Computers & Education最新文献_第4页

Longitudinal effects of learning analytics support for study planning and monitoring: Role of self-efficacy and data literacy 学习分析对学习计划和监控的纵向影响：自我效能感和数据素养的作用

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-12-11 DOI: 10.1016/j.compedu.2025.105532

Anceli Kaveri , Ismail Celik , Egle Gedrimiene , Anni Silvola , Hanni Muukkonen

Learning analytics (LA) can be an effective support for self-regulation of higher education students. Supporting different students on their academic paths requires considering students' self-efficacy beliefs and data-literacy skills as well as their varying uses and interpretations of LA. In this quasi-experimental study, we collected quantitative survey data on higher education students (N = 105) with and without access to a student-facing LA dashboard designed to support students on an academic path level. We collected data on students' perceived support for study planning and monitoring at three timepoints during one academic year. Utilizing latent growth curve modeling, the study investigated how students with different self-efficacy beliefs and data-literacy skills perceive receiving self-regulation support from LA throughout an academic year compared to peers with only regular digital tools. Our results showed that students with access to the LA dashboard reported a larger increase in perceived support compared to peers with access to only regular digital tools. Students with high data-literacy skills perceived receiving more support from LA compared to peers with low data-literacy. Students' self-efficacy beliefs did not significantly impact the extent of perceived support from LA. The results highlight the ethical risk of complex digital solutions, which, over time, put less technology-savvy students at a greater disadvantage and mainly benefit already higher-skilled students. The results strengthen current understanding on how LA supports higher education students on their academic paths but call for further investigation into ways of fostering students' data-literacy skills to maximize the support and overcome equity concerns.

学习分析可以为高等教育学生的自我调节提供有效的支持。支持不同学生的学术道路需要考虑学生的自我效能信念和数据素养技能，以及他们对洛杉矶的不同使用和解释。在这项准实验研究中，我们收集了高等教育学生（N = 105）的定量调查数据，这些学生有和没有使用面向学生的LA仪表板，该仪表板旨在支持学生的学术路径水平。我们在一学年的三个时间点收集了学生对学习计划和监控的感知支持的数据。利用潜在增长曲线模型，该研究调查了与仅使用常规数字工具的同龄人相比，具有不同自我效能信念和数据素养技能的学生如何看待整个学年从洛杉矶获得的自我调节支持。我们的研究结果表明，与仅使用常规数字工具的同龄人相比，使用洛杉矶仪表板的学生报告了更大的感知支持增长。与数据素养低的学生相比，数据素养高的学生认为从洛杉矶获得了更多的支持。学生的自我效能感信念并没有显著影响来自LA的感知支持程度。研究结果凸显了复杂的数字解决方案的伦理风险，随着时间的推移，对技术不太了解的学生处于更大的劣势，而主要受益的是已经具备较高技能的学生。研究结果加强了目前对洛杉矶如何支持高等教育学生走上学术道路的理解，但呼吁进一步研究培养学生数据素养技能的方法，以最大限度地提供支持并克服公平问题。

{"title":"Longitudinal effects of learning analytics support for study planning and monitoring: Role of self-efficacy and data literacy","authors":"Anceli Kaveri , Ismail Celik , Egle Gedrimiene , Anni Silvola , Hanni Muukkonen","doi":"10.1016/j.compedu.2025.105532","DOIUrl":"10.1016/j.compedu.2025.105532","url":null,"abstract":"<div><div>Learning analytics (LA) can be an effective support for self-regulation of higher education students. Supporting different students on their academic paths requires considering students' self-efficacy beliefs and data-literacy skills as well as their varying uses and interpretations of LA. In this quasi-experimental study, we collected quantitative survey data on higher education students (N = 105) with and without access to a student-facing LA dashboard designed to support students on an academic path level. We collected data on students' perceived support for study planning and monitoring at three timepoints during one academic year. Utilizing latent growth curve modeling, the study investigated how students with different self-efficacy beliefs and data-literacy skills perceive receiving self-regulation support from LA throughout an academic year compared to peers with only regular digital tools. Our results showed that students with access to the LA dashboard reported a larger increase in perceived support compared to peers with access to only regular digital tools. Students with high data-literacy skills perceived receiving more support from LA compared to peers with low data-literacy. Students' self-efficacy beliefs did not significantly impact the extent of perceived support from LA. The results highlight the ethical risk of complex digital solutions, which, over time, put less technology-savvy students at a greater disadvantage and mainly benefit already higher-skilled students. The results strengthen current understanding on how LA supports higher education students on their academic paths but call for further investigation into ways of fostering students' data-literacy skills to maximize the support and overcome equity concerns.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"246 ","pages":"Article 105532"},"PeriodicalIF":10.5,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing students’ critical thinking literacy in a generative AI context: Eye movement patterns of deepfake detection 在生成式人工智能背景下提高学生的批判性思维能力：Deepfake检测的眼动模式

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-12-11 DOI: 10.1016/j.compedu.2025.105529

