners can use AI tools effectively, but whether they can continue to think, understand, verify, regulate their learning, make responsible decisions, and preserve their intellectual autonomy while using them. The article proposes a human-centered AI culture framework structured around five complementary dimensions: cognitive culture, metacognitive culture, motivational culture, ethical culture, and human agency. Drawing on recent research on generative AI, metacognition, cognitive offloading, automation bias, and self-regulated learning, it shows that AI can support learning when pedagogically guided, but may also weaken reasoning, effort, critical thinking, and autonomy when used as a shortcut. The article offers policy recommendations for governments, schools, universities, teacher training institutions, and educational AI developers. It calls for curricula, assessment practices, teacher education, and AI tool design to be aligned with human-centered pedagogical values. Its main contribution is to redefine AI literacy as a broader educational culture aimed at ensuring that AI enhances human learning without replacing the cognitive, ethical, and autonomous processes through which learning takes place.
generative AI in education, human-centered AI, learner agency, Metacognitive regulation, AI literacy, ethical AI, cognitive autonomy, educational policy
generative AI in education, human-centered AI, learner agency, Metacognitive regulation, AI literacy, ethical AI, cognitive autonomy, educational policy
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
