Computers & Education最新文献_第6页

Theorizing AI literacy development using Habermas' three cognitive knowledge interests from a systematic review: A STEM interdisciplinary perspective 基于哈贝马斯的三种认知知识兴趣的人工智能读写能力发展理论综述：一个STEM跨学科的视角

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

Computers & Education

Pub Date : 2026-03-01 Epub Date: 2025-11-04 DOI: 10.1016/j.compedu.2025.105492

Yuk Mui Elly Heung , Hong-biao Yin , Lyn English , Thomas K.F. Chiu

Existing research demonstrates AI's potential to improve learning outcomes and engagement, emphasizing the importance of pedagogical designs that promote AI literacy. This systematic literature review investigates how different literacies connect to AI literacy and offers pedagogical suggestions from a science, technology, engineering, and mathematics (STEM) learning perspective. Using the PRISMA approach, we screened 1603 articles from four databases and selected 58 for this review. We theorize AI literacy development using Habermas' three cognitive knowledge interests: technical, practical, and emancipatory as the primary analytical framework. We examine each interest individually and collectively to structure and connect the progression levels within UNESCO's AI competency framework for teachers. Our findings highlight the need for an interdisciplinary approach, with various literacies—data, digital, mathematical, algorithmic, scientific, computational, media, language, and civic—being critical for developing AI literacy. We presented a hierarchical structure to describe how the literacies related to AI literacy. Moreover, we suggest age-appropriate, culturally sensitive pedagogical methodologies, with project-based and problem-based learning helpful in K-12 and higher education and game-based learning, which incorporates AI toys and role-play, especially advantageous in early childhood education. Furthermore, we emphasize case-based, reflective, and cultural learning as important strategies for establishing ethical AI citizenship by allowing students to balance sociocultural aspects while developing unbiased and responsible AI-enhanced applications for society and the environment.

现有研究表明，人工智能有潜力改善学习成果和参与度，强调了促进人工智能素养的教学设计的重要性。这篇系统的文献综述调查了不同的素养与人工智能素养之间的关系，并从科学、技术、工程和数学（STEM）学习的角度提出了教学建议。使用PRISMA方法，我们从4个数据库中筛选了1603篇文章，并选择了58篇用于本综述。我们将哈贝马斯的三个认知知识兴趣：技术、实践和解放作为主要的分析框架，将人工智能素养的发展理论化。我们单独和集体审查每个兴趣，以便在教科文组织教师人工智能能力框架内构建和连接进步水平。我们的研究结果强调了跨学科方法的必要性，数据、数字、数学、算法、科学、计算、媒体、语言和公民等各种素养对于培养人工智能素养至关重要。我们提出了一个层次结构来描述读写能力与人工智能读写能力之间的关系。此外，我们建议采用适合年龄的、文化敏感的教学方法，基于项目和基于问题的学习有助于K-12和高等教育，以及基于游戏的学习，其中结合了人工智能玩具和角色扮演，在幼儿教育中特别有利。此外，我们强调基于案例、反思性和文化学习是建立道德人工智能公民的重要策略，允许学生平衡社会文化方面，同时为社会和环境开发公正和负责任的人工智能增强应用。

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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 : 2026-03-01 Epub 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。

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引用次数: 0

More inspiration and attention: How Generative AI tools impact graduate students' affective engagement in L2 source-based academic writing 更多的灵感和关注：生成人工智能工具如何影响研究生在基于L2资源的学术写作中的情感参与

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

Computers & Education

Pub Date : 2026-03-01 Epub Date: 2025-11-05 DOI: 10.1016/j.compedu.2025.105495

Zhangze Chen , Jia Zhu , Joshua McGrane , Therese N. Hopfenbeck , Yilin Wang , Yilong Ji

Amidst the growing hype surrounding Generative AI (GenAI) for second language (L2) writing purposes, multiple studies have emerged, but few have emphasized its effects on students' affective engagement when they utilize it for source-based L2 academic writing. Against this backdrop, the present study employed a randomized controlled trial (RCT) with 81 participants in China to evaluate students' affective engagement through quantitative data from questionnaires and qualitative data from stimulated recall with screencasts and semi-structured interviews. The findings show that traditional AI tools (e.g., DeepL) and GenAI tools show different effects on students' affective engagement across writing stages. GenAI tools, particularly when integrated with suggested prompts, significantly enhanced students' overall positive affect. Participants reported increased feelings of inspiration, alertness, attentiveness, and determination. However, qualitative analyses additionally revealed that students using suggested prompts experienced mixed emotions in later writing stages, particularly during revision, when AI outputs occasionally mismatched their individual needs and stylistic preferences. Moreover, students' affective engagement was dynamic, fluctuating across writing stages and prompt design and construction. This research offers insights for educators on how to effectively integrate GenAI into L2 writing classrooms.

