NO PYTHONS, NO PANDAS, NO ROBOTS: WHAT AI LITERACY REALLY MEANS FOR K–12 EDUCATION.
The request for AI education in schools has led to basic programming classes, robotics clubs and technology courses as the main responses. These methods show good intentions, yet they confuse learning about AI technology with actual AI literacy. The paper establishes that AI literacy exists beyond b...
| Publicado en: | Scientific Culture Vol. 12; no. 1; pp. 358 - 367 |
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| Formato: | Artículo |
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University of the Aegean
2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=191958891&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 191958891 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 24080071 I6HU jtl: Scientific Culture issn: 24080071 maglogo: N pubinfo: dt: 2026 vid: 12 iid: 1 pid: 47715 pub: University of the Aegean artinfo: ui: 191958891 10.5281/zenodo.18405939 ppf: 358 ppct: 9 formats: tig: atl: NO PYTHONS, NO PANDAS, NO ROBOTS: WHAT AI LITERACY REALLY MEANS FOR K–12 EDUCATION. aug: au: Andoniou, Constantine affil: Department of Education. Abu Dhabi University, Abu Dhabi, United Arab Emirates. su: Artificial intelligence & ethics Human-artificial intelligence interaction Digital literacy Compulsory education Holistic education sug: subj: Artificial intelligence & ethics Human-artificial intelligence interaction Digital literacy Compulsory education Holistic education keyword: AI Literacy Critical AI Reasoning Cross-Curricular Design Curriculum Integration Data Agency Digital Ethics Educational Technology Human–AI Collaboration K–12 Education Teacher Readiness ab: The request for AI education in schools has led to basic programming classes, robotics clubs and technology courses as the main responses. These methods show good intentions, yet they confuse learning about AI technology with actual AI literacy. The paper establishes that AI literacy exists beyond being a subject and digital tools and computer science departments cannot handle its implementation. The capability exists as a cross-disciplinary learning skill which helps students understand AI systems while questioning them and working with them in academic and social and civic environments. The paper defines AI literacy through four essential domains: (a) Critical AI Reasoning for understanding AI system classification, prediction and information generation processes; (b) Digital Ethics and Data Agency for handling consent, privacy issues, surveillance and bias problems; (c) Human–AI Collaboration for determining AI usage, intervention points and effective teamwork with AI systems; and (d) Applied AI Across the Curriculum for teaching AI throughout languages, arts, sciences, humanities and vocational subjects, instead of treating it as a standalone technical subject. The paper provides classroom examples, teacher-ready implementation ideas, and a K–12 progression model that moves from AI awareness in early years to critical and creative collaboration in upper secondary. Instead of asking schools to produce AI engineers, the model prepares students to become informed, responsible participants in AI-shaped societies. The conclusion offers concrete steps for school leaders and teacher teams who need to act now, without waiting for perfect infrastructure or specialist staff. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2026 holdings: @attributes: islocal: N |
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