Learning and Motivation最新文献

{"title":"How do basic psychological needs evolve in AI-assisted EFL learning? A longitudinal study of Chinese university students grounded in Self-Determination Theory","authors":"Yajing Fu ,&nbsp;Ying Chen","doi":"10.1016/j.lmot.2025.102193","DOIUrl":"10.1016/j.lmot.2025.102193","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102193"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changing background music is sufficient to disrupt reversal learning: Evidence from an ABC renewal design","authors":"Sahar Aghajari,&nbsp;Harald Lachnit,&nbsp;Metin Üngör","doi":"10.1016/j.lmot.2025.102190","DOIUrl":"10.1016/j.lmot.2025.102190","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102190"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does artificial intelligence-assisted learning positively affect college students’ motivation, emotion regulation, and academic uncertainty? Insight from situated learning theory","authors":"Haozhuo Lin ,&nbsp;Qiu Chen","doi":"10.1016/j.lmot.2025.102202","DOIUrl":"10.1016/j.lmot.2025.102202","url":null,"abstract":"<div><div>This study aimed to explore the effects of AI-assisted learning on undergraduate students’ motivation, emotion regulation, and academic uncertainty within the framework of Situated Learning Theory. Conducted at a Chinese university, the quasi-experimental pretest-posttest control group design involved 78 undergraduates from a humanities school, aged 18–22, with 60 % female and 40 % male participants. They were randomly assigned by intact classes to either an AI-assisted learning group (n = 39), receiving adaptive feedback, real-time support, and task adjustments via DeepSeek, or a control group (n = 39), receiving traditional instruction with identical content. Validated quantitative instruments measured motivation, emotion regulation, and academic uncertainty at pretest and posttest, with ANCOVA and MANCOVA analyses controlling for baseline scores. Results revealed significantly higher motivation and emotion regulation, alongside reduced academic uncertainty, in the AI group compared to the control group, supported by a strong multivariate effect. These findings suggest that AI-assisted learning fosters resilient, engaged learning environments in Chinese EFL contexts, offering practical implications for integrating adaptive technologies to support student affect and academic clarity.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102202"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The roles of growth mindset, resilience, and self-efficacy in student Engagement with AI-enhanced Chinese learning: A self-determination theory perspective","authors":"Xiuwen Zhai ,&nbsp;Shengji Li","doi":"10.1016/j.lmot.2025.102183","DOIUrl":"10.1016/j.lmot.2025.102183","url":null,"abstract":"<div><div>With the ongoing evolution of technology-enhanced education, growing attention is being paid to the psychological factors that influence student engagement. While emerging digital tools have contributed to more personalized learning experiences, the underlying psychological traits that shape students’ engagement behaviors remain insufficiently understood. Framed within Self-Determination Theory (SDT), this study investigates the roles of growth mindset, resilience, and self-efficacy in student engagement in AI-assisted Chinese learning, focusing on 505 Malaysian learners of Chinese. The data were analyzed using SPSS 26 and AMOS 24. The findings demonstrated that growth mindset, resilience, and self-efficacy positively predicted student engagement. Additionally, the mediation analysis revealed that self-efficacy played a crucial role in mediating the relationships between both growth mindset and engagement, and resilience and engagement. This study emphasizes the importance of psychological factors, such as growth mindset and resilience, in promoting engagement in AI-enhanced language learning environments. These findings contribute to the growing body of research on the role of psychological factors in technology-mediated learning.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102183"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"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","authors":"Kaifang Deng ,&nbsp;Xiaozhou Chen","doi":"10.1016/j.lmot.2025.102167","DOIUrl":"10.1016/j.lmot.2025.102167","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102167"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The roles of need frustration and regulatory focus in conspiratorial thinking","authors":"Matthew Hunsinger ,&nbsp;Michael Parker","doi":"10.1016/j.lmot.2025.102188","DOIUrl":"10.1016/j.lmot.2025.102188","url":null,"abstract":"<div><div>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 (<em>N</em> = 275) and one experiment (<em>N</em> = 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.