Learning and Motivation最新文献_第6页

Digital educational game design: Music, speed, colour and collectible item 数字教育游戏设计：音乐、速度、颜色和可收集物品

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-16 DOI: 10.1016/j.lmot.2025.102186

Zeynep Cömert , Yavuz Samur

The objective of this research was to ascertain the optimal construction of design elements independent of learning content, such as colour, sound, the number of items collected, and speed, in educational games. The study involved a voluntary sample of 7th-grade students. Four distinct versions of an educational game designed to teach fractions were developed, each featuring a unique combination of auditory, visual, and interactive elements. While these variations differed in terms of their audio, visual presentation, number of addable items, and pace, they all retained the same core educational content. The students were randomly assigned to groups and completed a pre-test on fractions using tablets. Subsequently, the participants engaged with the game and completed a post-test, which assessed their knowledge, cognitive load, and flow experience. The findings indicated that background music increased cognitive load but enhanced achievement and cognitive process. Faster gameplay reduced student achievement and cognitive load but supported flow experience. An increase in the number of collectible items had a negative impact on achievement scores and raised cognitive load, but did not affect flow experience Regarding colour, games with pale colour palettes were associated with higher achievement scores and better flow experiences compared to vivid colour designs, although colour did not substantially affect cognitive load. These results offer insights into optimizing multimedia design features in educational games to better balance engagement and learning efficiency.

这项研究的目的是确定独立于学习内容的设计元素的最佳结构，如教育游戏中的颜色、声音、收集的物品数量和速度。这项研究涉及七年级学生的自愿样本。开发了四种不同版本的教育游戏，旨在教授分数，每个版本都具有听觉，视觉和互动元素的独特组合。虽然这些变体在音频、视觉呈现、可添加道具数量和节奏方面有所不同，但它们都保留了相同的核心教育内容。学生们被随机分配到不同的小组，并使用药片完成分数的预测试。随后，参与者参与游戏并完成后测，评估他们的知识、认知负荷和心流体验。研究结果表明，背景音乐增加了认知负荷，但提高了成绩和认知过程。更快的游戏玩法降低了学生的成绩和认知负荷，但支持了心流体验。关于颜色，与鲜艳的颜色设计相比，带有浅色配色的游戏具有更高的成就分数和更好的心流体验，尽管颜色并不会对认知负荷产生实质性影响。这些结果为优化教育类游戏的多媒体设计功能，更好地平衡用户粘性和学习效率提供了见解。

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引用次数: 0

Enhancing Chinese EFL University Students’ self-regulated learning through AI chatbot intervention: Insights from achievement goal theory AI聊天机器人干预促进中国大学生英语自主学习：来自成就目标理论的启示

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-15 DOI: 10.1016/j.lmot.2025.102191

Juan Gu , Quanyong Liu

This study explores the impact of AI chatbot-supported instruction on university students’ self-regulated learning (SRL) behaviors in English as a Foreign Language (EFL) contexts through the lens of Achievement Goal Theory (AGT). Adopting a mixed-methods quasi-experimental design with both quantitative (ANCOVA) and qualitative (thematic analysis) components, the research involved 62 first-year students from a Chinese university, with one group receiving teacher-guided chatbot intervention and the other engaging in regular instruction. Quantitative results revealed significant improvements in goal setting, task strategies, and time management among students in the experimental group, while showing minimal or negative change in environment structuring, help seeking, and self-evaluation. Thematic analysis of post-intervention interviews indicated that students perceived the chatbot as enhancing planning efficiency and task engagement, though concerns of over-reliance and reduced reflection emerged. Interpreted through AGT, the study contributes to theoretical understandings of motivation in AI-assisted education and offers practical insights for designing pedagogically guided chatbot interventions in EFL learning environments.

