Unlocking student potential: How AI-driven personalized feedback shapes goal achievement, self-efficacy, and learning engagement through a self-determination lens

IF 1.7 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation Pub Date : 2025-05-10 DOI:10.1016/j.lmot.2025.102138

Qunai Xu , Yijia Liu , Xue Li

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引用次数: 0

Abstract

This study explores how AI-driven personalized feedback influences goal achievement, self- efficacy, and learning engagement in Chinese college students through a self-determination theory lens. The participants, 1079 Chinese college students (56.2 % female, 43.8 % male; mean age = 21.4), including undergraduates, graduates, and PhD students, came from various academic disciplines. The study examines how personalized AI feedback impacts students’ motivation and academic performance. Data were collected via a questionnaire and analyzed using SPSS (version 27) and AMOS (version 24), employing descriptive statistics, correlation, regression analysis, and structural equation modeling (SEM) to investigate relationships among variables. The results reveal significant positive relationships between AI-driven personalized feedback and students’ goal achievement, academic self-efficacy, and learning engagement. AI feedback enhances students’ clarity of goals, boosts their confidence, and increases their involvement in learning by providing adaptive, personalized support. It fosters a sense of mastery and control, improving both goal achievement and self-efficacy, which subsequently enhances engagement. The study finds that AI-driven feedback is a strong predictor of these outcomes, with more personalized feedback leading to higher levels of motivation, engagement, and confidence. This research underscores the importance of AI-driven personalized feedback in supporting students’ academic success and intrinsic motivation.

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释放学生潜能：人工智能驱动的个性化反馈如何通过自我决定的视角塑造目标实现、自我效能和学习参与

本研究以自我决定理论为视角，探讨人工智能驱动的个性化反馈如何影响中国大学生的目标实现、自我效能和学习投入。参与者为1079名中国大学生(56.2% %女性，43.8% %男性；平均年龄= 21.4岁)，包括本科生、研究生和博士生，来自不同的学科。该研究考察了个性化人工智能反馈如何影响学生的学习动机和学习成绩。采用问卷调查的方式收集数据，使用SPSS （version 27）和AMOS （version 24）软件进行分析，采用描述性统计、相关分析、回归分析和结构方程模型（SEM）分析变量之间的关系。结果显示，人工智能驱动的个性化反馈与学生的目标实现、学业自我效能和学习参与度之间存在显著的正相关关系。人工智能反馈增强了学生对目标的清晰度，增强了他们的信心，并通过提供自适应的个性化支持来提高他们对学习的参与度。它培养了一种掌控感和控制感，提高了目标的实现和自我效能感，从而提高了参与度。研究发现，人工智能驱动的反馈是这些结果的有力预测因素，更个性化的反馈会带来更高水平的动机、参与度和信心。这项研究强调了人工智能驱动的个性化反馈在支持学生学业成功和内在动机方面的重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Learning and Motivation Multiple-

CiteScore

2.90

自引率

0.00%

发文量

期刊介绍： Learning and Motivation features original experimental research devoted to the analysis of basic phenomena and mechanisms of learning, memory, and motivation. These studies, involving either animal or human subjects, examine behavioral, biological, and evolutionary influences on the learning and motivation processes, and often report on an integrated series of experiments that advance knowledge in this field. Theoretical papers and shorter reports are also considered.