ARTIFICIAL INTELLIGENCE-ENABLED SUSTAINABLE LEARNING ECOSYSTEMS IN HIGHER EDUCATION: A NEUROMARKETING ANALYSIS OF TECHNOLOGY ADOPTION AND HUMAN DECISION-MAKING
Keywords:
Artificial Intelligence, Neuromarketing, Sustainable Learning Ecosystems, Technology Adoption, Higher Education, Human Decision-Making.,,Abstract
The precipitous assimilation of Artificial Intelligence (AI) within tertiary education has forced a
critical revaluation of "Sustainable Learning Ecosystems" (SLE). These systems are designed to
ensure pedagogical resilience and long-term knowledge regeneration. This research deconstructs
the interplay between AI-driven instructional tools and the neurobiological underpinnings of user
adoption. While traditional acceptance models emphasize rational utility, this study utilizes a
neuromarketing lens to argue that the majority of adoption behaviors are governed by non
conscious cognitive and affective processes. Drawing upon a conceptual analysis of data from the
OECD (2025-2026), UNESCO, and Scopus-indexed literature, the paper explores the "Affective
Cognitive Conflict" inherent in immersive AI environments. Findings indicate that while high-tech
interfaces like the metaverse capture significant neural attention, they often impose a prohibitive
mental workload that diminishes emotional satisfaction. The research proposes a multi-layered
conceptual model that bridges the gap between individual neurometric signals and institutional
sustainability goals. By distinguishing between "human-like" and "system-like" trust, the study
offers a path toward "appropriately calibrated trust" in human-AI collaboration. The ultimate
contribution is a synthesized conceptual pattern that views digital intelligence not as a replacement
for human agency, but as a "living ally" in the co-evolution of knowledge systems.
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