Learning and Motivation最新文献_第7页

Understanding user stickiness in GAI-IDLE platforms: Insights from self-determination theory 理解ai - idle平台中的用户粘性：来自自我决定理论的见解

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-23 DOI: 10.1016/j.lmot.2025.102179

Guanqiong Zhou , Qianghe Ma

Amidst the accelerating progress of generative artificial intelligence (GenAI), the rise of GenAI-assisted informal digital English learning (GAI-IDLE) platforms has prompted growing scholarly interest in understanding the psychological mechanisms that drive sustained learner engagement. Grounded in Self-Determination Theory (SDT), this study investigates how GAI-IDLE fosters user stickiness among Chinese university students by focusing on the psychological needs that influence intrinsic motivation. The constructs of perceived ease of use, perceived usefulness, control, and flow experience are interpreted within this motivational framework to reveal how learners’ internal psychological states influence their long-term engagement with GenAI-integrated learning environments. Guided by SDT, a survey was conducted with 669 participants, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via Smart PLS 4.0. Empirical findings demonstrate that GAI-IDLE significantly promotes user stickiness through both direct and indirect pathways. Notably, control (β = 0.440, p < 0.001) and flow experience (β = 0.180, p < 0.001) emerged as strong mediators, underscoring the centrality of learner autonomy and immersive experiences in sustaining engagement. While perceived ease of use showed a moderate positive association, perceived usefulness did not exert a significant effect, suggesting that affective and experiential dimensions may be more critical than utilitarian perceptions in motivating continued use. The study highlights the need for GAI-IDLE platforms to foster intrinsic motivation and sustain meaningful engagement.

随着生成式人工智能（GenAI）的加速发展，GenAI辅助的非正式数字英语学习（ai - idle）平台的兴起，促使学术界对理解驱动持续学习者参与的心理机制产生了越来越大的兴趣。本研究以自我决定理论（Self-Determination Theory， SDT）为基础，通过关注影响内在动机的心理需求，探讨了ai - idle如何培养中国大学生的用户粘性。感知易用性、感知有用性、控制和心流体验的构念在这个动机框架中得到解释，以揭示学习者的内部心理状态如何影响他们与genai集成学习环境的长期参与。在SDT的指导下，对669名参与者进行了调查，并通过Smart PLS 4.0使用偏最小二乘结构方程模型（PLS- sem）对数据进行分析。实证结果表明，ai - idle通过直接和间接途径显著促进用户粘性。值得注意的是，控制（β = 0.440, p <； 0.001）和心流体验（β = 0.180, p <； 0.001）成为强大的中介，强调了学习者自主和沉浸式体验在持续参与中的中心地位。虽然感知易用性表现出适度的正相关，但感知有用性并没有产生显著的影响，这表明情感和经验维度在激励持续使用方面可能比实用主义感知更重要。该研究强调了ai - idle平台培养内在动机和维持有意义的参与的必要性。

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引用次数: 0

Interest and mind wandering: How do individual and situational characteristics impact learning? 兴趣和走神：个人和情境特征如何影响学习？

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-18 DOI: 10.1016/j.lmot.2025.102177

Louise Perche, Nora Yennek, Laure Léger

This research examines the impact of individual and situational characteristics on mind wandering and interest on learning. Mind wandering is an attentional internal distraction that is deleterious to one’s performance in sustained attention tasks (Cheyne et al., 2009) and in learning (Szpunar et al., 2013). First, two studies were conducted to validate a mind wandering scale in French (with a trait and a state dimension)—both in ecological and in laboratory settings (studies 1 and 2). Then, an experiment was conducted to induce mind wandering and explore the link between individual and situational characteristics of interest and their impact on learning (Study 3). Interest was gauged using a self-reported scale. Mind wandering was measured both by probe-caught measures and self-reported scales. The main results suggest that mind wandering mediates the link between individual interest and situational interest and that a mind wandering state and situational interest jointly influence learning scores.

