Computers & Education最新文献

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Assessing digital etiquette in adolescents: A stealth approach using game-based learning to reduce anxiety, promote flow, and enhance learning gains 评估青少年的数字礼仪：一种使用基于游戏的学习来减少焦虑、促进心流和提高学习收益的隐形方法

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

Computers & Education

Pub Date : 2026-04-01 Epub Date: 2025-10-10 DOI: 10.1016/j.compedu.2025.105475

Jiawen Liu , Rustam Shadiev , Di Ge , Mei Cao , Yihua Xu , Ruotong Zhou

As digital behaviors among adolescents continue to rise, fostering digital etiquette has emerged as a critical issue in education. As a key skill within digital citizenship literacy, digital etiquette is highly contextual and primarily manifests in complex online interactions. Traditional measurement tools for digital etiquette often struggle to accurately reflect students' real-world behaviors. Although some studies have developed game-based stealth assessment tools, research on their practical application and user feedback remains limited. Specifically, empirical evidence regarding students' anxiety levels, flow experiences, and learning gains in this domain is still scarce, which is essential for the design and implementation of assessment tools. This study, grounded in an evidence-centered design framework, developed an automatic game-based stealth assessment (AGBSA) system that incorporates open-ended tasks and rich social cues. A multi-step evidence model construction method was proposed, utilizing expert judgment and machine learning techniques to ensure the validity and reliability of the assessment results. The research focused on the experiences of 82 middle school students after using the system, particularly their anxiety levels, flow experiences, and learning gains. Quantitative and qualitative findings indicated that students' anxiety levels significantly decreased while their flow experiences were enhanced. Interview results further revealed that the system effectively improved students' understanding and performance in digital etiquette.

随着青少年数字行为的不断增加，培养数字礼仪已成为教育中的一个关键问题。作为数字公民素养中的一项关键技能，数字礼仪是高度情境化的，主要体现在复杂的在线互动中。传统的数字礼仪测量工具往往难以准确反映学生在现实世界中的行为。虽然已经有一些研究开发了基于游戏的隐身评估工具，但对其实际应用和用户反馈的研究仍然有限。具体来说，关于学生焦虑水平、心流体验和学习收获在这一领域的经验证据仍然很少，这对评估工具的设计和实施至关重要。本研究基于以证据为中心的设计框架，开发了一种基于游戏的自动潜行评估（AGBSA）系统，该系统结合了开放式任务和丰富的社交线索。提出了一种多步骤证据模型构建方法，利用专家判断和机器学习技术来保证评估结果的有效性和可靠性。该研究关注了82名中学生在使用该系统后的体验，特别是他们的焦虑水平、心流体验和学习收获。定量和定性研究结果表明，学生的焦虑水平显著降低，心流体验增强。访谈结果进一步显示，该系统有效地提高了学生对数字礼仪的理解和表现。

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引用次数: 0

Assessing information problem solving through a simulation game: Validation evidence from a municipal enforcement official context 通过模拟游戏评估信息问题解决：来自市政执法官员背景的验证证据

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

Computers & Education

Pub Date : 2026-04-01 Epub Date: 2025-12-11 DOI: 10.1016/j.compedu.2025.105533

Aranka Bijl , Sebastiaan de Klerk , Bernard P. Veldkamp , Saskia Wools

Assessing complex vocational skills such as information problem solving is challenging, as it requires balancing authentic, construct-relevant tasks with standardized assessment conditions to ensure fair and meaningful results. This study responds to this challenge by addressing the gap in empirical validation of simulation games for summative assessment by validating Crossroads – a simulation game designed to measure information problem solving among municipal enforcement officials responsible for maintaining public safety. Grounded in the information problem solving model, the assessment focused on three of the model's constituent skills: scanning, processing, and organizing and presenting information. Performance on these skills was operationalized through six subscales. Using a known-groups design, the performance of first-year students, final-year students, and practicing municipal enforcement officials was examined. Participants completed a domain-specific information problem solving task in Crossroads: planning a surveillance route. A confirmatory factor analysis was conducted to investigate the underlying latent structure of the performance data. The results supported a one-factor model, suggesting that performance across subscales reflects a single underlying construct. Significant performance differences were observed between final-year students and both first-year students and practicing officials. Participants evaluated Crossroads positively in terms of usability and face validity. The findings provide evidence supporting the use of simulation games for summative assessment, demonstrating that Crossroads can elicit and differentiate levels of information problem solving in an assessment balancing authentic task characteristics with standardized assessment criteria. Several limitations highlight directions for future research, including expanding construct coverage, eliminating prior knowledge confounds, and balancing game autonomy with assessment structure.