Hayley Weigelt , Elad Segev , Gila Kurtz , Omri Kahana , Nohar Raz Fogel

This study examined, using eye-tracking technology, the gaze patterns of guided exposure to deepfake and authentic portrait images in comparison to unguided exposure to assess their influence on the acquisition and application of critical thinking literacy among first-year Bachelor students. Employing a between-groups experimental design, we analyzed visual gaze patterns between students who participated in the experiment group (n = 24) and those in the control group (n = 44). The results revealed significant differences in visual attention patterns, with the experimental group exhibiting a longer duration and broader distribution of fixations compared to the control group. The experimental group also achieved higher accuracy in identifying deepfake portrait images and exhibited a greater propensity to classify images as GenAI-generated. Nonetheless, both groups overestimated their detection capabilities, with no significant difference in perceived performance. As GenAI technologies continue to evolve, higher education institutions must prioritize the development of the essential 21st-century literacies, integrating cognitive training with technological solutions to combat GenAI-generated misinformation. This research contributes to the fields of GenAI literacy and critical thinking education by providing objective evidence, as measured through eye-tracking, that targeted interventions can significantly alter cognitive processing strategies. Educational practice must balance the development of critical evaluation skills with fostering a realistic awareness of human limitations, thereby preparing students to become discerning consumers and responsible creators in an increasingly complex digital information landscape.

本研究采用眼动追踪技术，考察了在引导下观看深度虚假和真实肖像图像的凝视模式，并将其与非引导下的凝视模式进行比较，以评估它们对一年级本科学生批判性思维素养的习得和应用的影响。采用组间实验设计，分析了实验组（n = 24）和对照组（n = 44）学生的视觉凝视模式。结果显示了视觉注意模式的显著差异，与对照组相比，实验组表现出更长的注视时间和更广泛的注视分布。实验组在识别深度假人像图像方面也取得了更高的准确性，并表现出更大的倾向于将图像分类为genai生成的。尽管如此，两组人都高估了自己的检测能力，在感知表现上没有显著差异。随着基因人工智能技术的不断发展，高等教育机构必须优先发展21世纪的基本素养，将认知训练与技术解决方案相结合，以打击基因人工智能产生的错误信息。本研究通过提供客观证据（通过眼动追踪测量），表明有针对性的干预可以显著改变认知加工策略，从而为GenAI识字和批判性思维教育领域做出了贡献。教育实践必须在培养批判性评估技能和培养对人类局限性的现实意识之间取得平衡，从而使学生在日益复杂的数字信息环境中成为有鉴赏力的消费者和负责任的创造者。

{"title":"Enhancing students’ critical thinking literacy in a generative AI context: Eye movement patterns of deepfake detection","authors":"Hayley Weigelt , Elad Segev , Gila Kurtz , Omri Kahana , Nohar Raz Fogel","doi":"10.1016/j.compedu.2025.105529","DOIUrl":"10.1016/j.compedu.2025.105529","url":null,"abstract":"<div><div>This study examined, using eye-tracking technology, the gaze patterns of guided exposure to deepfake and authentic portrait images in comparison to unguided exposure to assess their influence on the acquisition and application of critical thinking literacy among first-year Bachelor students. Employing a between-groups experimental design, we analyzed visual gaze patterns between students who participated in the experiment group (n = 24) and those in the control group (n = 44). The results revealed significant differences in visual attention patterns, with the experimental group exhibiting a longer duration and broader distribution of fixations compared to the control group. The experimental group also achieved higher accuracy in identifying deepfake portrait images and exhibited a greater propensity to classify images as GenAI-generated. Nonetheless, both groups overestimated their detection capabilities, with no significant difference in perceived performance. As GenAI technologies continue to evolve, higher education institutions must prioritize the development of the essential 21st-century literacies, integrating cognitive training with technological solutions to combat GenAI-generated misinformation. This research contributes to the fields of GenAI literacy and critical thinking education by providing objective evidence, as measured through eye-tracking, that targeted interventions can significantly alter cognitive processing strategies. Educational practice must balance the development of critical evaluation skills with fostering a realistic awareness of human limitations, thereby preparing students to become discerning consumers and responsible creators in an increasingly complex digital information landscape.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"244 ","pages":"Article 105529"},"PeriodicalIF":10.5,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FLoRA: An advanced AI-powered engine to facilitate hybrid human-AI regulated learning 弗洛拉：一个先进的人工智能驱动的引擎，促进人类和人工智能的混合学习

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-12-08 DOI: 10.1016/j.compedu.2025.105527

Xinyu Li , Tongguang Li , Lixiang Yan , Yuheng Li , Linxuan Zhao , Mladen Raković , Inge Molenaar , Dragan Gašević , Yizhou Fan

Self-Regulated Learning (SRL), defined as learners’ ability to systematically plan, monitor, and regulate their learning activities, is crucial for sustained academic achievement and lifelong learning competencies. Emerging AI developments profoundly influence SRL interactions by potentially either diminishing or strengthening learners’ opportunities to exercise their own regulatory skills. Recent literature emphasises a balanced approach termed Hybrid Human-AI Regulated Learning (HHAIRL), in which AI provides targeted, timely scaffolding while preserving the learners’ role as active decision-makers and reflective monitors of their learning process. Central to HHAIRL is the integration of adaptive and personalised learning systems; by modelling each learner’s knowledge and self-regulation patterns, AI can deliver contextually relevant scaffolds that support learners during all phases of the SRL process. Nevertheless, existing digital tools frequently fall short, lacking adaptability and personalisation, focusing narrowly on isolated SRL phases, and insufficiently supporting meaningful human-AI interactions. In response, this paper introduces the enhanced FLoRA Engine, which incorporates advanced generative AI features and state-of-the-art learning analytics, and grounds in solid educational theories. The FLoRA Engine offers tools such as collaborative writing, multi-agent chatbots, and detailed learning trace logging to support dynamic, adaptive scaffolding of self-regulation tailored to individual needs in real time. We further present a summary of several research studies that provide the validations for and illustrate how these tools can be utilised in real-world educational and experimental contexts. These studies demonstrate the effectiveness of FLoRA Engine in fostering SRL, providing both theoretical insights and practical solutions for the future of AI-enhanced learning contexts.