本研究考察了个体特征和情境特征对走神和学习兴趣的影响。走神是一种注意力的内部分散，不利于一个人在持续注意力任务中的表现（Cheyne et al., 2009）和学习（Szpunar et al., 2013）。首先，进行了两项研究，以验证法语的走神量表（具有特征和状态维度）-在生态和实验室环境中（研究1和2）。然后，通过诱导走神实验，探讨兴趣的个体特征和情境特征之间的联系及其对学习的影响（研究3）。兴趣是用自我报告的量表来衡量的。走神的测量方法包括探针捕捉法和自我报告量表。结果表明，走神在个体兴趣和情境兴趣之间起中介作用，走神状态和情境兴趣共同影响学习成绩。

引用次数: 0

Artificial intelligence tools: Improvement of motivation, psychological well-being, and psychological capital of EFL learners: A self-determination theory perspective 人工智能工具：自我决定理论视角下英语学习者动机、心理健康和心理资本的提升

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-16 DOI: 10.1016/j.lmot.2025.102169

Weiwei Dou , Xueyu Sun

The incorporation of artificial intelligence (AI) in educational settings has attracted considerable interest from scholars, specifically in English as a Foreign Language (EFL) education. While prior research has explored AI’s instructional benefits, limited attention has been given to its impact on learners’ emotional and psychological dimensions—specifically motivation, psychological well-being (PWB), and psychological capital (PsyCap). This research examines the influence of AI tools on the motivation, PWB, and PsyCap of EFL students. To evaluate these effects, a pre-test was administered utilizing three validated scales that measure motivation, PWB, and PsyCap. After this initial evaluation, subjects were assigned to two groups, namely, receiving traditional instruction and participating in AI-based instructional methods. After the instructional sessions, both groups completed a post-test using the same questionnaires to assess alterations in the three variables. The data gathered from the pre-test and post-test were analyzed using Analysis of Covariance (ANCOVA), which indicated that there were notable differences in the post-test scores between the two groups concerning positive motivation, PsyCap, and PWB. Particularly, the integration of AI tools was found to markedly improve students' motivation, PWB, and PsyCap. These results suggest that AI tools not only boost language acquisition but also contribute meaningfully to learners' motivation and PsyCap. Implications include the need for educators and policymakers to consider AI integration not just for academic outcomes, but for cultivating emotionally supported learning environments in EFL contexts.

人工智能（AI）在教育环境中的应用引起了学者们的极大兴趣，特别是在英语作为外语（EFL）教育领域。虽然之前的研究已经探索了人工智能的教学益处，但对其对学习者情感和心理维度的影响的关注有限，特别是动机、心理健康（PWB）和心理资本（PsyCap）。本研究考察了人工智能工具对英语学生的动机、PWB和心理cap的影响。为了评估这些影响，使用三个有效的测量动机、PWB和PsyCap的量表进行了预测试。初步评估后，受试者被分为两组，接受传统教学和参与基于人工智能的教学方法。在教学课程结束后，两组都使用相同的问卷完成了一个后测，以评估这三个变量的变化。采用协方差分析（ANCOVA）对前测和后测数据进行分析，结果表明，两组在积极动机、心理cap和PWB方面的后测得分存在显著差异。特别是，人工智能工具的整合被发现显著提高了学生的动机、PWB和PsyCap。这些结果表明，人工智能工具不仅促进了语言习得，而且对学习者的动机和心理cap有意义的贡献。这意味着教育工作者和政策制定者需要考虑人工智能的整合，不仅要考虑学术成果，还要考虑在英语背景下培养情感支持的学习环境。

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引用次数: 0

EFL students’ writing engagement and AI attitude in GenAI-assisted contexts: A mixed-methods study grounded in SDT and TAM 基因辅助语境下英语学生的写作投入和人工智能态度：基于SDT和TAM的混合方法研究

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-14 DOI: 10.1016/j.lmot.2025.102168

Lei Shen , Siyi Wang , Yihang Xin

While engagement has been widely recognized as a key factor in improving students’ learning outcomes, the role of attitudes toward generative artificial intelligence (GenAI) in shaping engagement, particularly in the context of writing, remains underexplored. Grounded in self-determination theory (SDT) and the technology acceptance model (TAM), the present study employs latent profile analysis (LPA), a person-centered approach that identifies distinct profiles of EFL learners’ engagement in GenAI-assisted writing. A one-way ANOVA is subsequently conducted to examine whether students’ attitudes toward GenAI differed across these engagement profiles. In addition, semi-structured interviews are conducted to investigate university teachers’ perceptions of how GenAI can enhance students’ writing engagement. The LPA identifies three engagement profiles as high engagement (31.9 %), medium engagement (50.8 %), and low engagement (17.3 %). However, GenAI attitude did not show a significant relationship with writing engagement. Qualitative findings indicate that teachers are aware of GenAI’s potential in improving students’ behavioral, emotional, and cognitive engagement, though few have actively integrated such tools into their teaching. This study offers new insights into the relationship between writing engagement and GenAI attitudes. It provides practical implications for students, instructors, and educational institutions seeking to implement GenAI technologies in English as a foreign language (EFL) learning and teaching.

