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for “AI Literacy” as a compass for human capital development, and to propose a distance-
learning ecosystem model that fosters lifelong learning to build a resilient, adaptable
workforce.
Particularly in the context of distance education systems, developing a digital
learning ecosystem to promote artificial intelligence literacy among undergraduate
students represents a critical frontier. Distance education models, which inherently rely
on digital mediation, possess a unique structural advantage to rapidly deploy AI-
integrated curricula across diverse demographics. By embedding AI literacy foundational
courses at the undergraduate level, educational institutions can preemptively equip the
future workforce with the cognitive and technical agility required to navigate an
unpredictable labor market, shifting their trajectory from potential displacement to
empowered collaboration.
2. Literature review
2.1. Conceptualizing artificial intelligence literacy
Artificial Intelligence Literacy (AI Literacy) has evolved from a narrow emphasis on
computational knowledge toward a broader, interdisciplinary construct encompassing
cognitive, technical, ethical, and socio-cultural competencies required to effectively
engage with AI systems (Long & Magerko, 2020; Ng et al., 2021; Kasneci et al., 2023).
Early definitions primarily focused on understanding algorithms and basic programming
logic as foundational knowledge (Long & Magerko, 2020). However, the emergence of
generative AI has significantly expanded this scope, requiring users to critically interpret
outputs, evaluate reliability, and apply AI tools in diverse real-world contexts (Kasneci et
al., 2023; UNESCO, 2023).
Recent scholarship conceptualizes AI literacy as a multidimensional competency
that integrates human-AI collaboration, data interpretation, and responsible decision-
making (Ng et al., 2021; Holmes et al., 2023). This shift reflects a transition from “learning
about AI” to “learning with AI,” where users actively co-create knowledge rather than
passively consume information (Holmes et al., 2023; Bond et al., 2024). Consequently, AI
literacy is increasingly framed as a critical capability for navigating complex digital
environments, requiring both technical fluency and critical awareness of ethical
implications, data privacy, and human agency (UNESCO, 2023; European Commission,
2026).
2.2. Digital learning ecosystems in distance education
The concept of digital learning ecosystems has gained increasing attention as
education systems respond to rapid technological transformation and the growing
demand for lifelong learning (Selwyn, 2023; Shelton & Dockens, 2025). A digital learning
ecosystem is an interconnected system that integrates technological infrastructure,
pedagogical strategies, and learner support mechanisms to enable continuous, flexible
learning experiences (Shelton & Dockens, 2025; Bond et al., 2024). In distance education
contexts, such ecosystems are particularly significant, as they facilitate scalable access to
learning across geographical and temporal boundaries (Brynjolfsson et al., 2020; Selwyn,
2023).
Contemporary research highlights that effective digital ecosystems extend beyond
technological adoption and require alignment among curriculum design, learner
engagement, and institutional capacity (Bond et al., 2024; Holmes et al., 2023). AI-
powered tools, including adaptive learning systems and intelligent tutoring agents, have
been shown to enhance personalization and learner autonomy within these

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