Computers and Education Open最新文献_第7页

Extended executive cognition, a learning outcome for the AI age 扩展执行认知，人工智能时代的学习成果

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-30 DOI: 10.1016/j.caeo.2025.100294

Alexander M. Sidorkin

Artificial intelligence fundamentally transforms professional expertise across disciplines, creating an expanding gap between higher education curricula and emerging workplace practices. This paper introduces "Extended Executive Cognition" as a critical learning outcome for the AI age, the ability to strategically allocate cognitive effort, coordinate AI-assisted tasks, and manage hybrid intelligence problem-solving. Drawing on curriculum theory, executive function psychology, and distributed cognition research, we argue that post-educational success increasingly depends on metacognitive skills for human-AI collaboration rather than traditional academic competencies. Extended Executive Cognition requires developing accurate mental models of AI capabilities and limitations to enable effective task delegation. The framework presented offers concrete curriculum integration strategies across general education and discipline-specific contexts, including assessment approaches that capture metacognitive development rather than mere product evaluation. By reconceptualizing learning outcomes around cognitive orchestration rather than content production, universities can prepare graduates for continuous technological evolution while preserving distinctly human capacity as education's central value.

人工智能从根本上改变了跨学科的专业知识，在高等教育课程和新兴工作场所实践之间造成了越来越大的差距。本文介绍了“扩展执行认知”作为人工智能时代的关键学习成果，战略分配认知努力，协调人工智能辅助任务和管理混合智能解决问题的能力。根据课程理论、执行功能心理学和分布式认知研究，我们认为，教育后的成功越来越依赖于人类与人工智能合作的元认知技能，而不是传统的学术能力。扩展执行认知需要开发准确的人工智能能力和局限性的心智模型，以实现有效的任务授权。所提出的框架提供了跨通识教育和学科特定背景的具体课程整合策略，包括捕捉元认知发展而不仅仅是产品评估的评估方法。通过围绕认知编排而不是内容生产重新定义学习成果，大学可以让毕业生为持续的技术进化做好准备，同时保留明显的人类能力作为教育的核心价值。

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引用次数: 0

Artificial intelligence as a pedagogical communicator: mixed-methods insights from Raffles International College Bangkok 人工智能作为教学传播者：来自曼谷莱佛士国际学院的混合方法见解

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-30 DOI: 10.1016/j.caeo.2025.100297

Qinjie Shen

Artificial intelligence (AI) is increasingly employed as a pedagogical assistant in higher education, but its role as a communicator in diverse classrooms is not fully understood. This mixed-methods study investigates AI as a pedagogical communicator at a private international college in Bangkok. The study extends the Technology Acceptance Model by integrating social presence and trust constructs to examine factors influencing student engagement and satisfaction with AI-mediated instruction. In an explanatory sequential design, a survey of 300 students was analyzed using structural equation modeling, followed by 10 in-depth interviews. Results indicated that student satisfaction is driven by two mediated pathways: perceived social presence in AI communication builds trust, which enhances satisfaction, and perceived usefulness of AI feedback promotes engagement, which likewise increases satisfaction. Ease of interacting with the AI increased perceived presence and usefulness and thus indirectly boosted satisfaction; however, it also raised expectations that sometimes dampened satisfaction. Interview themes clarified these patterns. Students valued the AI’s clear explanations, responsiveness, and round-the-clock support, which improved efficiency and engagement, but also noted its lack of human warmth and increased pressure from constant availability. These findings suggest design principles for AI communicators, such as using friendly, context-aware language and clear rationales to build trust, and providing stepwise, practical feedback to sustain engagement. In sum, culturally responsive AI tutors that balance human-like connection with instructional efficiency can enhance student engagement and satisfaction in multicultural educational settings.

