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基于计算机测试中作为第二语言写作成绩预测指标的心理生理因素

Psychophysiological factors as predictors of second language writing achievement in a computer-based test.

作者信息

Lee Shu-Ping, Chang Shujen Lee, Su Hui-Kai, Cui Zhen-Yang, Lee Shin-Da

机构信息

Department of Foreign Language, Asia University, Taichung, Taiwan.

Department of Psychology, Asia University, Taichung, Taiwan.

出版信息

Front Psychol. 2022 Oct 19;13:958938. doi: 10.3389/fpsyg.2022.958938. eCollection 2022.

Abstract

Sleep quality, personality, and cognitive load potentially increase second language writing (SLW) anxiety and subsequently affect SLW achievement. This study investigates the predictions of sleep quality, personality (social inhibition/ negative affectivity), and cognitive load (content/ computer) toward SLW anxiety and achievement in a computer-based test. Participants included 172 voluntary undergraduates majoring in English as foreign language. SLW anxiety in a computer-based test, sleep disturbance, personality and cognitive load was assessed with the SLW Anxiety Inventory, Pittsburg Sleep Quality Index, Type-D Personality, and cognitive load questionnaires. A structural equation modeling approach was applied to examine the interdependence among the observed variables. An adequate-fit SLW anxiety model was built (  = 6.37,  = 6,  = 0.383,  = 0.97,  = 1.00,  = 0.02; R-squared multiple correlations: SLW anxiety in a computer-based test = 0.19, computer-based SLW achievement = 0.07). The structural model showed that sleep disturbance (+0.17), social inhibition personality (+0.31), and computer-induced cognitive load (+0.16) were significant predictors of SLW anxiety in a computer-based test. Subsequently, SLW anxiety in a computer-based test (-0.16) and computer-induced cognitive load (-0.16) were significant negative predictors of computer-based SLW achievement.

摘要

睡眠质量、性格和认知负荷可能会增加第二语言写作(SLW)焦虑,进而影响第二语言写作成绩。本研究调查了在基于计算机的测试中,睡眠质量、性格(社交抑制/消极情感性)和认知负荷(内容/计算机)对第二语言写作焦虑和成绩的预测作用。研究参与者包括172名自愿参与的英语专业本科生。通过第二语言写作焦虑量表、匹兹堡睡眠质量指数、D型人格量表和认知负荷问卷,对基于计算机测试中的第二语言写作焦虑、睡眠障碍、性格和认知负荷进行了评估。采用结构方程模型方法来检验观测变量之间的相互依存关系。构建了一个拟合良好的第二语言写作焦虑模型(χ² = 6.37,df = 6,CFI = 0.383,IFI = 0.97,TLI = 1.00,RMSEA = 0.02;多重相关系数R²:基于计算机测试中的第二语言写作焦虑 = 0.19,基于计算机的第二语言写作成绩 = 0.07)。结构模型表明,睡眠障碍(+0.17)、社交抑制性格(+0.31)和计算机引发的认知负荷(+0.16)是基于计算机测试中第二语言写作焦虑的显著预测因素。随后,基于计算机测试中的第二语言写作焦虑(-0.16)和计算机引发的认知负荷(-0.16)是基于计算机的第二语言写作成绩的显著负向预测因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7048/9626855/2368cad20a58/fpsyg-13-958938-g001.jpg

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