摘要
在人工智能深度嵌入高等教育学习情境下,智能技术提升学习效率的同时,也显露出引发技术依赖与成瘾进而削弱个体自主学习动机的潜在风险。本文引入I-PACE理论框架,对大学生在智能助学情境中人工智能依赖与成瘾的生成机制及其对学习倦怠的影响路径进行实证分析。研究发现,学生自身特质及使用人工智能时形成的功能性认知与情感性体验,会显著强化其依赖性使用倾向,并在持续互动中推动技术使用向成瘾状态演化,进而加剧学习倦怠。人工智能依赖与成瘾在技术感知与学习倦怠之间构成递进式中介路径,揭示了智能助学由“技术赋能”转向“心理依赖”的内在机制,提示了技术使用风险在智能教育场景中的存在,为高校智能助学治理提供了理论启示。
Artificial intelligent technologies have enhanced learning efficiency but also revealed potential risks of inducing technological dependency and addiction,which undermine individuals'autonomous learning motivation.This paper introduced the I-PACE theoretical framework to empirically analyze the generative mechanisms of AI dependency and addiction among college students in intelligent tutoring scenarios and their impact on learning burnout.Findings show that functional cognition and affective experiences during AI usage strengthen students'dependency.Continuous interaction leads to addictive states and worsens learning burnout.AI dependency and addiction are a mediating pathway between technology perception and learning burnout,revealing how intelligent tutoring shifts from"technological empowerment"to“psychological dependency.”This study expands the explanatory scope of technology addiction in intelligent education from the perspective of technology usage risks and provides theoretical insights for governing intelligent learning assistance in higher education.
作者
蓝燕玲
刘司航
LAN Yanling;LIU Sihang(School of Film and Communication,Xiamen University of Technology,Xiamen 361024,China)
出处
《信息传播研究》
2026年第1期69-80,共12页
Information and Communication Research