人工智能（AI）越来越多地被用作高等教育的教学助理，但它在不同课堂中作为沟通者的作用尚未得到充分认识。这项混合方法的研究调查了人工智能作为曼谷一所私立国际学院的教学传播者。该研究通过整合社会存在和信任结构来扩展技术接受模型，以检查影响学生参与和对人工智能介导的教学满意度的因素。在解释性序列设计中，使用结构方程模型对300名学生的调查进行了分析，随后进行了10次深度访谈。结果表明，学生满意度由两种中介途径驱动：人工智能交流中感知到的社交存在建立信任，从而提高满意度；人工智能反馈的感知有用性促进了参与度，同样也提高了满意度。与AI互动的便利性增加了存在感和有用性，从而间接提高了满意度；然而，它也提高了期望值，有时会降低满意度。访谈主题阐明了这些模式。学生们重视人工智能的清晰解释、响应能力和24小时支持，这提高了效率和参与度，但也注意到它缺乏人性的温暖，并且增加了持续可用性的压力。这些发现为人工智能传播者提供了设计原则，例如使用友好的、情境感知的语言和清晰的理由来建立信任，并提供逐步的、实用的反馈来维持参与。总之，在多元文化教育环境中，具有文化响应能力的人工智能导师能够平衡与人类的联系和教学效率，从而提高学生的参与度和满意度。

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引用次数: 0

Privacy, identity, and fairness: Unpacking ethical influences on metaverse adoption in university learning 隐私、身份与公平：揭示大学学习中伦理对虚拟世界采用的影响

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-24 DOI: 10.1016/j.caeo.2025.100292

Mousa Al-kfairy , Meera Alalawi , Saed Alrabaee , Omar Alfandi

As immersive technologies like the Metaverse continue to reshape higher education, it becomes increasingly vital to examine the ethical dimensions shaping student engagement with these platforms. This study investigates how university students perceive privacy, digital identity, informed consent, and algorithmic fairness in Metaverse-based classrooms, and how these perceptions influence their trust and behavioral intention to adopt the technology. A quantitative survey was conducted with 310 university students, all of whom had prior exposure to virtual learning platforms. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0, the study found that Metaverse Ethical Dimensions (MED) significantly influence both Trusting Intention (TRI) (

β

= 0.740, p < 0.001) and Intention to Use (IU) (

β

= 0.573, p < 0.001). Additionally, TRI partially mediates the relationship between MED and IU (

β

= 0.206, p = 0.001). These results highlight the central role of ethical design and user trust in promoting the adoption of Metaverse-based classrooms.

随着像Metaverse这样的沉浸式技术继续重塑高等教育，审视影响学生与这些平台互动的道德维度变得越来越重要。本研究调查了大学生在基于metaverse的课堂中如何感知隐私、数字身份、知情同意和算法公平性，以及这些感知如何影响他们的信任和采用该技术的行为意愿。对310名大学生进行了一项定量调查，他们之前都接触过虚拟学习平台。通过SmartPLS 4.0使用偏最小二乘结构方程模型（PLS-SEM），研究发现，meta伦理维度（MED）显著影响信任意图（TRI）（β = 0.740, p < 0.001）和使用意图（IU）（β = 0.573, p < 0.001）。此外，TRI部分介导了MED和IU之间的关系（β = 0.206, p = 0.001）。这些结果突出了道德设计和用户信任在促进采用基于metaverse的教室中的核心作用。

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引用次数: 0

The community of inquiry framework and learning analytics: A systematic review of previous research 探究框架与学习分析的共同体：对以往研究的系统回顾

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-19 DOI: 10.1016/j.caeo.2025.100289

Secil Caskurlu , Daniela Castellanos-Reyes , Jieun Lim , Kadir Kozan

The purpose of the current systematic review is to provide a comprehensive overview of how the Community of Inquiry framework and learning analytics have been informing each other, thus providing suggestions for how to enhance future research and practice in online education. Overall results revealed that (a) research was primarily conducted in MOOCs and traditional online courses; (b) text and log data were the primary sources analyzed using various statistical, computational, and/or machine learning methods through various tools and software; and (c) descriptive and/or predictive analytics were the most common learning analytics methodology thus describing and/or predicting student and instructor outcomes including teaching, social and cognitive presence. Even though few studies have explicitly named it as the guiding framework, the Community of Inquiry framework has significantly influenced learning analytics research design and some studies have offered new theoretical insights. As for research quality or characteristics, fewer studies fully reported such important details as participant characteristics and data preprocessing procedures. All these findings led to the conclusion that the Community of Inquiry framework and learning analytics have been mutually beneficial so far, and similar future research needs to pay more attention to reporting quality thereby providing richer insights into both the theory and practice of online education.