自我调节学习（Self-Regulated Learning， SRL）被定义为学习者系统地计划、监控和调节其学习活动的能力，对于持续的学术成就和终身学习能力至关重要。新兴的人工智能发展通过潜在地减少或加强学习者锻炼自己的调节技能的机会，深刻地影响了SRL的互动。最近的文献强调了一种称为混合人类-人工智能调节学习（hairl）的平衡方法，在这种方法中，人工智能提供有针对性的、及时的脚手架，同时保留学习者作为积极决策者和学习过程的反思性监督者的角色。hairl的核心是适应性和个性化学习系统的整合；通过对每个学习者的知识和自我调节模式进行建模，人工智能可以提供与上下文相关的框架，在SRL过程的所有阶段为学习者提供支持。然而，现有的数字工具经常不足，缺乏适应性和个性化，狭隘地关注孤立的SRL阶段，并且不足以支持有意义的人类与ai交互。作为回应，本文介绍了增强的FLoRA引擎，它结合了先进的生成式人工智能功能和最先进的学习分析，并以坚实的教育理论为基础。FLoRA Engine提供了协作写作、多代理聊天机器人和详细的学习跟踪日志等工具，以支持动态、自适应的自我调节脚手架，以实时满足个人需求。我们进一步提出了几项研究的总结，这些研究提供了验证并说明了这些工具如何在现实世界的教育和实验环境中使用。这些研究证明了FLoRA Engine在培养SRL方面的有效性，为人工智能增强学习环境的未来提供了理论见解和实际解决方案。

{"title":"FLoRA: An advanced AI-powered engine to facilitate hybrid human-AI regulated learning","authors":"Xinyu Li , Tongguang Li , Lixiang Yan , Yuheng Li , Linxuan Zhao , Mladen Raković , Inge Molenaar , Dragan Gašević , Yizhou Fan","doi":"10.1016/j.compedu.2025.105527","DOIUrl":"10.1016/j.compedu.2025.105527","url":null,"abstract":"<div><div>Self-Regulated Learning (SRL), defined as learners’ ability to systematically plan, monitor, and regulate their learning activities, is crucial for sustained academic achievement and lifelong learning competencies. Emerging AI developments profoundly influence SRL interactions by potentially either diminishing or strengthening learners’ opportunities to exercise their own regulatory skills. Recent literature emphasises a balanced approach termed Hybrid Human-AI Regulated Learning (HHAIRL), in which AI provides targeted, timely scaffolding while preserving the learners’ role as active decision-makers and reflective monitors of their learning process. Central to HHAIRL is the integration of adaptive and personalised learning systems; by modelling each learner’s knowledge and self-regulation patterns, AI can deliver contextually relevant scaffolds that support learners during all phases of the SRL process. Nevertheless, existing digital tools frequently fall short, lacking adaptability and personalisation, focusing narrowly on isolated SRL phases, and insufficiently supporting meaningful human-AI interactions. In response, this paper introduces the enhanced FLoRA Engine, which incorporates advanced generative AI features and state-of-the-art learning analytics, and grounds in solid educational theories. The FLoRA Engine offers tools such as collaborative writing, multi-agent chatbots, and detailed learning trace logging to support dynamic, adaptive scaffolding of self-regulation tailored to individual needs in real time. We further present a summary of several research studies that provide the validations for and illustrate how these tools can be utilised in real-world educational and experimental contexts. These studies demonstrate the effectiveness of FLoRA Engine in fostering SRL, providing both theoretical insights and practical solutions for the future of AI-enhanced learning contexts.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"243 ","pages":"Article 105527"},"PeriodicalIF":10.5,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the regulation of learning within mobile mixed-reality environments: Insights from dynamic engagement transitions 探索移动混合现实环境中的学习规则：来自动态参与转换的见解

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-12-05 DOI: 10.1016/j.compedu.2025.105519

Yu Liu , Kang Yue , Yue Liu , Songyue Yang , Haolin Gao , Hao Sha

Analyzing transitions in multidimensional engagement states across regulated learning phases offers valuable insights into learning behaviors at a granular level. Nevertheless, the extraction of multimodal trigger signals to evaluate engagement dynamics remains a critical challenge, particularly within mixed-reality environments. Hence, this study developed a mixed-reality learning system using multi-scaffolding tools as system architectures to integrate regulatory mechanisms along the immersive learning trajectory. Specifically, the color-coded concept maps were designed as the user interface to support planning and goal orientation, while two-tier tests were incorporated as a content structuring mechanism to help learners monitor, evaluate, and adapt learning status. A comprehensive six-dimensional engagement framework was proposed to incorporate interactive, constructive, active, passive, emotional, and behavioral engagement, serving as the theoretical underpinning for the extraction of trigger signals within regulated learning phases and subprocesses. Empirical research was conducted to assess the effectiveness and learner perceptions of this novel mixed-reality learning system, utilizing a 2

\times

2 mixed factorial design, with regulation type (self-regulated vs. peer-scaffolded) as the between-subjects factor and device type (smartphones vs. tablets) as the within-subjects factor. Results from 64 high school students indicated that multi-scaffolding tools significantly enhanced learning achievement across conditions. Smartphones, due to lighter weight and smaller displays, encouraged more physical behavioral engagement, while tablets, with higher resolution and larger displays, fostered greater constructive engagement. Learners in peer-scaffolded learning exhibited higher engagement transition among emotional, active, and constructive states but inefficient learning adaption, whereas learners in self-regulated learning concentrated more on task-oriented behaviors.

