Analysis of Community Experiential Education Pathways Based on AIGC Technology and Their Impact on Literacy Enhancement

Abstract

Generative Artificial Intelligence (AIGC) provides a new technological pathway for overcoming the inherent limitations of community experiential education in terms of resources, context, and support. This study systematically constructs an AIGC-driven community experiential education framework. By elucidating its coupling mechanism with experiential learning theory concerning context deepening and cognitive transformation, it proposes intelligent education pathways encompassing personalized path generation, immersive scenario construction, and dynamic content adaptation. Building on this foundation, the study constructs a three-dimensional literacy analysis framework consisting of cognitive, social, and metacognitive dimensions. It analyzes the mechanisms through which AIGC, serving as an intelligent scaffold, a social simulator, and a metacognitive partner, drives literacy development. Furthermore, it develops a methodological system integrating multimodal learning analytics and processual assessment, thereby offering theoretical reference and practical guidance for AIGC-enabled contextualized learning.