当前系统综述的目的是全面概述探究共同体框架和学习分析是如何相互影响的，从而为如何加强在线教育的未来研究和实践提供建议。总体结果显示：(a)研究主要在mooc和传统在线课程中进行；(b)文本和日志数据是通过各种工具和软件使用各种统计、计算和/或机器学习方法分析的主要来源；(c)描述性和/或预测性分析是最常见的学习分析方法，因此描述和/或预测学生和教师的结果，包括教学、社会和认知存在。尽管很少有研究明确地将其命名为指导框架，但探究共同体框架对学习分析研究设计产生了重大影响，一些研究提供了新的理论见解。在研究质量或特征方面，充分报道参与者特征、数据预处理过程等重要细节的研究较少。所有这些发现得出的结论是，到目前为止，探究社区框架和学习分析是互惠互利的，未来类似的研究需要更多地关注报告质量，从而为在线教育的理论和实践提供更丰富的见解。

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引用次数: 0

Contextual knowledge and TPACK: Evidence from a global south setting 背景知识和TPACK：来自全球南方背景的证据

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-18 DOI: 10.1016/j.caeo.2025.100290

Van Loi Nguyen , Chung Thi Thanh Hang , Nguyen Trong Nguyen , Huynh Truong Sang

Extensive research on Technological Pedagogical Content Knowledge (TPACK) has revealed how contextual layers influence teachers’ perceptions and practice of technology integration, but the extent to which contextual knowledge (XK) contributes to the TPACK framework remains underexplored. This study, adopting the transformative view of TPACK in context, aimed to explore the XK-TPACK relationship. Data was collected from a survey on 148 English as a foreign language teachers working across various educational settings in the lower Mekong Delta of Vietnam. Partial Least Squares Factor analysis and Structural Equation Modeling (SEM) were used to explore three hypothesized models. Validation results supported the substantial direct contribution of XK to TPACK variation. This finding extends the literature and suggests that the interplay of TPACK domains becomes more complex, considering contextual knowledge. Future research should be conducted to corroborate this model.

对技术教学内容知识（TPACK）的广泛研究揭示了情境层如何影响教师对技术整合的认知和实践，但情境知识（XK）对TPACK框架的贡献程度仍未得到充分探讨。本研究采用语境中TPACK的变革性观点，旨在探讨XK-TPACK的关系。数据收集自对148名英语作为外语教师的调查，这些教师在越南湄公河三角洲下游的不同教育机构工作。利用偏最小二乘因子分析和结构方程模型（SEM）探讨了三个假设模型。验证结果支持XK对TPACK变异的实质性直接贡献。这一发现扩展了文献，并表明考虑到上下文知识，TPACK域的相互作用变得更加复杂。未来的研究应进一步证实这一模型。

引用次数: 0

Rethinking artificial-intelligence literacy through the lens of teacher educators: The adaptive AI model 通过教师教育者的视角重新思考人工智能素养：自适应人工智能模型

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-18 DOI: 10.1016/j.caeo.2025.100291

Liat Eyal

As artificial intelligence becomes increasingly integrated into educational settings, models for measuring related literacy among both teachers and students are rapidly emerging. Yet despite their strengths and benefits, many impose fixed competency levels or overlook contextual factors. Using design-based research, and with the participation of 22 higher-education teacher educators, this study critiques existing models and introduces the novel Adaptive Artificial-Intelligence-Literacy Model (AALM), grounded in case-study analysis. This evaluation framework highlights the dynamic, multi-dimensional nature of artificial-intelligence literacy, organized around three inter-related core axes: contextual fitness, professional needs, and dynamic development. A reflective self-assessment tool is also presented, enabling teachers to evaluate their own artificial-intelligence literacy. This framework offers practical guidance for educational policy and teacher development, advocating for assessment approaches that consider social and cultural contexts, professional needs, and the evolving nature of skills amid rapid technological change. Finally, the case studies illustrate the model's relevance across diverse educational settings.

