A new spiral model of AI literacy and competency in higher education developed through a systematic literature review

This study introduces a new spiral model of artificial intelligence (AI) literacy and competency in higher education. It conceptualizes AI competency as a recursive and multidimensional developmental process that evolves from foundational AI literacy. The model addresses persistent conceptual ambiguity between AI literacy and competency and extends existing static and fragmented frameworks by explaining how competency progressively develops through iterative learning. Following PRISMA 2020 guidelines, a systematic literature review and thematic synthesis of 18 studies identified three major gaps, including conceptual overlap between AI literacy and competency, fragmented framework structures, and limited developmental progression. In response, the proposed model integrates three interdependent dimensions, reflective, dispositional, and practical, within interactive learning environments. Repeated cycles progressively deepen students' critical, ethical, and applied engagement with AI. The model is theoretically grounded in Piaget's Cognitive Development Theory, Bandura's Social Cognitive Theory, Vygotsky's Sociocultural Theory, and Bruner's Spiral Curriculum Theory. Its developmental mechanism is further formalized through the Multiplicative Spiral Gain Function (MSGF), which represents how balanced growth across these dimensions strengthens the transformation of AI literacy into competency. The model provides a foundation for curriculum design, competency assessment, learning analytics, and future empirical validation.