围绕生成式人工智能（GenAI）用于第二语言（L2）写作目的的宣传越来越多，已经出现了许多研究，但很少有人强调它在学生将其用于基于源的L2学术写作时对情感投入的影响。在此背景下，本研究采用了一项随机对照试验（RCT），通过问卷调查的定量数据和屏幕录像和半结构化访谈的刺激回忆的定性数据来评估中国81名参与者的情感投入。研究结果表明，传统的人工智能工具（如DeepL）和GenAI工具对学生在写作阶段的情感投入表现出不同的影响。GenAI工具，特别是当与建议的提示相结合时，显著提高了学生的整体积极影响。参与者报告说，他们的灵感、警觉性、注意力和决心都增强了。然而，定性分析还显示，使用建议提示的学生在写作后期经历了复杂的情绪，特别是在修改期间，当人工智能输出偶尔与他们的个人需求和风格偏好不匹配时。此外，学生的情感投入是动态的，在写作阶段和提示设计和构建之间波动。这项研究为教育工作者提供了如何有效地将GenAI整合到第二语言写作课堂的见解。

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引用次数: 0

Hierarchical analysis of in-service teachers’ barriers to technology-integrated instruction: A review of 2000–2024 publications 在职教师技术整合教学障碍的层次分析：2000-2024年文献综述

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

Computers & Education

Pub Date : 2026-03-01 Epub Date: 2025-11-17 DOI: 10.1016/j.compedu.2025.105509

Chih-Hung Chen , Hua-Yi Fei , Chin-Chung Tsai

Barriers to technology adoption in education have emerged as a critical issue in technology-integrated instruction, widely recognized as key factors shaping teachers' willingness and readiness to adopt technology in classroom practice. This systematic literature review analyzed in-service teachers' barriers to technology-integrated instruction, based on 116 empirical studies published from 2000 to 2024 in the Web of Science SSCI database. A four-order hierarchical framework was proposed in this review to analyze the barriers: (1) First-order barriers, which include limited systemic support such as lack of resources, technical support, and time; (2) Second-order barriers, involving inadequate beliefs and attitudes such as teachers' concerns, emotion, and resistance to technology use; (3) Third-order barriers, addressing classroom management challenges; and (4) Fourth-order barriers, related to the lack of design thinking. Results drawn from the 116 studies revealed that first-order barriers were the most frequently mentioned challenges, followed by the second-, third-, and fourth-order barriers. Many studies identified overlapping barriers, with the combination of first- and second-order barriers being the most frequently mentioned, revealing more frequent co-occurrence of limited systemic support and inadequate beliefs and attitudes. Moreover, university teachers exhibited particularly higher occurrence rates across the second-, third-, and fourth-order barriers. This review also investigated the role of COVID-19 pandemic for the teachers' barriers to technology integration. Compared to non-pandemic studies, teachers confronted significantly higher occurrence rates of the second- and third-order barriers to technology integration during the COVID-19 pandemic. This implied that the sudden shift to fully online instruction increased teachers’ internal resistance, and highlighted the challenges of classroom management in a fully online instructional environment.