随着人工智能越来越多地融入教育环境，衡量教师和学生相关素养的模型正在迅速出现。然而，尽管他们有优势和好处，许多人强加了固定的能力水平，或者忽视了环境因素。本研究采用基于设计的研究方法，在22名高等教育教师教育者的参与下，对现有模型进行了批判，并引入了基于案例研究分析的新型自适应人工智能识字模型（AALM）。该评估框架突出了人工智能素养的动态、多维性，围绕三个相互关联的核心轴进行组织：环境适应性、专业需求和动态发展。还提出了一种反思性自我评估工具，使教师能够评估自己的人工智能素养。该框架为教育政策和教师发展提供了实用指导，倡导采用考虑社会和文化背景、专业需求以及快速技术变革中技能演变性质的评估方法。最后，案例研究说明了该模型在不同教育环境中的相关性。

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引用次数: 0

Gamifying cybersecurity: A narrative-driven approach to teaching steganography 游戏化网络安全：一种叙事驱动的隐写术教学方法

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-15 DOI: 10.1016/j.caeo.2025.100288

Femke G.J. Weijsenfeld, Dipti K. Sarmah

Serious games are increasingly used in educational settings to enhance student engagement and support deeper learning. While research shows that such games can improve holistic understanding and knowledge retention, their application in specialised cybersecurity topics such as steganography, the art of concealing information to avoid detection, remains limited. Current teaching approaches for steganography often rely on traditional methods, such as lectures and textbooks, offering little interactivity or immersion. This study addresses this gap by designing and evaluating StegAdventure, a narrative-based serious game designed to improve student engagement with steganography concepts. To assess the game’s effectiveness, we conducted a controlled study with 54 higher education students in The Netherlands, randomly divided into an experimental group (n = 27) who played the game and a control group (n = 27) who studied the same content through a traditional text-based resource. Participants in both groups completed the User Engagement Scale - Short Form (UES-SF) to assess perceived engagement, and a knowledge test to measure learning outcomes. Our analysis revealed a significant difference in engagement levels, favouring the game-based approach, while no significant difference was observed in knowledge test scores. These findings suggest that StegAdventure can serve as a valuable teaching tool, particularly for increasing student engagement in complex cybersecurity topics, with the potential to support long-term knowledge retention.

严肃游戏越来越多地用于教育环境，以提高学生的参与度和支持更深入的学习。虽然研究表明，这类游戏可以提高整体理解和知识保留，但它们在专业网络安全主题（如隐写术）中的应用仍然有限。隐写术是一种隐藏信息以避免被发现的艺术。目前的隐写术教学方法往往依赖于传统的方法，如讲座和教科书，提供很少的互动性或沉浸。本研究通过设计和评估《StegAdventure》来解决这一问题，这是一款基于叙述的严肃游戏，旨在提高学生对隐写术概念的参与度。为了评估游戏的有效性，我们对荷兰的54名高等教育学生进行了一项对照研究，将他们随机分为实验组（n = 27）和对照组（n = 27），实验组玩游戏，对照组通过传统的基于文本的资源学习相同的内容。两组的参与者都完成了用户参与量表-简短形式（UES-SF）来评估感知参与，以及知识测试来衡量学习成果。我们的分析揭示了在参与水平上的显著差异，倾向于基于游戏的方法，而在知识测试分数上没有观察到显著差异。这些发现表明，StegAdventure可以作为一种有价值的教学工具，特别是在增加学生对复杂网络安全主题的参与方面，具有支持长期知识保留的潜力。

