How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective.
<h4>Objective</h4>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...
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Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0313314 |
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| author | Wenjun Zhong Jianghua Luo Ya Lyu |
| author_facet | Wenjun Zhong Jianghua Luo Ya Lyu |
| author_sort | Wenjun Zhong |
| collection | DOAJ |
| description | <h4>Objective</h4>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.<h4>Method</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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. |
| format | Article |
| id | doaj-art-8e5f23dc887e4d758ac36df7b01b2e0c |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-8e5f23dc887e4d758ac36df7b01b2e0c2025-08-20T02:13:02ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011911e031331410.1371/journal.pone.0313314How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective.Wenjun ZhongJianghua LuoYa Lyu<h4>Objective</h4>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.<h4>Method</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.https://doi.org/10.1371/journal.pone.0313314 |
| spellingShingle | Wenjun Zhong Jianghua Luo Ya Lyu How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective. PLoS ONE |
| title | How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective. |
| title_full | How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective. |
| title_fullStr | How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective. |
| title_full_unstemmed | How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective. |
| title_short | How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective. |
| title_sort | how do personal attributes shape ai dependency in chinese higher education context insights from needs frustration perspective |
| url | https://doi.org/10.1371/journal.pone.0313314 |
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