评估复杂的职业技能（如信息解决问题）是具有挑战性的，因为它需要平衡真实的、与构建相关的任务和标准化的评估条件，以确保公平和有意义的结果。本研究回应了这一挑战，通过验证十字路口——一个旨在衡量负责维护公共安全的市政执法官员解决信息问题的模拟游戏，解决了模拟游戏在总结性评估的经验验证中的差距。在信息问题解决模型的基础上，评估集中在模型的三个组成技能上：扫描、处理、组织和呈现信息。这些技能的表现通过六个子量表进行操作。采用已知组设计，对一年级学生、最后一年级学生和执业市政执法官员的表现进行了检查。参与者在十字路口完成了一个特定领域的信息问题解决任务：规划监视路线。采用验证性因子分析探讨绩效数据的潜在结构。结果支持单因素模型，表明跨子量表的表现反映了一个单一的潜在结构。在高年级学生、一年级学生和在职官员之间观察到显著的绩效差异。参与者在可用性和人脸效度方面对十字路口给出了积极的评价。研究结果为使用模拟游戏进行总结性评估提供了证据，表明在平衡真实任务特征和标准化评估标准的评估中，Crossroads可以引出和区分信息问题解决的水平。一些限制突出了未来研究的方向，包括扩大结构覆盖范围，消除先验知识混淆，以及平衡游戏自主性和评估结构。

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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 : 2026-04-01 Epub 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。

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引用次数: 0

Do school-based ChatGPT policies Bridge or widen gaps in students’ computer and information literacy across gender, socioeconomic status, and immigration backgrounds 在性别、社会经济地位和移民背景方面，基于学校的聊天政策是弥合还是扩大了学生计算机和信息素养的差距

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

Computers & Education

Pub Date : 2026-04-01 Epub Date: 2025-12-13 DOI: 10.1016/j.compedu.2025.105536

Jia Chen Liu, Alan C.K. Cheung, Hyunwoo Yang

With the increasing application of generative AI tools, such as ChatGPT, many schools have developed school-based policies to regulate teachers' and students' use of these technologies. However, empirical evidence on the effectiveness of such policies remains limited. This study examines the relationship between school-based ChatGPT policies and students' computer and information literacy (CIL), and whether these policies moderate CIL disparities across students' gender, socioeconomic status (SES), and immigration background. The data come from International Computer and Information Literacy Study (ICILS) 2023, where school-based ChatGPT policies are distinguished for teachers and for students, each with three categories: unrestricted use, restricted use, and not allowed. Employing cross-level interaction models with random slopes, three findings emerge: (1) female, higher-SES, and non-immigrant students exhibit higher levels of CIL after controlling for student- and school-level covariates, including school-based ChatGPT policies; (2) policies permitting students' unrestricted use are negatively associated with CIL, whereas other policies for students and teachers show no significant direct relationship with CIL; (3) moderation is observed. Policies allowing teachers' use, whether unrestricted or restricted, narrow SES-related CIL gaps, while those permitting students’ unrestricted use exacerbate digital gender divide. These results highlight the need for well-designed and institution-supported AI use policies to promote equitable digital competence development in schools and to prevent the widening of existing digital divides.

随着ChatGPT等生成式人工智能工具的应用越来越多，许多学校制定了校本政策来规范教师和学生对这些技术的使用。然而，关于这些政策有效性的经验证据仍然有限。本研究探讨了基于学校的ChatGPT政策与学生计算机和信息素养（CIL）之间的关系，以及这些政策是否缓和了学生性别、社会经济地位（SES）和移民背景之间的CIL差异。数据来自国际计算机和信息素养研究（ICILS） 2023，其中以学校为基础的ChatGPT政策针对教师和学生进行了区分，每种政策分为三类：无限制使用、限制使用和不允许使用。采用随机斜率的跨水平相互作用模型，发现：(1)在控制了学生和学校水平的协变量（包括基于学校的ChatGPT政策）后，女性、高ses和非移民学生的CIL水平更高；(2)允许学生无限制使用网络语言的政策与网络语言水平呈负相关，而其他针对学生和教师的政策与网络语言水平无显著的直接关系；(3)观察适度。允许教师使用（无论是无限制的还是受限的）的政策缩小了与ses相关的CIL差距，而允许学生无限制使用的政策则加剧了数字性别鸿沟。这些结果突出表明，需要精心设计和机构支持的人工智能使用政策，以促进学校公平的数字能力发展，并防止现有数字鸿沟的扩大。

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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 : 2026-04-01 Epub 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。