教育中采用技术的障碍已经成为技术整合教学中的一个关键问题，被广泛认为是影响教师在课堂实践中采用技术的意愿和准备的关键因素。本文基于Web of Science SSCI数据库2000 - 2024年间发表的116篇实证研究，对在职教师进行技术整合教学的障碍进行了系统的文献综述。本文提出了一个四阶障碍分析框架：(1)一阶障碍包括缺乏资源、技术支持和时间等有限的系统支持；(2)二级障碍，包括不充分的信念和态度，如教师的关注点、情感和对技术使用的抵制；(3)第三阶障碍，解决课堂管理挑战；(4)第四阶障碍，与缺乏设计思维有关。从116项研究中得出的结果显示，第一阶障碍是最常被提及的挑战，其次是第二、第三和第四阶障碍。许多研究发现了重叠的障碍，最常提到的是一级和二级障碍的结合，揭示了有限的系统支持和不充分的信念和态度更频繁地同时发生。此外，大学教师在第二、第三和第四阶障碍中表现出特别高的发生率。本文还调查了新冠肺炎大流行对教师技术整合障碍的影响。与非大流行研究相比，在2019冠状病毒病大流行期间，教师面临的第二和第三级技术整合障碍的发生率明显更高。这意味着突然转向完全在线教学增加了教师的内部阻力，并突出了在完全在线教学环境下课堂管理的挑战。

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引用次数: 0

Fostering scientific inquiry with hybrid intelligence: A semester-long experiment on knowledge acquisition in the science classroom 用混合智能培养科学探究：科学课堂知识获取的一学期实验

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

Computers & Education

Pub Date : 2026-03-01 Epub Date: 2025-11-02 DOI: 10.1016/j.compedu.2025.105493

Fan Chen , Bo Xiong , Gaowei Chen

Scientific inquiry is essential for developing deep conceptual understanding and exploratory skill, yet its complexity presents significant challenges for classroom implementation. While technologies like learning analytics (LA) and artificial intelligence (AI) offer promising tools for monitoring and guidance, the comparative and longitudinal effects of their integration remain underexplored. This study addresses this gap through a semester-long quasi-experiment with 177 secondary students across four conditions representing progressively enhanced technological support: a control (GICG), a structured system (BICG), the system plus an LA dashboard (ADIG), and the full integration of the system, dashboard, and an AI assistant (HIIG). A mixed-method analysis was conducted to assess knowledge acquisition and learning experiences. Quantitative findings revealed a clear performance hierarchy in theme-specific knowledge assessments (HIIG > ADIG ≈ BICG > GICG), with the fully integrated HIIG group demonstrating significantly higher comprehensive knowledge acquisition than the control group. Qualitative findings highlighted positive student perceptions of technology-augmented inquiry, like improved engagement, reduced frustration, and enhanced ability to navigate inquiry challenges, though the level of technological support influenced help-seeking behaviors and collaboration dynamics. This study provides empirical evidence for the synergistic value of integrating AI and LA, demonstrating that their combination creates an effective scaffolding system that fosters sustained knowledge acquisition by supporting both the cognitive and affective dimensions of student inquiry in authentic classrooms.

科学探究对于发展深刻的概念理解和探索技能至关重要，但其复杂性对课堂实施提出了重大挑战。虽然学习分析（LA）和人工智能（AI）等技术为监测和指导提供了很有前途的工具，但它们整合的比较和纵向影响仍未得到充分探索。本研究通过对177名中学生进行为期一个学期的准实验，在四种条件下解决了这一差距，这些条件代表了逐步增强的技术支持：控制（gigg）、结构化系统（BICG）、系统加LA仪表板（ADIG），以及系统、仪表板和人工智能助手（HIIG）的完全集成。采用混合方法分析知识获取和学习经验。定量研究结果显示，在特定主题知识评估（HIIG > ADIG≈BICG > gig）中，表现层次明显，完全整合HIIG组的综合知识获取显著高于对照组。定性研究结果强调了学生对技术增强探究的积极看法，如提高参与度，减少挫折感，增强应对探究挑战的能力，尽管技术支持水平影响了寻求帮助的行为和协作动态。本研究为整合AI和LA的协同价值提供了经验证据，表明它们的结合创造了一个有效的脚手架系统，通过支持真实课堂中学生探究的认知和情感维度，促进持续的知识获取。

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引用次数: 0

Fostering Preservice Teachers’ Design Thinking by Integrating Generative AI and Analytics-Supported Reflective Assessment in a Collaborative Inquiry Environment 通过在协作探究环境中整合生成式人工智能和分析支持的反思性评估，培养职前教师的设计思维

IF 12 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2026-02-24 DOI: 10.1016/j.compedu.2026.105602

