Learning and Motivation最新文献_第10页

The low-dose of PDE5 inhibitor, sildenafil, attenuates morphine-induced memory impairment in male mice 低剂量PDE5抑制剂西地那非可减轻吗啡引起的雄性小鼠记忆损伤

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-30 DOI: 10.1016/j.lmot.2025.102181

Adeleh Maleki , Mohammad Amin Manavi , Armin Shirzadian , Ahmad Reza Dehpour

Objectives

The study aimed to evaluate the effect of sildenafil, a phosphodiesterase 5 (PDE5) inhibitor, on morphine (MOR)-induced memory impairment.

Methods

Male mice received morphine (MOR; 3 or 10 mg/kg, i.p.) 30 min before the acquisition phase to induce memory deficits. Sildenafil (1, 2, or 5 mg/kg, i.p.) was administered 15 min after MOR. Memory performance was evaluated using the Y-maze (spatial recognition) and passive avoidance (aversive learning) tasks. To explore underlying mechanisms, naltrexone (NTX; 3 mg/kg, i.p.) and L-NAME (10 mg/kg, i.p.) were administered as an opioid receptor antagonist and nitric oxide synthase inhibitor, respectively. In addition to behavioral tests, hippocampal nitric oxide (NO) levels were measured using the Griess assay, TNF-α and IL-1β were quantified with ELISA, and protein expression of ERK and phosphorylated ERK (p-ERK) was examined by western blotting.

Key findings

A low dose of sildenafil (1 mg/kg) effectively improved spatial recognition memory and learning impaired by MOR (3 mg/kg and 10 mg/kg, respectively). While sildenafil (5 mg/kg) showed no significant benefit, NTX significantly enhanced its effects. Sildenafil also reversed the increased NO and TNF-α levels induced by MOR (3 mg/kg) in the hippocampus. Additionally, MOR (3 mg/kg)-induced memory impairment, linked with decreased p-ERK protein expression in the hippocampus, was significantly mitigated by sildenafil (1 mg/kg).

Conclusions

Learning and memory for spatial recognition are enhanced by low doses of sildenafil. Short-term memory performance is improved by NTX and L-NAME, which counteract the effects of morphine.

目的探讨磷酸二酯酶5 （PDE5）抑制剂西地那非对吗啡（MOR）所致记忆障碍的影响。方法小鼠注射吗啡（MOR； 3或10 mg/kg， ig）。30 在习得阶段前min诱发记忆缺陷。MOR后给予西地那非（1、2或5 mg/kg， i.p） 15 min。记忆表现通过y形迷宫（空间识别）和被动回避（厌恶学习）任务进行评估。为了探索潜在的机制，纳曲酮（NTX; 3 mg/kg, i.p）和L-NAME（10 mg/kg, i.p）分别作为阿片受体拮抗剂和一氧化氮合酶抑制剂给予。除行为学实验外，采用Griess法测定海马一氧化氮（NO）水平，ELISA法测定TNF-α和IL-1β水平，western blotting法检测ERK和磷酸化ERK （p-ERK）蛋白表达。低剂量西地那非（1 mg/kg）可有效改善MOR（3 mg/kg和10 mg/kg）所致的空间识别记忆和学习障碍。虽然西地那非（5 mg/kg）没有明显的益处，但NTX显著增强了其效果。西地那非还能逆转MOR（3 mg/kg）诱导的海马组织NO和TNF-α水平升高。此外，西地那非（1 mg/kg）可显著减轻MOR（3 mg/kg）引起的记忆障碍（与海马中p-ERK蛋白表达降低有关）。结论小剂量西地那非对空间识别的学习记忆有增强作用。NTX和L-NAME可以改善短期记忆，它们可以抵消吗啡的影响。

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引用次数: 0

Linking basic psychological needs, grit, and peace of mind to engagement in AI-assisted language learning: A self-determination theory perspective 将基本的心理需求、勇气和平静的心态与人工智能辅助语言学习联系起来：一个自决理论的视角

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-08-23 DOI: 10.1016/j.lmot.2025.102178

An Qi

As artificial intelligence (AI) becomes increasingly integrated into language education, understanding the psychological mechanisms that influence learner engagement remains underexplored. This study draws on Self-Determination Theory to examine how basic psychological needs influence grit, peace of mind, and engagement in AI-assisted language learning. A quantitative research design was employed using validated survey instruments administered to English as a Foreign Language learners with AI-based classroom experience. Structural equation modeling was used to analyze the data and test both direct and mediated relationships. Results showed that the satisfaction of autonomy, competence, and relatedness significantly predicted learners’ grit and peace of mind. Both grit and peace of mind, in turn, positively influenced engagement. Additionally, basic psychological needs had a strong direct effect on engagement. These results highlight the importance of designing AI-assisted learning environments that support learners’ psychological and emotional needs, ultimately fostering more sustained and self-determined engagement.

随着人工智能（AI）越来越多地融入语言教育，对影响学习者参与的心理机制的理解仍未得到充分探索。本研究利用自我决定理论来研究基本心理需求如何影响人工智能辅助语言学习中的毅力、内心平静和参与度。定量研究设计采用了有效的调查工具，对英语作为一门外语的学习者进行了基于人工智能的课堂体验。采用结构方程模型对数据进行分析，检验直接关系和中介关系。结果表明，自主性满意度、能力满意度和相关性满意度显著预测了学习者的毅力和平和心态。勇气和内心的平静反过来又对参与度产生积极影响。此外，基本的心理需求对参与度有强烈的直接影响。这些结果强调了设计支持学习者心理和情感需求的人工智能辅助学习环境的重要性，最终促进更持久和自主的参与。

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引用次数: 0

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