Digital Education in the Age of Artificial Intelligence: Towards anEmirati Model for Protecting Family Identity and EnhancingSocial Cohesion
DOI:
https://doi.org/10.54878/5yz8va60Keywords:
Digital education, artificial intelligence, new media, family identity, social cohesion, United Arab Emirates, digital ethics.Abstract
Artificial intelligence (AI), algorithmically curated platforms, and generative media are reshaping how people access information, communicate, and learn. These developments create educational opportunities while raising questions about privacy, misinformation, bias, family interaction, cultural identity, and social cohesion. This conceptual paper examines digital education as a framework for developing the knowledge, judgement, and ethical dispositions needed to participate responsibly in AI-mediated environments. It focuses on the United Arab Emirates (UAE), where national efforts to advance AI literacy provide a relevant policy context for considering how technological capability can be aligned with cultural context and human values. The paper uses a qualitative descriptive-analytical approach to examine selected international frameworks and institutional policy documents alongside conceptual literature on networked communication, media literacy, participatory culture, and digital ethics. It does not claim to measure the prevalence or causal effects of digital risks in Emirati families; rather, it synthesises relevant concepts and derives a proposed educational framework. The analysis identifies five mutually reinforcing pillars: digital national and cultural identity; media and algorithmic literacy; digital ethics and safety; partnership among families, schools, media, and public institutions; and a human-centred balance between technology use and face-to-face relationships. The paper argues that these pillars should be translated into age-appropriate learning outcomes, family guidance, teacher development, and coordinated institutional practice. It concludes that the proposed model is a conceptual contribution requiring subsequent expert review and empirical evaluation before its effectiveness can be established
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