Yuqin Yang, Linbaiyu Chen, Daner Sun, Wangda Zhu, Shiyan Pang

引用次数: 0

Webcam use and its role in children's engagement and achievement during extended remote learning 网络摄像头的使用及其在扩展远程学习期间儿童参与和成就中的作用

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

Computers & Education

Pub Date : 2026-02-01 Epub Date: 2025-08-21 DOI: 10.1016/j.compedu.2025.105443

Sharlyn Ferguson-Johnson , Allison M. Ryan , Kai S. Cortina

Online classes substitute in-person instruction in K-12 general education, yet whether children's webcam use in online classes is meaningful for their learning remains poorly understood. This study examined children's webcam use and academic outcomes during the COVID-19 pandemic using data from 1426 elementary students (49% male, 47% female, 93% White) across 65 classrooms, exploring how individual- and classroom-level webcam use, along with socioeconomic and demographic factors and remote learning duration, explained variation in childrens' engagement and achievement. In May 2021, students reported their remote learning routines and online class participation since May 2020; responses were then linked with 2020–2021 MSTEP achievement scores and demographic data. Correlational analyses revealed individual webcam use varied as a function of children's perceived engagement, academic achievement, socioeconomic disadvantage, and gender identity, while classrooms differed in mean webcam use based on socioeconomic and demographic composition, remote learning duration, and mean engagement and achievement. MANOVA results indicated classroom webcam use norms had a larger effect on engagement during remote learning relative to individual use. Specifically, children in classrooms with universal webcam-on norms reported significantly higher mean emotional and behavioral engagement compared to children in classrooms with moderate/mixed or low webcam-on norms. Multilevel models revealed classmates' mean webcam use explained a significant portion of the variance in children's 2020–2021 achievement and was a stronger predictor of achievement than individual webcam use. Overall, findings underscore the need to consider classroom-level webcam use policies and incentives when developing and refining effective online classroom structure and curricula for elementary school student populations.

在K-12通识教育中，在线课程取代了面对面的教学，然而，孩子们在在线课程中使用网络摄像头对他们的学习是否有意义，人们仍然知之甚少。本研究使用来自65个教室的1426名小学生（49%男性，47%女性，93%白人）的数据，调查了COVID-19大流行期间儿童的网络摄像头使用和学业成绩，探讨了个人和课堂层面的网络摄像头使用、社会经济和人口因素以及远程学习持续时间如何解释儿童参与度和成就的变化。2021年5月，学生报告了自2020年5月以来的远程学习习惯和在线课堂参与情况；然后将回答与2020-2021年MSTEP成就和人口统计数据联系起来。相关分析表明，个人网络摄像头的使用随着儿童感知参与、学业成就、社会经济劣势和性别认同的变化而变化，而教室的平均网络摄像头使用基于社会经济和人口组成、远程学习持续时间、平均参与和成就而不同。方差分析结果表明，相对于个人使用，课堂网络摄像头规范对远程学习的参与有更大的影响。具体来说，在普遍网络摄像头规范的教室里，与在中等/混合或低网络摄像头规范的教室里的孩子相比，在普遍网络摄像头规范的教室里的孩子报告的平均情感和行为投入显著更高。多层模型显示，同学使用网络摄像头解释了儿童2020-2021年成绩差异的很大一部分，并且比个人使用网络摄像头更能预测2020-2021年的成绩。总体而言，研究结果强调，在为小学生群体开发和完善有效的在线课堂结构和课程时，需要考虑课堂级网络摄像头的使用政策和激励措施。

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引用次数: 0

Investigating the effects of an LLM-based Socratic conversational agent on students’ academic performance and reflective thinking in higher education 基于法学硕士的苏格拉底对话代理对高等教育学生学习成绩和反思性思维的影响

