Communicational Transfer of Generative Artificial Intelligence in Ibero-Lusophone Institutional Resources
DOI:
https://doi.org/10.61283/91j0xn05Keywords:
applied communication, digital education, generative artificial intelligence, knowledge transfer, media literacy, public communicationAbstract
Objective: to analyse, from Applied Communication and knowledge transfer, how open institutional resources on generative artificial intelligence, media literacy and digital education transform expert knowledge into understandable, accessible and actionable guidance for educational and family audiences. The article examines institutional documentary provision as communicational mediation, not as evidence of use or impact. Methodology: the study adopts a comparative empirical-documentary design with a qualitative-quantitative orientation, based on manual coding assisted by Jupyter/Python; the purposive sample consists of 12 institutional sources selected according to official status, public accessibility, connection with generative AI, media literacy or digital education, and relevance for educational or family audiences. The unit of analysis is the complete institutional document or resource. Results: the average communicational transfer index is 4.00/5, with 8 out of 12 documents classified at high or very high levels; all sources address teachers, whereas only 5 explicitly include families. Discussion: the findings, connected with the literature on knowledge transfer, public communication, media literacy and AI literacy, identify a school-home documentary asymmetry. Conclusions: the study does not measure reception, use or actual impact, but rather documentary conditions for transfer. New contribution: it proposes a replicable matrix for assessing clarity, accessibility, applicability and communicational anchoring in institutional resources on generative AI.
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Data Availability Statement
The research data supporting the study’s findings have been made available to the journal for editorial review. The documentary corpus analysed consists of open institutional sources, while the coding matrix, master source register, tabular outputs and methodological traceability materials are available to the editorial team and reviewers.
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