虽然参与度已被广泛认为是提高学生学习成果的关键因素，但对生成式人工智能（GenAI）的态度在塑造参与度方面的作用，特别是在写作方面，仍未得到充分探讨。本研究以自我决定理论（SDT）和技术接受模型（TAM）为基础，采用潜在特征分析（LPA），这是一种以人为中心的方法，可以识别出英语学习者参与基因人工智能辅助写作的不同特征。随后进行了单向方差分析，以检查学生对GenAI的态度是否在这些参与概况中有所不同。此外，还进行了半结构化访谈，以调查大学教师对GenAI如何提高学生写作参与度的看法。LPA确定了三种参与度概况：高参与度（31.9 %），中等参与度（50.8 %）和低参与度（17.3 %）。然而，GenAI态度与写作投入没有显著的关系。定性研究结果表明，教师意识到GenAI在提高学生行为、情感和认知参与方面的潜力，尽管很少有人积极地将这些工具整合到他们的教学中。这项研究为写作投入和GenAI态度之间的关系提供了新的见解。它为寻求在英语作为外语（EFL）的学习和教学中实施GenAI技术的学生、教师和教育机构提供了实际意义。

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引用次数: 0

Role of spatial memory in spatial design: A systematic review 空间记忆在空间设计中的作用：系统回顾

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-13 DOI: 10.1016/j.lmot.2025.102166

M.N.R. Wijetunge, D.W. Kasun Gayantha, T. Chandrasekera

Spatial memory plays a pivotal role in spatial design, influencing both academic and professional achievements. However, while individual studies have explored spatial memory in spatial design, the literature lacks comprehensive reviews that holistically examine its impact across multiple dimensions of spatial design. This systematic review addresses this gap by analyzing nine studies from three prominent scientific databases. Five key aspects of spatial design significantly influenced by spatial memory were identified: spatial knowledge, visualization, spatial text, problem-solving, planning, and geometry processing. Additionally, 11 spatial memory testing instruments were classified based on their unique mechanisms for encoding and retrieving spatial information. The review highlights the need for validated, discipline-specific spatial memory tests tailored to architecture and interior design. The findings provide actionable insights for educators, emphasizing the integration of spatial memory in teaching methodologies to enhance spatial design skills. By bridging fragmented findings, this review offers a foundational framework for future research to advance the design process through enhanced spatial memory capabilities.

空间记忆在空间设计中起着举足轻重的作用，影响着人们的学术成就和专业成就。然而，虽然个别研究探索了空间设计中的空间记忆，但文献缺乏对其在空间设计多个维度上的影响进行全面考察的综合综述。本系统综述通过分析来自三个著名科学数据库的九项研究来解决这一差距。空间记忆显著影响空间设计的五个关键方面：空间知识、可视化、空间文本、问题解决、规划和几何处理。此外，根据11种空间记忆测试工具独特的空间信息编码和检索机制，对它们进行了分类。这篇综述强调了为建筑和室内设计量身定制的经过验证的、特定学科的空间记忆测试的必要性。研究结果为教育工作者提供了可操作的见解，强调了空间记忆在教学方法中的整合，以提高空间设计技能。通过衔接零散的研究结果，本综述为未来的研究提供了一个基础框架，通过增强空间记忆能力来推进设计过程。

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引用次数: 0

Exploring the impact of AI-driven emotional resilience on academic persistence, motivation, cognitive flexibility, and autonomy in self-regulated learning: A self-determination theory perspective 探讨人工智能驱动的情绪弹性对自我调节学习中的学习持久性、动机、认知灵活性和自主性的影响：自决理论视角

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-11 DOI: 10.1016/j.lmot.2025.102167

