Center for Studies of Education and Psychology of Ethnic Minorities in Southwest China, Southwest University, Chongqing, China.
College of Educational Science, Xinjiang Normal University, Urumqi, Xinjiang, China.
PLoS One. 2024 Nov 1;19(11):e0313314. doi: 10.1371/journal.pone.0313314. eCollection 2024.
The adoption of Generative AI in education presents both opportunities and challenges, particularly regarding its potential to foster student dependency. However, the psychological drivers of this dependency remain unclear. This study addresses this gap by applying the Interaction of Person-Affect-Cognition-Execution (I-PACE) model and Basic Psychological Needs (BPN) theory to explore how specific personality traits-neuroticism, self-critical perfectionism, and impulsivity-contribute to AI dependency through needs frustration, negative academic emotions, and reinforced performance beliefs.
Data were collected from 958 university students (Mage = 21.67) across various disciplines. Structural equation modeling (SEM) was used to analyze the relationships among the variables.
Neuroticism, self-critical perfectionism, and impulsivity were found to be significantly associated with increase needs frustration and negative academic emotions, which in turn reinforced students' positive beliefs about performance of AI tools, deepening their dependency. The study also uncovered complex serial mediation effects, highlighting intricate psychological pathways that drive maladaptive AI use.
This research provides a critical insight into the interplay between personality traits and technology use, shedding light on the nuanced ways in which individual differences influence dependency on generative AI. The findings offer practical strategies for educators to promote balanced AI use and support student well-being in educational settings.
生成式人工智能在教育中的采用既带来了机遇，也带来了挑战，特别是其可能培养学生依赖性的问题。然而，这种依赖性的心理驱动因素尚不清楚。本研究通过应用人格-情感-认知-执行的相互作用（I-PACE）模型和基本心理需求（BPN）理论，来解决这一差距，以探讨特定的人格特质——神经质、自我批评的完美主义和冲动性——如何通过需求受挫、消极的学术情绪和强化的表现信念导致对人工智能的依赖。
本研究共收集了来自不同学科的 958 名大学生（Mage = 21.67）的数据。采用结构方程模型（SEM）分析变量之间的关系。
神经质、自我批评的完美主义和冲动性与需求受挫和消极的学术情绪显著相关，进而强化了学生对人工智能工具表现的积极信念，加深了他们对人工智能的依赖。研究还揭示了复杂的序列中介效应，突显了驱动适应性人工智能使用的复杂心理途径。
本研究深入探讨了人格特质与技术使用之间的相互作用，揭示了个体差异影响对生成式人工智能依赖的微妙方式。研究结果为教育工作者提供了实用的策略，以促进平衡的人工智能使用，并在教育环境中支持学生的幸福感。
