研究论文

基于元认知理论的大学生偏差信息搜寻行为影响因素及预测研究

  • 王煜霞 ,
  • 韩毅
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  • 1西南大学商贸学院 重庆 402460;
    2西南大学新闻传媒学院 重庆 400715
王煜霞,硕士研究生;韩毅,教授,博士,通信作者,E-mail:hanyi72@swu.edu.cn。

收稿日期: 2025-03-31

  修回日期: 2025-07-02

  网络出版日期: 2026-05-07

基金资助

本文系西南大学研究生科研创新资助项目“元认知能力对偏差信息搜寻行为的影响研究”(项目编号:SWUS24200)研究成果之一。

Researches on the Influencing Factors and Prediction of College Students’ Biased Information-Seeking Behavior Based on Metacognitive Theory

  • Wang Yuxia ,
  • Han Yi
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  • 1 Business College, Southwest University, Chongqing 402460;
    2 School of Journalism and Communication, Southwest University, Chongqing 400715
Wang Yuxia, Master’s Candidate; Han Yi, Professor, PhD, Corresponding Author, E-mail: hanyi72@swu.edu.cn.

Received date: 2025-03-31

  Revised date: 2025-07-02

  Online published: 2026-05-07

Supported by

This work is supported by Southwest University Graduate Research and Innovation Funding project titled “Research on the Influence of Metacognitive Ability on Biased Information-Seeking Behavior” (Grant No. SWUS24200).

摘要

[目的/意义]深入剖析元认知能力与偏差信息搜寻行为之间的内在联系,助力个体优化信息搜寻策略,破解信息茧房困境,全面提升信息素养。[方法/过程]基于“认知—态度—行为”模型,将元认知体验与元认知监测作为双中介变量,构建个体偏差信息搜寻行为影响因素概念模型,采用岭回归和Bootstrap方法对495份有效问卷数据进行实证分析。基于实证结果,采用随机森林算法构建个体偏差信息搜寻行为预测模型。[结果/结论]元认知能力各维度均有效抑制了偏差信息搜寻行为,且元认知体验与元认知监测在其中分别发挥部分中介作用。特别地,元认知知识通过元认知体验和元认知监测的链式中介作用间接影响偏差信息搜寻行为,该发现丰富了信息搜寻行为中的元认知调控模型。预测结果显示,基于发散式调控模式和收敛式调控模式构建的混合分类器在预测个体信息搜寻偏差程度方面表现出良好性能。

本文引用格式

王煜霞 , 韩毅 . 基于元认知理论的大学生偏差信息搜寻行为影响因素及预测研究[J]. 图书情报工作, 2026 , 70(10) : 122 -134 . DOI: 10.13266/j.issn.0252-3116.2026.10.010

Abstract

[Purpose/Significance] This study aims to delve into the intrinsic relationship between metacognitive ability and biased information-seeking behavior. It seeks to help individuals optimize their information search strategies, break out of information cocoons, and enhance overall information literacy. [Method/Process] Based on the “cognitive-attitude-behavior” model, this study constructed a conceptual model of the factors influencing individual biased information-seeking behavior by treating metacognitive experience and metacognitive evaluation as causally related dual mediators. Ridge regression and Bootstrap methods were used to empirically analyze data from 495 valid questionnaires. Based on empirical results, a prediction model for individual biased information-seeking behavior was constructed using the random forest algorithm. [Result/Conclusion] The empirical results indicate that the various dimensions of metacognitive ability effectively inhibit biased information-seeking behavior. Both metacognitive experience and metacognitive monitoring play partial mediating roles in this process. In particular, metacognitive knowledge indirectly influences biased information-seeking behavior through the chain-mediation effect of metacognitive experience and metacognitive monitoring. This finding enriches the metacognitive regulation model of information-seeking behavior. The predictive results demonstrate that the hybrid classifier constructed based on divergent and convergent regulatory modes shows good performance in predicting the degree of information-seeking bias.

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