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

Computers & Education

Pub Date : 2026-02-01 Epub Date: 2025-11-03 DOI: 10.1016/j.compedu.2025.105494

Linjin Xi , Yi Zhang , Qiyun Wang

The rapid advancement of GenAI has created unprecedented opportunities to enhance student learning through large language models (LLMs). While LLM-based conversational agents have demonstrated potential in improving accessibility and instructional support, evidence of their impact on higher-order thinking remains limited, especially within the context of Chinese higher education. This study introduces the Socratic Intelligent Conversational Agent (S-ICA), which integrates Socratic questioning strategies with semantic generation mechanisms to promote student learning and reflective thinking in disciplinary contexts. A total of 94 university students from China participated in the study, with random assignment to an experimental group (EG) using the S-ICA and a control group (CG) using a non-Socratic conversational agent (nS-ICA). The results showed that the EG outperformed the CG in both academic achievement and reflective thinking, particularly in the dimensions of “reflection” and “critical reflection”. Cognitive network analysis revealed that the EG students activated more advanced reflective pathways, linking understanding, reflection, and critical reflection processes. Although no significant differences were found in learning motivation between the groups, interviews with students indicated that the S-ICA facilitated more effective learning and deeper reflective engagement. These findings contribute to research on integrating classical pedagogical strategies into GenAI-based systems, offering insights into how such technologies can foster higher-order thinking and guide the design of future collaborative human–AI learning systems.

GenAI的快速发展为通过大型语言模型（llm）提高学生的学习创造了前所未有的机会。虽然基于法学硕士的会话代理在提高可访问性和教学支持方面已经显示出潜力，但它们对高阶思维的影响证据仍然有限，特别是在中国高等教育的背景下。本研究引入苏格拉底式智能对话代理（S-ICA），将苏格拉底式提问策略与语义生成机制相结合，以促进学生在学科情境中的学习和反思性思维。共有94名来自中国的大学生参加了这项研究，随机分配到使用S-ICA的实验组（EG）和使用非苏格拉底会话代理（nS-ICA）的对照组（CG）。结果表明，EG在学业成绩和反思思维两个维度上都优于CG，尤其是在“反思”和“批判性反思”两个维度上。认知网络分析显示，EG学生激活了更高级的反思途径，将理解、反思和批判性反思过程联系起来。虽然小组之间的学习动机没有显著差异，但对学生的访谈表明，S-ICA促进了更有效的学习和更深层次的反思参与。这些发现有助于将经典教学策略整合到基于genai的系统中，为这些技术如何培养高阶思维和指导未来人类-人工智能协作学习系统的设计提供见解。

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引用次数: 0

Development and implementation of a generative AI-based personalized recommender system to improve students’ self-regulated learning and academic performance 基于生成式人工智能的个性化推荐系统的开发与实施，提高学生自主学习和学习成绩

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

Computers & Education

Pub Date : 2026-02-01 Epub Date: 2025-10-14 DOI: 10.1016/j.compedu.2025.105486

Xinyi Luo, Sikai Wang, Khe Foon Hew

Students' ability to manage their own learning is crucial for academic success, but many struggle with self-regulation, often leading to disengagement. Past studies have explored tactics to boost students' self-regulated learning (SRL), such as writing self-reflective reports and incorporating prompts in video lectures. These tactics, however, often lack timely, personalized feedback due to the labor-intensive nature of such support. In this study, we report the development and implementation of an innovative large language model (LLM)-based recommender system named SRLAdvisor to address these limitations. The system combines a web interface with a series of LLM-based agents, allowing students to receive immediate, personalized feedback. By processing students' natural language interactions in real-time, SRLAdvisor dynamically profiles their self-regulation and delivers personalized recommendations. This study involved 22 postgraduate students and employed a sequential explanatory mixed-methods approach to evaluate students’ self-regulation and learning performance. We found near-perfect agreement between the system detection and human coding. SRLAdvisor exhibited greater recommendation precision in self-monitoring and self-evaluation tasks. Students who perceived the system as highly useful showed significantly greater self-reported SRL gains than those with lower perceptions. Additionally, a k-means cluster analysis indicated that students who engaged more frequently with SRLAdvisor achieved significantly greater improvements in learning performance. These findings underscore the potential of leveraging LLMs to deliver personalized recommendations. However, they also reveal potential concerns, such as over-reliance on AI and prompt monotony, that need to be further examined. These issues are particularly relevant in the context of LLM-supported SRL interventions and warrant further discussion.