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引用次数: 0

Bridging higher educators’ beliefs and practice in online education: A qualitative systematic review 衔接高等教育工作者在网络教育中的信念与实践：一个定性的系统回顾

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-10 DOI: 10.1016/j.caeo.2025.100286

Dorothy Gwada , Jo Tondeur , Bram Bruggeman , Samuel Liyala , Silvance O. Abeka

As online education becomes increasingly prevalent in higher education, educators’ beliefs about teaching practices have become critical to its success. These beliefs influence key aspects of online course design, including course structure, communication methods, and the use of technology, all of which affect student engagement and achievement. This study explores the relationship between educators' beliefs about online education and their actual teaching practices through a qualitative systematic literature review of 19 studies published between 2010 and 2023. Using a meta-aggregation approach, themes were identified, grouped, and synthesized to capture global trends in the relationship between educators’ beliefs and their practices. The findings indicate that educators believe online education requires adapting instructional approaches to align with technological affordances and student needs, while also fostering social presence and group cohesion to enhance participation. While many existing models focus on acceptance or resistance, this review highlights more complex dynamics, such as tensions between educators’ beliefs and the challenges of aligning technology use with those beliefs. It shows that online teaching practices are shaped not only by technical considerations but also by educators’ beliefs about online teaching and the value of technology. These insights offer a deeper understanding of how educators’ beliefs interact with their online teaching practices and have significant implications for designing professional development programs and informing institutional policies that support the transition to online teaching.

随着在线教育在高等教育中越来越普遍，教育者对教学实践的信念已成为其成功的关键。这些信念影响着在线课程设计的关键方面，包括课程结构、交流方法和技术的使用，所有这些都会影响学生的参与度和成绩。本研究通过对2010年至2023年间发表的19项研究进行定性系统的文献综述，探讨了教育者对在线教育的信念与他们实际教学实践之间的关系。使用元聚合方法，确定、分组和综合主题，以捕捉教育者信念与其实践之间关系的全球趋势。研究结果表明，教育工作者认为，在线教育需要调整教学方法，使其与技术能力和学生需求保持一致，同时还需要培养社会存在感和群体凝聚力，以提高参与度。虽然许多现有的模型关注于接受或抵制，但这篇综述强调了更复杂的动态，比如教育者的信念和将技术使用与这些信念相一致的挑战之间的紧张关系。它表明，在线教学实践不仅受到技术考虑的影响，而且受到教育者对在线教学和技术价值的信念的影响。这些见解提供了对教育者的信念如何与他们的在线教学实践相互作用的更深入的理解，并对设计专业发展计划和告知支持向在线教学过渡的机构政策具有重要意义。

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引用次数: 0

Authentic open data inquiry in schools 学校的真实开放数据查询

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-09 DOI: 10.1016/j.caeo.2025.100287

Alejandra Celis Vargas , Rikke Magnussen , Ingrid Mulder , Birger Larsen

Open data offers the potential to enhance citizen participation, transparency, and accountability in society. However, a lack of competencies that enable citizens to engage in open data ecosystems remains a barrier. Although authentic open data inquiry has been identified as a promising approach to develop open data learning designs in schools, its connection to open data competencies is not yet well understood. To advance the understanding of open data competencies and learning designs, this study focuses on the inductive analysis of two design-based research cycles and four interventions in Danish schools. A cohort of 7th to 9th grade pupils (n = 78) and their teachers (n = 4) engaged with The Open Data Newsroom, an open data learning design that situates pupils in the role of data journalists to solve an environmental mystery. Following a thematic analysis approach, we examined qualitative data from observations, surveys, and interviews to identify four categories that encompass pupils’ practices for (1) navigating open data: find and assess relevant information and data to identify a problem; (2) developing authentic open data analysis: analyse and interpret data in connection to real-world problems and local contexts; (3) building authentic data arguments and stories: explain a problem with data from different sources and domains to lay audiences; and (4) creating open data representations: build tools to support inquiry and communication. We argue that these practices, grounded in data literacy and real-world problem solving, contribute to defining open data competencies in schools, and we present a model to illustrate this connection.