本研究通过成就目标理论（AGT）的视角，探讨了人工智能聊天机器人支持下的教学对大学生英语自我调节学习行为的影响。采用定量（ANCOVA）和定性（主题分析）相结合的混合方法准实验设计，该研究涉及来自中国一所大学的62名一年级学生，其中一组接受教师引导的聊天机器人干预，另一组接受常规教学。定量结果显示实验组学生在目标设定、任务策略和时间管理方面有显著改善，而在环境结构、寻求帮助和自我评价方面则表现出微小或消极的变化。干预后访谈的专题分析表明，学生认为聊天机器人提高了计划效率和任务参与度，尽管出现了过度依赖和反思减少的担忧。通过AGT的解释，该研究有助于对人工智能辅助教育动机的理论理解，并为在英语学习环境中设计教学指导的聊天机器人干预提供实践见解。

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引用次数: 0

How do basic psychological needs evolve in AI-assisted EFL learning? A longitudinal study of Chinese university students grounded in Self-Determination Theory 在人工智能辅助的英语学习中，基本心理需求是如何演变的？基于自我决定理论的中国大学生纵向研究

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-13 DOI: 10.1016/j.lmot.2025.102193

Yajing Fu , Ying Chen

The integration of artificial intelligence (AI) into English as a Foreign Language (EFL) education offers new opportunities for enhancing learner motivation, yet little is known about how students’ psychological needs evolve in such environments over time. Grounded in Self-Determination Theory, this longitudinal study investigated the developmental trajectories of three basic psychological needs (autonomy, competence, and relatedness) among Chinese university students engaged in AI-assisted EFL learning. A total of 313 students completed surveys at three time points over one semester. Descriptive statistics and multivariate latent growth curve modeling were employed to examine both individual growth patterns and interrelations among the needs. Results revealed significant positive growth in all three needs, with autonomy showing the largest increase. Intercept-level covariances indicated that students with higher initial satisfaction in one need also tended to score higher in others. Slope-level correlations demonstrated partial synchrony, particularly between autonomy and relatedness. These findings highlight the dynamic and interconnected nature of motivational development in AI-enhanced language learning contexts. They also underscore the potential of thoughtfully integrated AI tools to support students’ autonomy, competence, and relatedness, offering both theoretical insights into motivation development and practical implications for instructional design in digital language learning environments.

人工智能（AI）与英语作为外语（EFL）教育的整合为增强学习者的动机提供了新的机会，但人们对这种环境下学生的心理需求如何随着时间的推移而演变知之甚少。本研究以自我决定理论为基础，考察了中国大学生在人工智能辅助英语学习中的三种基本心理需求（自主性、能力和关联性）的发展轨迹。共有313名学生在一个学期的三个时间点完成了调查。采用描述性统计和多变量潜在增长曲线模型来检验个体增长模式和需求之间的相互关系。结果显示，这三种需求都有显著的正增长，其中自主性增长最大。截距水平协方差表明，在一种需求上初始满意度较高的学生在其他需求上的得分也较高。斜率相关性显示出部分同步性，特别是在自主性和相关性之间。这些发现强调了在人工智能增强的语言学习环境中，动机发展的动态和相互联系的本质。他们还强调了精心集成的人工智能工具的潜力，以支持学生的自主性、能力和相关性，为数字语言学习环境中的教学设计提供了动机发展的理论见解和实践意义。

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引用次数: 0

Changing background music is sufficient to disrupt reversal learning: Evidence from an ABC renewal design 改变背景音乐足以扰乱逆向学习：来自ABC更新设计的证据

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-13 DOI: 10.1016/j.lmot.2025.102190

Sahar Aghajari, Harald Lachnit, Metin Üngör

The present study investigated whether musical stimuli can acquire contextual control over anticipatory responses to visual cues. Specifically, we tested whether merely changing the background music that was present during reversal learning would be sufficient to disrupt reversal performance, using an ABC renewal paradigm. In each of two human predictive learning experiments, participants first learned to discriminate between two cues (X + , Y−) in one musical context (Context A), followed by reversal learning (X − , Y+) in a second musical context (Context B). In a subsequent test phase, cues were presented in a third musical context (Context C). In Experiment 1, Context C was novel to the participants when introduced during testing. In Experiment 2, Context C was matched with the reversal context in terms of familiarity and learning history. That is, prior to testing, Context C had served as the reversal context for another pair of cues (W, Z). In both experiments, presentations of the cues in Context C - outside their corresponding reversal context - disrupted reversal learning in the direction of initial learning. Our findings demonstrate the utility of musical stimuli as contexts in human learning paradigms. Theoretical and practical implications are discussed.