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引用次数: 0

Adding Pedagogical Agents Who Point or Trace to Children’s Instructional Videos 添加指向或追踪儿童教学视频的教学代理

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

Computers & Education

Pub Date : 2026-03-20 DOI: 10.1016/j.compedu.2026.105618

Meixia Cheng, Peihua Qiao, Heng Ni, Heping Xie, Richard E. Mayer, Fuxing Wang

引用次数: 0

Trusting AI to detect AI? A systematic evaluation of the reliability and robustness of current AIGC detection tools for student academic work 信任人工智能来检测人工智能？对当前用于学生学术工作的AIGC检测工具的可靠性和鲁棒性进行系统评估

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

Computers & Education

Pub Date : 2026-03-19 DOI: 10.1016/j.compedu.2026.105616

Yicheng Sun, Yihan Liao, Xiaoxue Ma

引用次数: 0

Innovating diagnostic learning: How generative AI explanation styles influence cognitive load and confidence calibration in medical students 创新诊断学习：生成式人工智能解释风格如何影响医学生的认知负荷和信心校准

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

Computers & Education

Pub Date : 2026-03-19 DOI: 10.1016/j.compedu.2026.105619

Fang Tang, Feng Yao, Minghe Zhou

引用次数: 0

Teachers’ doings in the AI era: From transmission to relation 人工智能时代教师的行为：从传递到关系

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

Computers & Education

Pub Date : 2026-03-18 DOI: 10.1016/j.compedu.2026.105617

Miguel Nussbaum, Zvi Bekerman, Leanna Archambault, Maria Ranieri, Ramazan Yilmaz, Jiun-Yu Wu, Johan van Braak, Di Zou, Chin-Chung Tsai

引用次数: 0

The Interplay of Self-regulation, Cognitive Load and Learner Resources: Implications for Learning Outcomes in Virtual Reality 自我调节、认知负荷和学习者资源的相互作用：对虚拟现实学习成果的影响

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

Computers & Education

Pub Date : 2026-03-06 DOI: 10.1016/j.compedu.2026.105612

Nina Peltzer, Jochen Kuhn, Matthias Stadler, Raphael Cera, Christoph Hoyer, Salome Flegr, Martin R. Fischer, Constanze Richters

This study investigated how cognitive load, self-regulation, and learner resources interact to shape conceptual learning in immersive virtual reality (iVR). Building on Seufert’s (2018) model, we examined whether its predictions hold in iVR, how intrinsic (ICL) and extraneous cognitive load (ECL) relate to self-regulation and learning, and how learner resources contribute to these relations. Data from 473 students showed a consistent negative linear effect of ECL on both self-regulation and learning, underscoring ECL as a critical burden in iVR-based learning. ICL did not predict the frequency of self-regulation but negatively moderated its effectiveness for learning. In terms of learner resources, interest and self-efficacy supported the application of self-regulation under load, whereas prior knowledge was more closely related to whether regulatory activity translated into learning. These findings diverge from the U-shaped relations proposed by Seufert (2018) and suggest that in iVR, established relations between cognitive load and self-regulation are overlaid by additional regulatory demands inherent to immersive environments. Consequently, optimizing iVR-based learning requires not only minimizing ECL but also explicitly supporting learning-relevant self-regulation. Overall, the results demonstrate that models of self-regulated learning validated in traditional settings cannot be assumed to transfer unaltered to immersive environments, with implications for both instructional design and theory-driven research on learning in iVR.

本研究探讨了沉浸式虚拟现实（iVR）中认知负荷、自我调节和学习者资源如何相互作用以形成概念学习。在Seufert（2018）模型的基础上，我们研究了其预测是否适用于iVR，内在（ICL）和外在认知负荷（ECL）与自我调节和学习的关系，以及学习者资源如何促进这些关系。来自473名学生的数据显示，ECL对自我调节和学习都有一致的负线性影响，强调了ECL在基于ivr的学习中是一个关键的负担。ICL不能预测自我调节的频率，但对其学习效果有负向调节作用。在学习者资源方面，兴趣和自我效能感支持负荷下自我调节的应用，而先验知识与调节活动是否转化为学习的关系更为密切。这些发现与Seufert（2018）提出的u型关系不同，并表明在iVR中，认知负荷和自我调节之间的既定关系被沉浸式环境固有的额外调节需求所覆盖。因此，优化基于ivr的学习不仅需要最小化ECL，还需要明确支持与学习相关的自我调节。总体而言，研究结果表明，在传统环境中得到验证的自我调节学习模型不能被假设不变地转移到沉浸式环境中，这对iVR学习的教学设计和理论驱动研究都有启示。

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