Kaifang Deng , Xiaozhou Chen

This study explores the impact of AI-driven emotional resilience on academic persistence, motivation, cognitive flexibility, and autonomy in self-regulated learning from a Self-Determination Theory perspective. A total of 534 Chinese students, including 390 females (73 %) and 144 males (27 %), with an average age of 19.38 years, participated in the study. The sample comprised 97.3 % undergraduate students, with a minor representation of master’s and doctoral students. The participants, drawn from diverse academic disciplines such as Medicine, Law, and Literature, provided self-assessments on their emotional resilience, academic persistence, motivation, cognitive flexibility, and autonomy in self-regulated learning. Data were analyzed using SPSS (version 27) for statistical analyses, including descriptive statistics, correlation, and regression, while structural equation modeling (SEM) in AMOS (version 24) was employed to assess the complex relationships between variables. The findings reveal significant positive relationships between AI-enhanced emotional resilience and the aforementioned academic traits. AI-driven environments, offering personalized feedback and adaptive pathways, bolster emotional resilience by reducing frustration and enhancing students’ confidence. This, in turn, improves academic persistence, motivation, and cognitive flexibility. Additionally, AI tools that foster self-reflection and autonomy further enhance self-regulation. The results indicate that academic persistence, motivation, cognitive flexibility, and perceived autonomy are strong predictors of emotional resilience, suggesting that students demonstrating these traits are better equipped to navigate academic challenges and maintain emotional balance. This study highlights the potential of AI-driven environments in promoting emotional resilience and supporting students’ academic success through enhanced self-regulated learning capabilities.

本研究从自我决定理论的角度探讨了人工智能驱动的情绪弹性对自我调节学习的学习持久性、动机、认知灵活性和自主性的影响。共有534名中国学生参与研究，其中女生390人（占73% %），男生144人（占27% %），平均年龄19.38岁。样本包括97.3% %的本科生，还有少量的硕士和博士生。参与者来自医学、法律和文学等不同学科，他们对自己的情绪弹性、学习持久性、动机、认知灵活性和自我调节学习的自主性进行了自我评估。数据采用SPSS （version 27）进行统计分析，包括描述性统计、相关分析和回归分析，采用AMOS （version 24）中的结构方程模型（SEM）评估变量之间的复杂关系。研究结果显示，人工智能增强的情绪弹性与上述学术特征之间存在显著的正相关关系。人工智能驱动的环境，提供个性化的反馈和自适应途径，通过减少挫折和增强学生的信心来增强情绪弹性。这反过来又提高了学习的持久性、动力和认知的灵活性。此外，促进自我反思和自主的人工智能工具进一步增强了自我监管。结果表明，学业坚持、动机、认知灵活性和感知自主性是情绪弹性的强预测因子，表明表现出这些特征的学生更能应对学业挑战并保持情绪平衡。这项研究强调了人工智能驱动的环境在通过增强自我调节学习能力来促进情绪弹性和支持学生学业成功方面的潜力。

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引用次数: 0

Perceived teacher support on international students’ engagement and psychological well-being in AI-based learning: The mediating role of motivation through the lens of self-determination theory 感知教师支持对国际学生人工智能学习投入和心理健康的影响：自我决定理论视角下动机的中介作用

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-01 DOI: 10.1016/j.lmot.2025.102165

Shujiao Chen

As artificial intelligence (AI) continues to reshape educational practices, higher education institutions are incorporating AI tools to modernize instructional techniques and boost learner success. This paradigm shift has highlighted the importance of engagement and psychological well-being (PWB) in academic research, addressing the challenges learners encounter in AI-enhanced environments. Both external factors, like teacher support, and internal factors, such as motivation, play crucial roles in the learning process. Guided by Self-determination theory (SDT), this study seeks to explore the influence of teacher support on promoting learner engagement and PWB, considering the possible mediating effects of learners’ motivation in AI-based contexts. For this purpose, data were gathered from 442 international overseas students across various academic disciplines in Chinese colleges, utilizing Structural Equation Modeling (SEM) to assess the measurement model and conducting multiple regression analyses. The results indicate that perceived teacher support positively predicts both engagement and PWB, with motivation serving as a significant mediating variable. This finding suggests that motivation acts as a psychological bridge between external instructional support and internal learning experiences in AI contexts. Moreover, AI-driven features—such as personalized prompts and adaptive feedback—may amplify or complement traditional sources of support, offering new pathways for student empowerment. This study contributes to the literature by contextualizing SDT within AI-mediated education and demonstrating how hybrid support systems—human and algorithmic—shape learner outcomes. Implications for instructional design and teacher training are discussed, including the need to align emotional support strategies with AI analytics to personalize learning and foster positive academic experiences.