分析跨规范学习阶段的多维参与状态的转换，可以在粒度级别上对学习行为提供有价值的见解。然而，提取多模态触发信号来评估参与动态仍然是一个关键的挑战，特别是在混合现实环境中。因此，本研究开发了一个混合现实学习系统，使用多脚手架工具作为系统架构，沿沉浸式学习轨迹集成监管机制。具体来说，颜色编码的概念图被设计为用户界面，以支持计划和目标导向，而两层测试被纳入内容结构机制，以帮助学习者监控、评估和适应学习状态。提出了一个综合的六维参与框架，包括互动、建设性、主动、被动、情感和行为参与，作为在调节学习阶段和子过程中提取触发信号的理论基础。利用2 × 2混合因子设计，以调节类型（自我调节vs.同伴支架）为主体间因素，设备类型（智能手机vs.平板电脑）为主体内因素，进行了实证研究，以评估这种新型混合现实学习系统的有效性和学习者感知。对64名高中生的研究结果表明，多脚手架工具在不同条件下显著提高了学习成绩。智能手机由于更轻的重量和更小的显示屏，鼓励更多的身体行为参与，而平板电脑具有更高的分辨率和更大的显示屏，促进了更大的建设性参与。同伴框架学习的学习者在情绪、积极和建设性状态之间表现出较高的投入度过渡，但学习适应效率较低，而自我调节学习的学习者更注重任务导向行为。

{"title":"Exploring the regulation of learning within mobile mixed-reality environments: Insights from dynamic engagement transitions","authors":"Yu Liu , Kang Yue , Yue Liu , Songyue Yang , Haolin Gao , Hao Sha","doi":"10.1016/j.compedu.2025.105519","DOIUrl":"10.1016/j.compedu.2025.105519","url":null,"abstract":"<div><div>Analyzing transitions in multidimensional engagement states across regulated learning phases offers valuable insights into learning behaviors at a granular level. Nevertheless, the extraction of multimodal trigger signals to evaluate engagement dynamics remains a critical challenge, particularly within mixed-reality environments. Hence, this study developed a mixed-reality learning system using multi-scaffolding tools as system architectures to integrate regulatory mechanisms along the immersive learning trajectory. Specifically, the color-coded concept maps were designed as the user interface to support planning and goal orientation, while two-tier tests were incorporated as a content structuring mechanism to help learners monitor, evaluate, and adapt learning status. A comprehensive six-dimensional engagement framework was proposed to incorporate interactive, constructive, active, passive, emotional, and behavioral engagement, serving as the theoretical underpinning for the extraction of trigger signals within regulated learning phases and subprocesses. Empirical research was conducted to assess the effectiveness and learner perceptions of this novel mixed-reality learning system, utilizing a 2 <span><math><mo>×</mo></math></span> 2 mixed factorial design, with regulation type (self-regulated vs. peer-scaffolded) as the between-subjects factor and device type (smartphones vs. tablets) as the within-subjects factor. Results from 64 high school students indicated that multi-scaffolding tools significantly enhanced learning achievement across conditions. Smartphones, due to lighter weight and smaller displays, encouraged more physical behavioral engagement, while tablets, with higher resolution and larger displays, fostered greater constructive engagement. Learners in peer-scaffolded learning exhibited higher engagement transition among emotional, active, and constructive states but inefficient learning adaption, whereas learners in self-regulated learning concentrated more on task-oriented behaviors.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"243 ","pages":"Article 105519"},"PeriodicalIF":10.5,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction notice to “Collaborative AI-in-the-loop pedagogical conversational agent to enhance social and cognitive presence in cMOOC” [Computers & Education 240 (206) 105451] 关于“协作ai -in- loop教学会话代理增强cMOOC中的社交和认知存在”的撤回通知[Computers & Education 240 (206) 105451]

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-12-04 DOI: 10.1016/j.compedu.2025.105516

Jianjun Xiao , Yulin Tian , Cixiao Wang

引用次数: 0

From users to creators: Design and evaluation of a VR professional development program for educators 从用户到创作者：教育工作者VR专业发展计划的设计和评估

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-12-02 DOI: 10.1016/j.compedu.2025.105518

Ali Geri̇ş , Barış Çukurbaşi , Yeliz Tunga , Gizem Engi̇n

As immersive technologies expand in education, a gap persists between teachers’ familiarity with virtual reality (VR) tools and effective pedagogical use. This study designed, implemented, and evaluated a 60-h VR Trainer Training Program using Educational Design Research (EDR) and the Taba-Tyler curriculum model. Sixteen teachers participated in a needs analysis, followed by 42 in-service teachers from 30 provinces in Türkiye engaging in the training program. The curriculum combined theoretical instruction with hands-on practice in tools such as Unity and Blender, supported by scaffolded learning and peer collaboration. Findings show significant gains in technical competence and pedagogical integration, with 85 % of participants producing technically functional VR projects and 72 % aligning them with curricular objectives. Teachers reported increased confidence and a shift from users to creators of VR content, though challenges remained regarding subject-specific examples, limited time for mastering advanced tools, and the need for sustained institutional support. The study offers a scalable model for professional development in immersive learning and underscores the importance of structured training for sustainable VR adoption.