本研究探讨了音乐刺激是否能够获得对视觉线索的预期反应的语境控制。具体来说，我们使用ABC更新范式测试了仅仅改变反转学习期间出现的背景音乐是否足以破坏反转表现。在两个人类预测学习实验中，参与者首先学会了在一个音乐背景（背景A）中区分两个线索（X + ，Y−），然后在第二个音乐背景（背景B）中进行反向学习（X − ，Y+）。在随后的测试阶段，线索被呈现在第三个音乐背景中（背景C）。在实验1中，情境C对被试来说是新奇的。在实验2中，情境C与反转情境在熟悉度和学习历史上是匹配的。也就是说，在测试之前，情境C已经作为另一对线索（W， Z）的反转情境。在这两个实验中，情境C中提示的呈现——在其相应的反转情境之外——在初始学习的方向上扰乱了反转学习。我们的研究结果证明了音乐刺激在人类学习范式中作为语境的效用。讨论了理论和实践意义。

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引用次数: 0

The roles of need frustration and regulatory focus in conspiratorial thinking 需求挫败感和监管焦点在阴谋思维中的作用

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-12 DOI: 10.1016/j.lmot.2025.102188

Matthew Hunsinger , Michael Parker

Research on conspiratorial thinking suggests that conspiracy theories can arise because of several motivational and cognitive processes. Using self-determination theory as our theoretical framework, we propose that basic psychological need threat is a precursor to these beliefs through regulatory focus. We tested this hypothesis with one correlational study (N = 275) and one experiment (N = 334), which suggested that prevention focus mediated the relationship between need frustration (autonomy, competence, and relatedness) and conspiratorial thinking. Our results are in line with motivational approaches to understanding the antecedents of conspiratorial beliefs and offer additional theoretical specificity regarding the nature of the relationship between need threat and conspiratorial thinking. Implications and future testable hypotheses are discussed.

对阴谋论思维的研究表明，阴谋论的产生是由于几个动机和认知过程。以自我决定理论为理论框架，我们提出基本心理需求威胁是通过调节焦点形成这些信念的前兆。我们通过一项相关研究（N = 275）和一项实验（N = 334）验证了这一假设，结果表明，预防焦点介导了需求挫折（自主性、能力和亲缘性）与阴谋思维之间的关系。我们的研究结果与理解阴谋信念前因的动机方法一致，并为需求威胁与阴谋思维之间关系的本质提供了额外的理论特异性。讨论了影响和未来可检验的假设。

引用次数: 0

Exploring learning uncertainty and test anxiety with mindfulness as a mediator in EFL students: An Expectancy-Value Approach 正念对英语学生学习不确定性和考试焦虑的中介作用：期望-价值方法

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-12 DOI: 10.1016/j.lmot.2025.102189

Genhua Chang , Shamim Akhter , Chaohai Lin

Learning uncertainty and test anxiety represent significant challenges for English as a Foreign Language (EFL) learners, potentially hindering academic progress and fostering negative learning experiences. While research has established links between these constructs, the mediating role of mindfulness, particularly within the framework of an Expectancy-Value Approach, remains underexplored in the EFL context. This study addressed this gap by investigating the relationships between learning uncertainty, test anxiety, and mindfulness among a sample of 532, including 215 (40.4 %) male and 317 (59.6 %) female participants in China. Participants were recruited through stratified random sampling and completed a series of validated self-report questionnaires. Structural Equation Modelling (SEM) analysis revealed a positive and significant correlation between learning uncertainty and test anxiety, indicating that higher levels of uncertainty were associated with increased anxiety. Conversely, a negative and significant correlation was found between learning uncertainty and mindfulness, and between mindfulness and test anxiety. Additionally, SEM analysis confirmed that mindfulness significantly mediated the relationship between learning uncertainty and test anxiety. These findings underscore that cultivating mindfulness may serve as a valuable strategy for mitigating the negative impact of learning uncertainty on test anxiety, ultimately promoting more positive and effective learning outcomes for EFL students.

