激励和参与作为途径:人工智能增强的在线评估如何塑造职业EFL教室的英语语言能力
Xianyan Dai1,2, Yongjian Wang3, Jiawen Yu4
1School of Chinese and International Education, Guangzhou International Economics College, Guangzhou, Guangdong, China.
Frontiers in psychology
|January 22, 2026
概括
在线评估 (OA) 中的人工智能 (AI) 对职业EFL学习者的英语语言能力 (ESC) 有积极的影响,特别是当与高动力和参与相结合时. 即使没有人工智能,动机也是发展语言技能的关键.
科学领域:
- 教育技术的教育技术
- 应用语言学 应用语言学
- 学习心理学学习的心理学.
背景情况:
- 人工智能 (AI) 越来越多地用于语言评估,但它对沟通技能的心理影响需要进一步研究.
- 了解AI增强的在线评估 (OA) 如何影响学习者的自我认知英语语言能力 (ESC) 对职业英语外语 (EFL) 语境至关重要.
- 在这种关系中,数字教学中的动机 (MODT) 和数字教学中的参与 (ENDT) 的调解作用未得到充分探索.
研究的目的:
- 在职业EFL学习者中研究AI增强的OA和ESC之间的关系.
- 调查MODT和ENDT对OA-ESC链接的调解作用.
- 在支持人工智能的学习环境中确定高ESC的关键配置.
主要方法:
- 使用了部分最小平方结构方程建模 (PLS-SEM) 和模糊集定性比较分析 (fsQCA).
- 从中国广东省的463名职业EFL学生收集了数据.
- 用标记变量分析和PLSpredict来评估常用方法的差异性和模型预测准确性.
主要成果:
- 开放式开放对社会经济委员会有直接的,虽然很小的积极影响,通过MODT和ENDT产生更强烈的间接影响.
- fsQCA揭示了高ESC的多个足够配置,强调了动机的持续重要性.
- 人工智能反最准确地预测了流性和连贯性,对词汇和修辞表达的预测较弱.
结论:
- 动机是持续表现和感知语言发展的核心条件,在人工智能增强的职业EFL学习中.
- 在以学习为导向的评估中,人工智能反的有效性取决于所感知的可信度,能力提升和职业相关性,而不仅仅是自动化.
- 人工智能驱动的开放式学习可以增强社会经济意识,但它的成功与学习者的动机和在相关的职业环境中的参与交织在一起.
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