随着沉浸式技术在教育领域的扩展，教师对虚拟现实（VR）工具的熟悉程度与有效的教学使用之间仍然存在差距。本研究使用教育设计研究（EDR）和Taba-Tyler课程模型设计、实施并评估了一个60小时的VR培训师培训计划。16名教师参与了需求分析，随后来自日本30个省的42名在职教师参与了培训计划。该课程将理论教学与Unity和Blender等工具的实践相结合，并辅以框架式学习和同伴协作。研究结果显示，在技术能力和教学整合方面取得了显著进步，85%的参与者制作了技术上功能性的VR项目，72%的参与者将其与课程目标相一致。教师们报告说，他们的信心增强了，从用户转向了VR内容的创造者，尽管在特定学科的例子、掌握先进工具的时间有限以及需要持续的机构支持方面仍然存在挑战。该研究为沉浸式学习的专业发展提供了一个可扩展的模型，并强调了结构化培训对可持续采用VR的重要性。

{"title":"From users to creators: Design and evaluation of a VR professional development program for educators","authors":"Ali Geri̇ş , Barış Çukurbaşi , Yeliz Tunga , Gizem Engi̇n","doi":"10.1016/j.compedu.2025.105518","DOIUrl":"10.1016/j.compedu.2025.105518","url":null,"abstract":"<div><div>As immersive technologies expand in education, a gap persists between teachers’ familiarity with virtual reality (VR) tools and effective pedagogical use. This study designed, implemented, and evaluated a 60-h VR Trainer Training Program using Educational Design Research (EDR) and the Taba-Tyler curriculum model. Sixteen teachers participated in a needs analysis, followed by 42 in-service teachers from 30 provinces in Türkiye engaging in the training program. The curriculum combined theoretical instruction with hands-on practice in tools such as Unity and Blender, supported by scaffolded learning and peer collaboration. Findings show significant gains in technical competence and pedagogical integration, with 85 % of participants producing technically functional VR projects and 72 % aligning them with curricular objectives. Teachers reported increased confidence and a shift from users to creators of VR content, though challenges remained regarding subject-specific examples, limited time for mastering advanced tools, and the need for sustained institutional support. The study offers a scalable model for professional development in immersive learning and underscores the importance of structured training for sustainable VR adoption.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"243 ","pages":"Article 105518"},"PeriodicalIF":10.5,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Principals’ ethical leadership in the AI Era: A narrative literature review of emerging challenges, strategies, and outcomes 人工智能时代校长的道德领导：对新出现的挑战、策略和结果的叙事文献综述

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-12-01 DOI: 10.1016/j.compedu.2025.105517

Chun Sing Maxwell Ho

The integration of artificial intelligence (AI) into education has intensified questions about how principals exercise ethical leadership in the adoption and governance of emerging technologies. This article reports a systematic review of research published between 2018 and July 2025 at the intersection of school leadership, ethics, and AI. Using a PRISMA-informed search databases, 62 peer-reviewed studies were identified and synthesized. The analysis revealed four categories of insight: trends in principals' experiences of dilemmas such as balancing efficiency with equity, strategies for acting in contexts where guidance is limited, influencing factors including policy frameworks and school cultures, and outcomes ranging from increased trust to organizational conflict. From these findings, the Principals' Ethical AI Leadership (PEAIL) framework was developed. The framework conceptualizes leadership not as a linear progression of phases, but as a prism refracting simultaneous demands at individual, organizational, and systemic levels. Despite this emergent body of work, three important gaps remain. First, theoretical approaches are not well integrated across normative, critical, and sociotechnical traditions. Second, leadership preparation and professional learning rarely address AI ethics explicitly. Third, there is little empirical evidence linking principals' ethical choices about AI to classroom practices or to students’ learning and well-being. Future directions include embedding AI ethics into leadership training, designing empirical studies that trace leadership decisions to student outcomes, and developing policies that institutionalize accountability and equity. By identifying these gaps and outlining concrete pathways forward, the article provides both a conceptual framework and a practice-oriented agenda for ethical school leadership in the AI era.

人工智能（AI）与教育的融合加剧了校长如何在采用和治理新兴技术方面发挥道德领导作用的问题。本文对2018年至2025年7月期间发表的关于学校领导、伦理和人工智能交叉领域的研究进行了系统回顾。利用prisma信息检索数据库，鉴定并综合了62项同行评议的研究。分析揭示了四类见解：校长在平衡效率与公平等困境方面的经验趋势，在指导有限的情况下采取行动的策略，包括政策框架和学校文化在内的影响因素，以及从增加信任到组织冲突等结果。根据这些发现，制定了校长道德人工智能领导（PEAIL）框架。该框架将领导力概念化为不同阶段的线性发展，而是在个人、组织和系统层面同时折射需求的棱镜。尽管有这些新兴的工作，三个重要的差距仍然存在。首先，理论方法没有很好地整合规范、批判和社会技术传统。其次，领导力准备和专业学习很少明确涉及人工智能伦理。第三，很少有经验证据表明校长对人工智能的道德选择与课堂实践或学生的学习和福祉有关。未来的发展方向包括将人工智能伦理纳入领导力培训，设计将领导力决策与学生成绩联系起来的实证研究，以及制定将问责制和公平性制度化的政策。通过确定这些差距并概述具体的前进道路，本文为人工智能时代的伦理学校领导提供了一个概念框架和一个以实践为导向的议程。