学习不确定性和考试焦虑是英语作为外语学习者面临的重大挑战，可能会阻碍学业进步，并产生负面的学习经历。虽然研究已经建立了这些构念之间的联系，但正念的中介作用，特别是在期望-价值方法的框架内，在EFL背景下仍未得到充分探索。本研究通过调查532名中国参与者的学习不确定性、考试焦虑和正念之间的关系来解决这一差距，其中包括215名（40.4 %）男性和317名（59.6 %）女性参与者。参与者采用分层随机抽样的方法，完成一系列有效的自我报告问卷。结构方程模型（SEM）分析显示，学习不确定性与考试焦虑之间存在显著正相关，表明不确定性水平越高，焦虑程度越高。相反，学习不确定性与正念之间、正念与考试焦虑之间呈显著负相关。此外，扫描电镜分析证实，正念显著中介学习不确定性和考试焦虑之间的关系。这些发现强调，培养正念可能是一种有价值的策略，可以减轻学习不确定性对考试焦虑的负面影响，最终促进外语学生获得更积极、更有效的学习成果。

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引用次数: 0

Associations between deep learning vs. surface learning styles with both AI competence and personal enhancement by AI 深度学习与表面学习风格与人工智能能力和人工智能个人提升之间的关系

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-11 DOI: 10.1016/j.lmot.2025.102182

Christian Montag , Jon D. Elhai

Societal discussion has recently focused on what degree people use AI for personal enhancement such as using their own cognitive functions more effectively. Discussion has also centered on whether AI use has detrimental consequences for a user’s cognitive abilities. This new debate needs to be supplemented by empirical research, whereas the present research aims to shed light on who has a positive view about using AI for personal enhancement in the context of individual differences in learning styles. For this reason, n = 266 German-participants from the general population were recruited. In addition, n = 283 US-participants with a student background were recruited. All participants filled in a range of questionnaires including a measure on deep/surface learning style, items related to self-determination-theory in the context of AI and the Personal Enhancement by AI Scale (PEAIS). In the German sample, we observed that greater self-reported competence in AI was associated with more personal enhancement by AI tendencies. This association was mediated by deep learning style. In the US student sample, we replicated this association between AI-competence and greater personal enhancement by AI, but deep learning style was unrelated to both AI competence and personal enhancement by AI in this sample. Interestingly, post-hoc analyses revealed that associations between the three variables (AI-competence, deep learning style, personal enhancement by AI) were visible with small to moderate effect sizes in the US male subsample; so the lack of association between deep learning style and personal enhancement by AI within the US female sample was a failed replication. The present study findings should be seen as preliminary, and we hope to encourage other researchers to conduct follow-up research in this important, new research area.

最近，社会讨论的焦点是人们在多大程度上利用人工智能来增强个人能力，比如更有效地利用自己的认知功能。讨论还集中在人工智能的使用是否会对用户的认知能力产生有害影响。这种新的争论需要通过实证研究来补充，而目前的研究旨在阐明在个体学习风格差异的背景下，谁对使用人工智能来增强个人能力持积极看法。因此，n = 从普通人群中招募了266名德国参与者。此外，n = 283名具有学生背景的美国参与者被招募。所有参与者都填写了一系列问卷，包括深度/表面学习风格测量、人工智能背景下的自决理论相关项目和人工智能个人增强量表（PEAIS）。在德国的样本中，我们观察到，更强的人工智能自我报告能力与人工智能倾向对个人的提升有关。这种关联是由深度学习风格介导的。在美国学生样本中，我们复制了人工智能能力与人工智能个人提升之间的这种关联，但在这个样本中，深度学习风格与人工智能能力和人工智能个人提升都无关。有趣的是，事后分析显示，在美国男性子样本中，三个变量（人工智能能力、深度学习风格、人工智能的个人增强）之间的关联是可见的，效应大小为小到中等；因此，在美国女性样本中，深度学习风格和人工智能个人提升之间缺乏联系是一个失败的复制。目前的研究结果应被视为初步的，我们希望鼓励其他研究人员在这个重要的新研究领域进行后续研究。

