Scaffold Strategies for Integrating Large Language Models into Production-Oriented Approach Teaching from a Sociocultural Theory Perspective

Abstract

With the rapid development of artificial intelligence technology, large language models (LLMs) have demonstrated immense potential in educational applications. This study explores scaffold strategies for integrating LLMs into Production-Oriented Approach (POA) teaching from a sociocultural theory perspective. The research systematically demonstrates the theoretical compatibility between LLMs and sociocultural theory in three aspects: learning tool mediation, Zone of Proximal Development application, and social interactive learning. Building on this foundation, the study examines specific scaffold strategies for LLMs across different stages of POA teaching: in the motivating stage, proposing three key strategies – intelligent situation generation, interactive task design, and real-time capability gap diagnosis; in the enabling stage, constructing a support system comprising intelligent task description, selective learning support, and output practice guidance; in the assessment stage, designing evaluation mechanisms including intelligent assessment criteria construction, multi-dimensional immediate feedback, and portfolio-based evaluation tracking. Finally, the study highlights key considerations for implementation, including balancing cognitive dependency with learning internalization, dynamic adjustment between learning autonomy and support levels, unifying scientific validity and operability in assessment standards, and maintaining equilibrium between technological support and humanistic care. 105-118 Scaffold Strategies for Integrating Large Language Models into Production-Oriented Approach Teaching from a Sociocultural Theory Perspective 下载 Pages: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Share this: Share on X (Opens in new window) X Share on Facebook (Opens in new window) Facebook