{"title":"Principals’ ethical leadership in the AI Era: A narrative literature review of emerging challenges, strategies, and outcomes","authors":"Chun Sing Maxwell Ho","doi":"10.1016/j.compedu.2025.105517","DOIUrl":"10.1016/j.compedu.2025.105517","url":null,"abstract":"<div><div>The integration of artificial intelligence (AI) into education has intensified questions about how principals exercise ethical leadership in the adoption and governance of emerging technologies. This article reports a systematic review of research published between 2018 and July 2025 at the intersection of school leadership, ethics, and AI. Using a PRISMA-informed search databases, 62 peer-reviewed studies were identified and synthesized. The analysis revealed four categories of insight: trends in principals' experiences of dilemmas such as balancing efficiency with equity, strategies for acting in contexts where guidance is limited, influencing factors including policy frameworks and school cultures, and outcomes ranging from increased trust to organizational conflict. From these findings, the Principals' Ethical AI Leadership (PEAIL) framework was developed. The framework conceptualizes leadership not as a linear progression of phases, but as a prism refracting simultaneous demands at individual, organizational, and systemic levels. Despite this emergent body of work, three important gaps remain. First, theoretical approaches are not well integrated across normative, critical, and sociotechnical traditions. Second, leadership preparation and professional learning rarely address AI ethics explicitly. Third, there is little empirical evidence linking principals' ethical choices about AI to classroom practices or to students’ learning and well-being. Future directions include embedding AI ethics into leadership training, designing empirical studies that trace leadership decisions to student outcomes, and developing policies that institutionalize accountability and equity. By identifying these gaps and outlining concrete pathways forward, the article provides both a conceptual framework and a practice-oriented agenda for ethical school leadership in the AI era.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"243 ","pages":"Article 105517"},"PeriodicalIF":10.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring students' self-regulated learning behavioural patterns and perceptions in an English speaking task within a generative AI-supported immersive VR environment 在生成式人工智能支持的沉浸式虚拟现实中，探索学生在英语口语任务中自我调节的学习行为模式和感知

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-11-27 DOI: 10.1016/j.compedu.2025.105515

Lei Tao, Yanjie Song, Jiachen Fu

Generative AI (GenAI) has introduced new opportunities for self-regulated learning (SRL) by enabling adaptive, conversational support in immersive educational environments. Yet little is known about how SRL unfolds in real time during oral communication tasks with GenAI support in immersive virtual reality (iVR). Most studies rely on post-task questionnaires, leaving unclear how different types of agent support influence regulatory processes and whether GenAI agents provide more effective support than scripted ones. This randomised experimental study compared college students' SRL behaviours under two conditions: a control group interacting with a scripted agent (34 students) and an experimental group interacting with a GenAI agent (37 students). Their interactions were coded using a validated SRL framework and analysed through behavioural sequence analysis. Results showed that learners with GenAI support demonstrated more frequent reflection behaviours (21.2 % vs. 8.9 %) and greater diversity in their regulatory strategies, indicating more adaptive engagement across SRL phases. Within the GenAI condition, two learner profiles were identified: strategic learners, who sustained longer and more diverse regulatory cycles, and reactive learners, whose behaviours were shorter and more affect-driven, demonstrating that individual learners responded differently to GenAI support. Regression and ANCOVA analyses confirmed that these behavioural profiles significantly predicted learners' perceived SRL gains, after controlling for baseline differences. These findings show that GenAI agents provide adaptive support that strengthens learners' planning, monitoring, and reflection processes in immersive speaking tasks. They also underline the educational significance of linking behavioural profiles with adaptive agent design to advance personalised support in iVR language learning environments.

生成式人工智能（GenAI）通过在沉浸式教育环境中实现自适应对话支持，为自我调节学习（SRL）带来了新的机会。然而，在沉浸式虚拟现实（iVR）中，在GenAI的支持下，SRL是如何在口头交流任务中实时展开的，人们对此知之甚少。大多数研究依赖于任务后问卷调查，不清楚不同类型的代理支持如何影响监管过程，以及GenAI代理是否比脚本代理提供更有效的支持。这项随机实验研究比较了两种情况下大学生的SRL行为：对照组与脚本代理交互（34名学生），实验组与GenAI代理交互（37名学生）。它们的相互作用使用经过验证的SRL框架进行编码，并通过行为序列分析进行分析。结果显示，在GenAI支持下的学习者表现出更频繁的反思行为（21.2%对8.9%），并且他们的调节策略更多样化，表明在SRL阶段有更多的适应性参与。在GenAI条件下，确定了两种学习者概况：战略学习者，他们持续更长、更多样化的调节周期，以及反应型学习者，他们的行为更短、更受情感驱动，这表明个体学习者对GenAI支持的反应不同。回归和ANCOVA分析证实，在控制基线差异后，这些行为特征显著地预测了学习者感知的SRL增益。这些发现表明，GenAI代理提供适应性支持，加强学习者在沉浸式口语任务中的计划、监控和反思过程。他们还强调了将行为概况与自适应代理设计联系起来，在iVR语言学习环境中推进个性化支持的教育意义。