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引用次数: 0

Radial maze memory retention in rats: Controlling olfactory cues 大鼠径向迷宫记忆保持：控制嗅觉线索

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-10 DOI: 10.1016/j.lmot.2025.102187

Kanji Hayashida, Chiaki Tanaka, Tohru Taniuchi

This study investigated long-term spatial memory retention in rats using an eight-arm radial maze. Tanaka and Taniuchi (2024) had previously confirmed significant performance after 72 h in late middle-aged rats, approximately 19 months old. This current study explored memory retention in young adult rats, beginning at about 100–120 days old, which we expected to have better memory capacity than late middle-aged rats. In Experiment 1, adult rats were subjected to forced-choice and free-choice tasks. As the retention interval was extended, significant performance was observed even after a 96-h retention interval, suggesting that adult rats can retain memories for up to 96 h. However, like the study by Tanaka and Taniuchi (2024), Experiment 1 could not completely eliminate the possible use of olfactory traces from markings as discriminative cues for arm selection. Therefore, in Experiment 2, inserts placed in the maze arms were randomly repositioned during the retention interval to eliminate potential olfactory stimuli from serving as valid cues for performance. The results showed significant performance up to a 72-h retention interval, but not at the 96-h retention interval. This study demonstrates that even without non-mnemonic olfactory cues, rats can retain spatial memory in a radial maze for at least 72 h.

本研究利用八臂放射状迷宫研究大鼠的长期空间记忆保持。Tanaka和Taniuchi（2024）先前证实，大约19个月大的中年大鼠在72 h后表现显著。目前的研究探索了年轻成年大鼠的记忆保留，从大约100-120天开始，我们预计这比中年晚期的大鼠有更好的记忆能力。在实验1中，成年大鼠分别接受强迫选择和自由选择任务。随着记忆保持间隔的延长，即使在96小时的记忆保持间隔后，也能观察到显著的表现，这表明成年大鼠可以保持长达96 小时的记忆。然而，就像Tanaka和Taniuchi（2024）的研究一样，实验1并不能完全排除将标记的嗅觉痕迹作为选择手臂的区别线索的可能性。因此，在实验2中，放置在迷宫臂中的插入物在保留间隔期间被随机重新放置，以消除潜在的嗅觉刺激作为有效提示的作用。结果表明，保留时间为72 h时，性能显著；保留时间为96 h时，性能不显著。这项研究表明，即使没有非助记性嗅觉线索，大鼠也能在径向迷宫中保持至少72 小时的空间记忆。

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引用次数: 0

Chinese engineering students’ perceived emotional experiences in AI-mediated education: An expectancy-value theory (EVT) perspective 中国工科学生在人工智能中介教育中的感知情感体验：一个期望-价值理论（EVT）的视角

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-09 DOI: 10.1016/j.lmot.2025.102180

Yan Huang , Hongfei Wang

The use of artificial intelligence (AI) technologies in engineering education has recently captured increasing scholarly attention. However, the emotional consequences of using AI tools by engineering students have been ignored in the literature. To fill the gaps, this qualitative study aimed to examine Chinese engineering students’ AI-induced emotional experiences and their reasons, drawing on the expectancy-value theory (EVT). A group of 83 engineering students was non-randomly selected to attend semi-structured interviews. Thematic analysis revealed that Chinese engineering students had experienced eight positive and six negative emotions in their AI-mediated education for different reasons pertaining their ‘self-efficacy’, ‘mastery and accomplishment experiences’, ‘perceived value of education’, ‘technical challenges’, ‘fear of being replaced’, and ‘perceived inefficiency and bias’ in AI tools. Each AI-induced emotional experience is discussed thoroughly, and implications are presented for engineering students and teachers to increase their awareness of AI-induced emotionality in their field.

