NextGen Talent-Driven AI Educational Agent

Abstract

This research addresses critical gaps in Artificial Intelligence (AI)-driven educational systems by developing a NextGen Talent-Driven AI Educational Agent framework that systematically integrates human-centric competencies to advance Sustainable Development Goal (SDG) 4. The methodology combines a comprehensive literature review of research articles, validation through expert interviews, and Confirmatory Factor Analysis (CFA). The framework operationalizes four core NextGen Talent dimensions through systematic integration into AI agent architecture, progressing from conceptual development through pilot implementation to scalable deployment. CFA results demonstrate satisfactory model fit (χ²/df = 1.261, Cross-Field Innovators (CFI) = 1.000, Goodness of Fit Index (GFI) = 0.970, Root Mean Square Error of Approximation (RMSEA) = 0.026) with Cross-Field Innovators emerging as the most influential dimension (factor loading = 1.00). The technical architecture integrates ChatGPT’s Natural Language Processing (NLP) capabilities with Role-Task-Output configuration, enabling personalized learning experiences that adapt to individual learner needs while maintaining pedagogical soundness. This human-centric approach addresses limitations in current AI educational systems including inadequate evaluation protocols, technical constraints in processing unstructured data, and insufficient consideration of socio-emotional learning factors. The framework provides concrete architectural principles for developing AI agents that enhance rather than replace human capabilities, offering scalable solutions for inclusive and equitable quality education aligned with SDG 4 principles.

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