学生管理自己学习的能力对学业成功至关重要，但许多人在自我调节方面遇到困难，往往导致他们脱离学习。过去的研究探索了促进学生自我调节学习（SRL）的策略，比如写自我反思报告和在视频讲座中加入提示。然而，由于这种支持的劳动密集型性质，这些策略往往缺乏及时、个性化的反馈。在这项研究中，我们报告了一个名为SRLAdvisor的创新的基于大语言模型（LLM）的推荐系统的开发和实现，以解决这些限制。该系统将网络界面与一系列基于法学硕士的代理相结合，使学生能够获得即时的个性化反馈。通过实时处理学生的自然语言互动，SRLAdvisor动态地分析他们的自我调节并提供个性化的建议。本研究以22名研究生为研究对象，采用序贯解释混合方法评估学生的自我调节和学习表现。我们发现在系统检测和人类编码之间存在近乎完美的一致性。SRLAdvisor在自我监控和自我评价任务中表现出更高的推荐精度。那些认为该系统非常有用的学生比那些认为该系统非常有用的学生表现出更大的自我报告的SRL收益。此外，k-means聚类分析表明，更频繁地使用SRLAdvisor的学生在学习成绩上取得了显著更大的进步。这些发现强调了利用法学硕士提供个性化推荐的潜力。然而，它们也揭示了潜在的问题，比如过度依赖人工智能和即时单调，这些问题需要进一步研究。这些问题与法学硕士支持的SRL干预措施特别相关，值得进一步讨论。

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引用次数: 0

Team collaborative norms enhance students’ behavioral engagement in team-based flipped classrooms: A multilevel analysis 团队合作规范在基于团队的翻转课堂中提高学生的行为投入：一个多层次的分析

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

Computers & Education

Pub Date : 2026-02-01 Epub Date: 2025-10-01 DOI: 10.1016/j.compedu.2025.105468

Hui-Min Lai , Pi-Jung Hsieh , Fang-Chuan Ou Yang

The flipped classroom (FC) model replaces traditional in-class lectures with student-centered, team-based activities. In the FC model, in-class sessions are typically conducted in teams to promote active participation, group discussion, problem-solving, and collaborative learning. However, a review of previous studies reveals that the factors contributing to behavioral engagement in team-based FCs remain underexplored. Thus, we aim to explore team-based FCs by integrating the theories of expectancy–value and social motivation. Given that collaborative norms are crucial for enhancing students’ behavioral engagement in teams, we propose that team collaborative norms moderate the relationship between individuals’ beliefs (value and competence beliefs) and behavioral engagement. We collected data from 808 students across 238 teams in 28 team-based FCs and used a hierarchical linear model to examine the hypothesized relationships. The results indicated a positive relationship between utility value and students’ behavioral engagement, as well as between interest value and engagement in team-based FCs. Conversely, there was a negative relationship between learning anxiety and students’ behavioral engagement. No significant relationship was found between attainment value and engagement. Additionally, self-efficacy and team collaborative norms were positively associated with students’ behavioral engagement in team-based FCs. Notably, the moderating effect of team collaborative norms on the relationships between utility value and behavioral engagement and between interest value and behavioral engagement was stronger under high team collaborative norms than under low ones. This study contributes to existing research by validating the role of team collaborative norms in students’ behavioral engagement within team-based FCs.

翻转课堂（FC）模式以学生为中心，以团队为基础的活动取代了传统的课堂讲座。在FC模型中，课堂会议通常在团队中进行，以促进积极参与、小组讨论、解决问题和协作学习。然而，对先前研究的回顾表明，在基于团队的fc中，影响行为参与的因素仍未得到充分探索。因此，我们旨在通过整合期望值理论和社会动机理论来探索基于团队的FCs。鉴于协作规范对提高学生在团队中的行为投入至关重要，我们提出团队协作规范调节个人信念（价值信念和能力信念）与行为投入之间的关系。我们收集了来自28个基于团队的fc的238个团队的808名学生的数据，并使用分层线性模型来检验假设的关系。结果表明，在团队型FCs中，效用价值与学生的行为投入存在正相关，兴趣价值与行为投入存在正相关。反之，学习焦虑与学生行为投入呈负相关。学业成就值与敬业度之间无显著关系。此外，自我效能感和团队合作规范与学生的行为投入正相关。值得注意的是，团队协作规范对团队效用价值与行为投入、兴趣价值与行为投入关系的调节作用在高团队协作规范下强于低团队协作规范下。本研究通过验证团队协作规范在团队型FCs中学生行为投入中的作用，为现有研究做出了贡献。

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