随着人工智能（AI）继续重塑教育实践，高等教育机构正在将人工智能工具纳入教学技术的现代化和提高学习者的成功。这种范式转变突出了学术研究中参与和心理健康（PWB）的重要性，解决了学习者在人工智能增强环境中遇到的挑战。外部因素（如教师支持）和内部因素（如动机）在学习过程中都起着至关重要的作用。在自我决定理论（SDT）的指导下，本研究旨在探讨教师支持对促进学习者投入和PWB的影响，并考虑人工智能情境下学习者动机可能的中介作用。为此，本研究收集了442名中国高校不同学科的国际留学生的数据，利用结构方程模型（SEM）对测量模型进行评估，并进行多元回归分析。结果表明，教师支持感知正向预测敬业度和PWB，动机是显著的中介变量。这一发现表明，在人工智能环境中，动机在外部教学支持和内部学习体验之间起着心理桥梁的作用。此外，人工智能驱动的功能——如个性化提示和自适应反馈——可能会扩大或补充传统的支持来源，为学生赋权提供新的途径。本研究通过将SDT置于人工智能介导的教育环境中，并展示了混合支持系统-人类和算法-如何塑造学习者的结果，从而为文献做出了贡献。讨论了对教学设计和教师培训的影响，包括将情感支持策略与人工智能分析相结合的必要性，以个性化学习和培养积极的学术体验。

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引用次数: 0

Examining longitudinal development of writing motivation in the GenAI context: A self-determination theory perspective 自我决定理论视角下的写作动机纵向发展研究

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-07-29 DOI: 10.1016/j.lmot.2025.102157

Mark Feng Teng

This longitudinal study examines the development of motivation among a sample of 261 Chinese EFL student writers in generative AI (GenAI)-supported writing contexts through the lens of Self-Determination Theory (SDT). Using three-wave data collection, the focus was on how GenAI influences four key motivational constructs: autonomy, competence, relatedness, and identified regulation, and the developmental trajectory of motivation over time. Results from mixed-effects modeling reveal significant time and group interactions, demonstrating that GenAI use leads to substantial motivational gains over time. The results from Gradient Boosting Machine for Time Series (GBMT) indicated that the EFL learners’ motivation development follows curvilinear trajectories, characterized by rapid initial growth that gradually plateaus. Theoretically, the findings extend SDT’s application to AI-mediated learning by demonstrating how GenAI scaffolds psychological needs: fostering competence through adaptive feedback, autonomy via personalized support, and relatedness and identified regulation through simulated social interaction. The study contributes to emerging discourse on technology-enhanced motivation while highlighting the need for proficiency-sensitive implementation strategies in EFL writing contexts.

本纵向研究通过自我决定理论（SDT）的视角，考察了261名中国英语学生在生成式人工智能（GenAI）支持的写作环境中写作动机的发展。使用三波数据收集，重点关注基因ai如何影响四个关键动机结构：自主性、能力、相关性和识别调节，以及动机随时间的发展轨迹。混合效应模型的结果揭示了显著的时间和群体互动，表明GenAI的使用随着时间的推移会带来可观的动机收益。时间序列梯度增强机（GBMT）的结果表明，英语学习者的动机发展遵循曲线轨迹，其特征是最初的快速增长逐渐趋于平稳。从理论上讲，研究结果通过展示GenAI如何支撑心理需求，将SDT的应用扩展到人工智能介导的学习：通过适应性反馈培养能力，通过个性化支持培养自主性，以及通过模拟社会互动培养相关性和识别性调节。该研究促进了关于技术增强动机的新兴论述，同时强调了在英语写作环境中需要熟练度敏感的实施策略。

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引用次数: 0

Three decades of neurofeedback in motor behavior research: A systematic review in healthy young adults 运动行为研究的三十年神经反馈：对健康年轻人的系统回顾

IF 1.7 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-07-18 DOI: 10.1016/j.lmot.2025.102163

Lucas Eduardo Antunes Bicalho , Beatriz Couto-Fortuna , Lidiane Aparecida Fernandes , Joana Andrade Ramalho Pinto , Guilherme Menezes Lage