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102188"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of robot-assisted learning in fostering learners’ motivation, self-efficacy, and autonomy: Self-determination theory framework","authors":"Zhijuan Zhang","doi":"10.1016/j.lmot.2025.102184","DOIUrl":"10.1016/j.lmot.2025.102184","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102184"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring enjoyment, motivation, self-efficacy, and engagement in AI-assisted English learning: A self-determination theory approach","authors":"Linyan Wang ,&nbsp;Long Wang","doi":"10.1016/j.lmot.2025.102197","DOIUrl":"10.1016/j.lmot.2025.102197","url":null,"abstract":"<div><div>As artificial intelligence becomes rapidly integrated into language education, the need to understand learners’ psychological responses has grown increasingly important. However, limited research has systematically examined how emotional and motivational factors interact in AI-assisted English learning. This study investigates the relationships among enjoyment, motivation, self-efficacy, and engagement in the context of AI-assisted English learning, guided by Self-Determination Theory (SDT). A total of 840 university students participated in the study. Data analysis was carried out using SPSS 26.0 and AMOS 26.0. Structural equation modeling revealed that both enjoyment and motivation significantly predicted self-efficacy and engagement, while self-efficacy also strongly predicted engagement. Mediation analysis further confirmed that self-efficacy significantly mediated the relationships between enjoyment and engagement, as well as between motivation and engagement. These findings highlight the critical role of emotional and motivational factors in enhancing learner confidence and involvement in technology-supported language education. The results provide empirical support for applying SDT in AI-enhanced learning environments and offer practical implications for designing emotionally supportive and psychologically empowering AI tools for language learners.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102197"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling Chinese youth students’ AI adoption goals and experiences: An achievement goal theory (AGT) perspective","authors":"Ying Sun","doi":"10.1016/j.lmot.2025.102198","DOIUrl":"10.1016/j.lmot.2025.102198","url":null,"abstract":"<div><div>Different studies have been done on various tools and technologies powered by artificial intelligence (AI) in recent years. However, the role of age groups in using and perceiving AI tools has been ignored in academic contexts. To fill the gap, this qualitative research aimed to explore Chinese youth students’ perceived AI adoption goals and experiences. A semi-structured interview was conducted with 58 general education students. The results of thematic analysis showed different AI adoption goals and experiences. The students had employed AI tools for ‘deep learning and understanding’, ‘personal growth and skill development’, ‘discovery of novel ideas and solutions’, ‘others’ outperformance and surpassing’, and ‘praise and recognition attainment’. Regarding experiences, the participants referred to four themes, namely ‘the emotional impact of AI on learners’, ‘providing a personalized and adaptive learning path’, ‘AI-mediated language learning’, and ‘the ethical considerations of AI technologies’. The findings are discussed and implications are provided for youth students, teachers, and educators to augment their AI literacy and help them set realistic goals and orientations regarding the use of AI tools.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102198"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Male? Female? Neutral! Using novel polyhedral figures as gender-neutral stimuli in a mental-rotation test","authors":"Vera Ruthsatz,&nbsp;Mirko Saunders,&nbsp;Michelle Lennon-Maslin,&nbsp;Claudia M. Quaiser-Pohl","doi":"10.1016/j.lmot.2025.102210","DOIUrl":"10.1016/j.lmot.2025.102210","url":null,"abstract":"<div><div>This study investigates sex differences in mental-rotation performance using novel, gender-neutral polyhedral stimuli. In contrast to the widely used cube figures, which are often perceived as male-stereotyped, these stimuli were specifically designed to be structurally analogous but less familiar and therefore less gender stereotypical. We hypothesised that such neutral stimuli might reduce sex differences, and that controlling for childhood play behaviour might improve explanatory precision by accounting for experiential differences between male and female participants. A total of 122 participants (83 females and 39 males; <em>M</em> = 25.95 years, <em>SD</em> = 9.26) completed the mental-rotation test and a self-assessment scale. In addition, they assessed the stereotypical nature of the polyhedra and answered a questionnaire assessing childhood gender-role behaviour. Participants confirmed that the novel polyhedral figures did not evoke gender associations, supporting their suitability for bias-reduced mental-rotation testing. Despite contrary expectations, mental-rotation accuracy differed significantly between sexes, whereas reaction times did not. To better understand the observed difference, regression analyses were conducted. These revealed that the effect of sex on accuracy was mediated by childhood play behaviour. While this effect was present across the full sample, correlation analyses suggested it was primarily driven by female participants. Moreover, feminine gender-role behaviour was associated with faster reaction times and worse accuracy, possibly reflecting differences in task engagement and motivational factors. Overall, the results support the interpretation that sex differences in mental-rotation accuracy reflect experiential rather than inherent cognitive factors. This study contributes to mental-rotation research by introducing an alternative stimulus set and by highlighting the need to consider developmental and motivational influences, which might vary with the choice of stimulus material, when interpreting differences in mental-rotation performance.</div></div>","PeriodicalId":47305,"journal":{"name":"Learning and Motivation","volume":"92 ","pages":"Article 102210"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145473953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}