AI双师课堂心理适应性研究——基于学习投入与情感交互的视角

Psychological Adaptability in AI Dual-Teacher Classrooms—From the Perspective of Learning Engagement and Emotional Interaction

摘要: 本研究基于教育心理学、认知心理学与人机交互心理学，以自我决定理论、认知负荷理论、自我效能感理论、元认知理论、情绪认知理论及技术接受理论为核心支撑，系统探究AI与教师协同双师课堂下的学生心理变化。研究发现：AI能降低认知负荷、提升胜任感与元认知；真人教师则弥补情感与心理支持不足，维持归属感与情绪稳定。但新模式也引发AI依赖、思维惰性、人机疏离等心理问题。本文从认知、动机、情绪、人格、人机平衡五个维度提出优化策略，旨在构建“技术赋能认知、教师温暖育心”的新型课堂心理生态，为智能教学改革与心理健康培育提供参考。

Abstract: Based on the theoretical frameworks of educational psychology, cognitive psychology, and human-computer interaction psychology, and drawing on self-determination theory, cognitive load theory, self-efficacy theory, metacognitive theory, emotional cognitive theory, and technology acceptance theory as core supports, this study systematically explores students’ psychological changes in AI-teacher collaborative dual-teacher classrooms. The findings reveal that AI can reduce cognitive load, enhance perceived competence and metacognition, while human teachers compensate for AI’s lack of emotional and psychological support, maintaining students’ sense of belonging and emotional stability. However, this new model also triggers psychological issues such as AI dependence, mental inertia, and human-machine alienation. This paper proposes optimization strategies from five dimensions—cognition, motivation, emotion, personality, and human-machine balance—aiming to construct a new classroom psychological ecosystem characterized by “technology empowering cognition, teachers nurturing the heart with warmth”, providing theoretical and practical references for intelligent teaching reform and student mental health cultivation.