Neurofeedback is a promising tool for enhancing motor behavior by integrating optimal brain states into practice. This scoping review systematically mapped the available evidence on the effects of neurofeedback on motor performance in healthy young adults. Literature searches were conducted in PubMed, Scopus, and Web of Science in January 2023, covering studies published from 1990 to 2023. Of the 5271 records screened, 43 studies met the inclusion criteria, involving over 1290 participants. These studies yielded a total of 56 protocol-specific analyses. Among them, 25 did not incorporate motor practice into the neurofeedback protocol, relying solely on a pretest-posttest design. Eleven analyses included practice sessions prior to neurofeedback, while nine delivered neurofeedback during motor execution. The findings revealed that many studies have overlooked established behavioral principles when designing neurofeedback interventions. Basic methodological aspects, such as sex differences, laterality, and the assessment of learning, were often neglected. Furthermore, evidence regarding the effectiveness of neurofeedback for enhancing motor learning remains limited. The quality of studies examining various motor tasks, including visuomotor adaptation, sequential movement execution, and temporal performance, was predominantly low to moderate. These shortcomings underscore the need for more rigorous and behaviorally informed approaches in future research.

神经反馈是一种很有前途的工具，通过将最佳大脑状态整合到实践中来增强运动行为。本综述系统地绘制了关于神经反馈对健康年轻人运动表现影响的现有证据。文献检索于2023年1月在PubMed、Scopus和Web of Science中进行，涵盖1990年至2023年发表的研究。在筛选的5271份记录中，有43项研究符合纳入标准，涉及1290多名参与者。这些研究共产生了56项具体方案分析。其中25人没有将运动练习纳入神经反馈方案，仅仅依靠前测后测设计。11项分析包括在神经反馈之前的练习，而9项分析在运动执行期间提供神经反馈。研究结果表明，许多研究在设计神经反馈干预措施时忽视了既定的行为原则。基本的方法方面，如性别差异、侧边性和学习的评估，往往被忽视。此外，关于神经反馈对增强运动学习的有效性的证据仍然有限。检查各种运动任务的研究质量，包括视觉运动适应、顺序运动执行和时间表现，主要是低到中等。这些缺点强调了在未来的研究中需要更严格和行为知情的方法。

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引用次数: 0

Investigating Chinese English learners’ readiness for Artificial Intelligence (AI) technologies: A theory of planned behavior (TPB) perspective 中国英语学习者对人工智能（AI）技术的准备程度调查：计划行为理论视角

IF 1.7 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-07-15 DOI: 10.1016/j.lmot.2025.102164

Huan Zhang

With a rapid shift toward the use of Artificial Intelligence (AI) technologies in various aspects of human life and career, second and foreign language (L2) educators and practitioners highlighted AI readiness and literacy for students to succeed in learning English. However, there is insufficient empirical evidence on how much Chinese English as a foreign language (EFL) students are ready to accept and implement AI tools in their L2 learning. To address this gap, drawing on theory of planned behavior (TPB), the present quantitative study employed a survey with 283 EFL students from different Chinese universities. The results of a one-sample t-test and descriptive statistics revealed that Chinese EFL students had demonstrated an above-average level of AI readiness in their L2 education reflecting the three dimensions of TPB (i.e., attitudes, subjective norms, and perceived behavioral control) through an emphasis on positive attitudes towards and intentions to adopt AI tools. They also showed higher than average scores in three sub-factors of AI readiness (i.e., ethics, ability, and vision). Only the cognitive dimension was below the average point. The results are discussed in relation to TPB and practical implications are provided for EFL students and teachers to maintain and develop their level of AI readiness in the context of L2 education.

随着人工智能（AI）技术在人类生活和职业的各个方面的迅速转变，第二语言和外语（L2）教育者和从业者强调了人工智能的准备和素养，以帮助学生成功学习英语。然而，关于中国英语作为外语（EFL）的学生在他们的第二语言学习中准备接受和实施人工智能工具的程度，尚无足够的实证证据。为了解决这一问题，本研究运用计划行为理论，对283名来自中国不同大学的英语学生进行了调查。单样本t检验和描述性统计的结果显示，中国英语学生在第二语言教育中表现出高于平均水平的人工智能准备，这反映了TPB的三个维度（即态度、主观规范和感知行为控制），强调对人工智能工具的积极态度和意图。在人工智能准备程度的3个子因素（道德、能力、愿景）中，他们的得分也高于平均水平。只有认知维度低于平均水平。本文讨论了与TPB相关的结果，并为英语学生和教师在第二语言教育背景下保持和发展他们的人工智能准备水平提供了实际意义。

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引用次数: 0