人工智能（AI）技术在工程教育中的应用最近引起了越来越多的学术关注。然而，工程专业学生使用人工智能工具的情感后果在文献中被忽视了。为了填补这一空白，本定性研究旨在利用期望值理论（EVT），研究中国工科学生人工智能诱发的情绪体验及其原因。83名工程专业学生被随机抽取参加半结构化面试。专题分析显示，中国工科学生在人工智能介导的教育中经历了8种积极情绪和6种消极情绪，原因不同，包括“自我效能感”、“掌握和成就体验”、“感知教育价值”、“技术挑战”、“害怕被取代”以及“感知人工智能工具的效率低下和偏见”。本文深入讨论了每一种人工智能诱发的情感体验，并为工程专业的学生和教师提供了提高他们对人工智能诱发的情感的认识的启示。

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引用次数: 0

The role of robot-assisted learning in fostering learners’ motivation, self-efficacy, and autonomy: Self-determination theory framework 机器人辅助学习在培养学习者动机、自我效能感和自主性中的作用：自我决定理论框架

IF 1.8 4区心理学 Q3 PSYCHOLOGY, BIOLOGICAL

Learning and Motivation

Pub Date : 2025-09-08 DOI: 10.1016/j.lmot.2025.102184

Zhijuan Zhang

The integration of robot-assisted learning (RAL) in educational settings has emerged as a novel approach to enhance students' academic outcomes. This study scrutinizes the role of RAL in fostering learners' psychological factors, namely self-efficacy, autonomy, and motivation. A total of 82 students from some universities in Xinxiang participated, and the three questionnaires, namely self-efficacy, autonomy, and motivation, were administered. The study used a pretest-posttest design, with data collection conducted in two phases: the first in October and the second in November. The students were assigned to two groups: the control and experimental groups. The former was taught based on conventional teaching, including PowerPoint presentations and hands-on activities, while the latter was taught through robots. The intervention sessions, namely the use of robots, played a pivotal role in creating a structured and supportive setting for students to interact with robots and improve their learning outcomes. With the provision of immediate feedback, motivational incentives, and bilingual support, these sessions were designed to cultivate a positive and engaging educational experience. The findings through running Analysis of Covariance (ANCOVA) indicated significant developments in self-efficacy, autonomy, and motivation for the group exposed to RAL, with medium effect sizes. These results suggest that RAL can be an effective tool for enhancing key psychological factors that contribute to successful learning outcomes. Indeed, RAL interventions generally yield significant improvements in students' psychological factors, particularly self-efficacy, autonomy, and motivation. By exploring the impacts of RAL, some educational suggestions of the study are pinpointed.

机器人辅助学习（RAL）在教育环境中的整合已经成为提高学生学业成绩的一种新方法。本研究考察了RAL在培养学习者的心理因素，即自我效能感、自主性和动机方面的作用。共有82名来自新乡市部分高校的大学生参与，采用自我效能感、自主性和动机三份问卷进行问卷调查。该研究采用了前测后测设计，数据收集分两个阶段进行：第一个阶段在10月，第二个阶段在11月。这些学生被分为两组：对照组和实验组。前者基于传统教学，包括ppt演示和实践活动，而后者则通过机器人进行教学。干预环节，即机器人的使用，在创造一个结构化和支持性的环境，让学生与机器人互动，提高他们的学习成果方面发挥了关键作用。通过提供即时反馈、激励措施和双语支持，这些课程旨在培养积极和吸引人的教育体验。通过运行协方差分析（ANCOVA）的发现表明，暴露于RAL的群体在自我效能、自主性和动机方面有显著的发展，具有中等效应量。这些结果表明，RAL可以有效地提高关键的心理因素，有助于成功的学习成果。事实上，RAL干预通常能显著改善学生的心理因素，尤其是自我效能感、自主性和动机。通过探讨RAL的影响，提出了本研究的一些教育建议。

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引用次数: 0