{"title":"Exploring students' self-regulated learning behavioural patterns and perceptions in an English speaking task within a generative AI-supported immersive VR environment","authors":"Lei Tao, Yanjie Song, Jiachen Fu","doi":"10.1016/j.compedu.2025.105515","DOIUrl":"10.1016/j.compedu.2025.105515","url":null,"abstract":"<div><div>Generative AI (GenAI) has introduced new opportunities for self-regulated learning (SRL) by enabling adaptive, conversational support in immersive educational environments. Yet little is known about how SRL unfolds in real time during oral communication tasks with GenAI support in immersive virtual reality (iVR). Most studies rely on post-task questionnaires, leaving unclear how different types of agent support influence regulatory processes and whether GenAI agents provide more effective support than scripted ones. This randomised experimental study compared college students' SRL behaviours under two conditions: a control group interacting with a scripted agent (34 students) and an experimental group interacting with a GenAI agent (37 students). Their interactions were coded using a validated SRL framework and analysed through behavioural sequence analysis. Results showed that learners with GenAI support demonstrated more frequent reflection behaviours (21.2 % vs. 8.9 %) and greater diversity in their regulatory strategies, indicating more adaptive engagement across SRL phases. Within the GenAI condition, two learner profiles were identified: strategic learners, who sustained longer and more diverse regulatory cycles, and reactive learners, whose behaviours were shorter and more affect-driven, demonstrating that individual learners responded differently to GenAI support. Regression and ANCOVA analyses confirmed that these behavioural profiles significantly predicted learners' perceived SRL gains, after controlling for baseline differences. These findings show that GenAI agents provide adaptive support that strengthens learners' planning, monitoring, and reflection processes in immersive speaking tasks. They also underline the educational significance of linking behavioural profiles with adaptive agent design to advance personalised support in iVR language learning environments.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"242 ","pages":"Article 105515"},"PeriodicalIF":10.5,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging prompt-based LLMs for automated scoring and feedback generation in higher education 利用基于提示的法学硕士在高等教育中自动评分和反馈生成

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-11-26 DOI: 10.1016/j.compedu.2025.105511

Eman Mudhi AlGhamdi , Yuheng Li , Dragan Gašević , Guanliang Chen

As demand grows for personalized, scalable assessments in higher education (including both scoring and feedback provision), large language models (LLMs) have emerged as promising tools. While human educators typically perform scoring and feedback in a sequential and interrelated manner, existing research has largely addressed these tasks separately. This raises important questions about LLMs’ ability to handle scoring and feedback within a single workflow and the extent to which task sequencing affects their performance. To address this gap, this study investigates how prompting LLMs to perform scoring and feedback either together in one single prompt (prompt composition) or separately in two consecutive prompts (prompt decomposition), and the order in which these tasks are prompted affect the performance of GPT-4o, a cutting-edge LLM, in postgraduate open-ended assessments. We analyzed the scoring performance across student groups of varying performance levels. To tailor GPT-4o-generated feedback to individual student learning needs, we embedded well-established learner-centered feedback principles into the prompt design and assessed the quality of the generated feedback based on these principles. The scoring results revealed that prompt effectiveness varied modestly across student groups, with higher scoring errors on lower quality submissions. In terms of generated feedback, GPT-4o demonstrated greater support for learner agency. Task order influenced how this agency was expressed: prompting feedback first fostered learner autonomy, while prompting it after scoring emphasized the student–teacher connection.

随着高等教育对个性化、可扩展评估（包括评分和反馈）需求的增长，大型语言模型（llm）已经成为一种有前途的工具。虽然人类教育工作者通常以顺序和相互关联的方式进行评分和反馈，但现有的研究在很大程度上是分别解决这些任务的。这就提出了一个重要的问题，即法学硕士在单一工作流程中处理评分和反馈的能力，以及任务排序在多大程度上影响他们的表现。为了解决这一差距，本研究调查了提示法学硕士如何在一个提示（提示组成）或在两个连续提示（提示分解）中一起执行评分和反馈，以及这些任务提示的顺序如何影响gpt - 40（前沿法学硕士）在研究生开放式评估中的表现。我们分析了不同表现水平的学生群体的得分表现。为了使gpt - 40生成的反馈适合每个学生的学习需求，我们将完善的以学习者为中心的反馈原则嵌入到提示设计中，并根据这些原则评估生成的反馈的质量。评分结果显示，不同学生群体的即时有效性差异不大，在质量较低的提交中，评分错误较高。在生成的反馈方面，gpt - 40表现出对学习者代理的更大支持。任务顺序影响了这种中介的表达方式：提示反馈首先培养了学习者的自主性，而评分后提示则强调了学生与教师的联系。

{"title":"Leveraging prompt-based LLMs for automated scoring and feedback generation in higher education","authors":"Eman Mudhi AlGhamdi , Yuheng Li , Dragan Gašević , Guanliang Chen","doi":"10.1016/j.compedu.2025.105511","DOIUrl":"10.1016/j.compedu.2025.105511","url":null,"abstract":"<div><div>As demand grows for personalized, scalable assessments in higher education (including both scoring and feedback provision), large language models (LLMs) have emerged as promising tools. While human educators typically perform scoring and feedback in a sequential and interrelated manner, existing research has largely addressed these tasks separately. This raises important questions about LLMs’ ability to handle scoring and feedback within a single workflow and the extent to which task sequencing affects their performance. To address this gap, this study investigates how prompting LLMs to perform scoring and feedback either together in one single prompt (prompt composition) or separately in two consecutive prompts (prompt decomposition), and the order in which these tasks are prompted affect the performance of GPT-4o, a cutting-edge LLM, in postgraduate open-ended assessments. We analyzed the scoring performance across student groups of varying performance levels. To tailor GPT-4o-generated feedback to individual student learning needs, we embedded well-established learner-centered feedback principles into the prompt design and assessed the quality of the generated feedback based on these principles. The scoring results revealed that prompt effectiveness varied modestly across student groups, with higher scoring errors on lower quality submissions. In terms of generated feedback, GPT-4o demonstrated greater support for learner agency. Task order influenced how this agency was expressed: prompting feedback first fostered learner autonomy, while prompting it after scoring emphasized the student–teacher connection.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"243 ","pages":"Article 105511"},"PeriodicalIF":10.5,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effects of LLM use and note-taking on reading comprehension and memory: A randomised experiment in secondary schools 使用LLM和笔记对阅读理解和记忆的影响：一项在中学进行的随机实验