开放数据提供了增强公民参与、透明度和社会问责制的潜力。然而，缺乏使公民参与开放数据生态系统的能力仍然是一个障碍。虽然真实的开放数据调查已被确定为在学校开发开放数据学习设计的有前途的方法，但其与开放数据能力的联系尚未得到很好的理解。为了促进对开放数据能力和学习设计的理解，本研究侧重于对丹麦学校中两个基于设计的研究周期和四个干预措施的归纳分析。一组七年级到九年级的学生（n = 78）和他们的老师（n = 4）参与了开放数据新闻编辑室，这是一种开放数据学习设计，让学生扮演数据记者的角色，解决一个环境之谜。遵循主题分析方法，我们检查了来自观察、调查和访谈的定性数据，以确定包含学生实践的四个类别：(1)浏览开放数据：查找和评估相关信息和数据以识别问题；(2)发展真正的开放数据分析：分析和解释与现实世界问题和当地背景相关的数据；(3)构建真实的数据论证和故事：用不同来源和领域的数据向外行观众解释问题；(4)创建开放的数据表示：构建支持查询和交流的工具。我们认为，这些以数据素养和解决现实问题为基础的实践有助于定义学校的开放数据能力，我们提出了一个模型来说明这种联系。

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引用次数: 0

A review of reviews on TPACK research: is there any focus? 关于TPACK研究的综述：有什么重点吗？

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-09-06 DOI: 10.1016/j.caeo.2025.100285

Febe Fontyn , Jo Tondeur , Jan Sermeus

The TPACK framework describes what knowledge educators need to effectively integrate technology into teaching specific content. This integrated knowledge is specific to the domains that TPACK combines, i.e. to the content that is taught, the pedagogical approaches chosen and the technology used. Given that there is a substantial body of research literature on TPACK, it seems useful to focus review-studies on one domain. For example, a review might summarize what is known about teachers’ TPACK using a specific technology, comparing and combining the literature across content domains or pedagogical approaches. Inversely a review could also focus on specific content or on a specific pedagogical approach. In this review of reviews we investigate to what extent review research on TPACK focuses on specific domains (technology, pedagogy or content) or their related knowledge components in the TPACK-framework. Based on a systematic literature review of 32 review studies we find that few reviews focus their research questions, selection criteria or results on specific domains or knowledge components. This could be due to a lack of clarity regarding the interpretation of the model (analytic or holistic), about which only six reviews were explicit. We call on the field to clarify the interpretation of TPACK and to decide on which research would be needed to test the model. We argue that focused review studies could be one way to significantly advance the TPACK research field.

TPACK框架描述了教育者需要哪些知识来有效地将技术整合到教学的特定内容中。这些整合的知识是TPACK结合的特定领域，即所教授的内容、所选择的教学方法和所使用的技术。鉴于有大量关于TPACK的研究文献，将综述研究集中在一个领域似乎是有用的。例如，一篇综述可以用一种特定的技术来总结关于教师TPACK的已知情况，比较和结合跨内容领域或教学方法的文献。相反，审查也可以侧重于特定的内容或特定的教学方法。在这篇综述中，我们调查了TPACK的综述研究在多大程度上关注于特定领域（技术、教学法或内容）或TPACK框架中相关的知识组件。通过对32篇综述性研究的系统文献回顾，我们发现很少有综述将其研究问题、选择标准或结果集中在特定的领域或知识组成部分。这可能是由于缺乏关于模型解释（分析的或整体的）的清晰度，其中只有六个评论是明确的。我们呼吁该领域澄清对TPACK的解释，并决定需要哪些研究来测试该模型。我们认为，重点综述研究可能是显著推进TPACK研究领域的一种方法。

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引用次数: 0