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-11-24 DOI: 10.1016/j.compedu.2025.105514

Pia Kreijkes , Viktor Kewenig , Martina Kuvalja , Mina Lee , Jake M. Hofman , Sylvia Vitello , Abigail Sellen , Sean Rintel , Daniel G. Goldstein , David Rothschild , Lev Tankelevitch , Tim Oates

Students' rapid uptake of Generative Artificial Intelligence tools, particularly large language models (LLMs), raises urgent questions about their effects on learning. We compared the impact of LLM use to that of traditional note-taking, or a combination of both, on secondary school students' reading comprehension and retention. We conducted a pre-registered, randomised controlled experiment with within- and between-participant design elements in schools in England. 405 students, aged 14–15 years, studied two text passages and completed comprehension and retention tests three days later. Quantitative results demonstrated that both note-taking alone and combined with LLM use had significant positive effects on retention and comprehension compared to using the LLM alone. Yet, most students preferred using the LLM over note-taking, and perceived it as more helpful. Qualitative results revealed that many students valued the LLM for making complex material more accessible and reducing cognitive load, while they appreciated note-taking for promoting deeper engagement and aiding memory. Additionally, we identified “archetypes” of prompting behaviour, offering insights into the different ways students interacted with the LLM. Overall, our findings suggest that, while note-taking promotes cognitive engagement and long-term comprehension and retention, LLMs may facilitate initial understanding and student interest. The study reveals the continued importance of traditional learning activities, the benefits of combining LLM use with traditional learning over using LLMs alone, and the AI skills that students need to maximise those benefits.

学生们对生成式人工智能工具，特别是大型语言模型（llm）的快速接受，引发了关于它们对学习影响的紧迫问题。我们比较了法学硕士的使用与传统笔记的使用，或两者结合，对中学生阅读理解和记忆的影响。我们在英国的学校进行了一项预先注册的随机对照实验，采用参与者内部和参与者之间的设计元素。405名14-15岁的学生学习了两篇课文，并在三天后完成了理解和记忆测试。定量结果表明，与单独使用LLM相比，单独记笔记和结合使用LLM对记忆和理解都有显著的积极影响。然而，与记笔记相比，大多数学生更喜欢使用法学硕士，并认为它更有帮助。定性结果显示，许多学生认为LLM使复杂的材料更容易理解，减少了认知负荷，而他们欣赏记笔记，以促进更深层次的参与和帮助记忆。此外，我们确定了提示行为的“原型”，为学生与法学硕士互动的不同方式提供了见解。总的来说，我们的研究结果表明，虽然记笔记可以促进认知参与和长期理解和保留，但法学硕士课程可能会促进初步理解和学生的兴趣。该研究揭示了传统学习活动的持续重要性，将法学硕士与传统学习相结合的好处，以及学生需要的人工智能技能，以最大限度地发挥这些好处。

{"title":"Effects of LLM use and note-taking on reading comprehension and memory: A randomised experiment in secondary schools","authors":"Pia Kreijkes , Viktor Kewenig , Martina Kuvalja , Mina Lee , Jake M. Hofman , Sylvia Vitello , Abigail Sellen , Sean Rintel , Daniel G. Goldstein , David Rothschild , Lev Tankelevitch , Tim Oates","doi":"10.1016/j.compedu.2025.105514","DOIUrl":"10.1016/j.compedu.2025.105514","url":null,"abstract":"<div><div>Students' rapid uptake of Generative Artificial Intelligence tools, particularly large language models (LLMs), raises urgent questions about their effects on learning. We compared the impact of LLM use to that of traditional note-taking, or a combination of both, on secondary school students' reading comprehension and retention. We conducted a pre-registered, randomised controlled experiment with within- and between-participant design elements in schools in England. 405 students, aged 14–15 years, studied two text passages and completed comprehension and retention tests three days later. Quantitative results demonstrated that both note-taking alone and combined with LLM use had significant positive effects on retention and comprehension compared to using the LLM alone. Yet, most students preferred using the LLM over note-taking, and perceived it as more helpful. Qualitative results revealed that many students valued the LLM for making complex material more accessible and reducing cognitive load, while they appreciated note-taking for promoting deeper engagement and aiding memory. Additionally, we identified “archetypes” of prompting behaviour, offering insights into the different ways students interacted with the LLM. Overall, our findings suggest that, while note-taking promotes cognitive engagement and long-term comprehension and retention, LLMs may facilitate initial understanding and student interest. The study reveals the continued importance of traditional learning activities, the benefits of combining LLM use with traditional learning over using LLMs alone, and the AI skills that students need to maximise those benefits.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"243 ","pages":"Article 105514"},"PeriodicalIF":10.5,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145583828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0