Computers and Education Open最新文献_第7页

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 : 2025-12-01 Epub 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

Special Issue: Datafied by default: Examining the intersect between children's digital rights and education 特刊：默认数据化：审视儿童数字权利与教育之间的交集

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2024-12-13 DOI: 10.1016/j.caeo.2024.100237

Tiffani Apps , Karley Beckman , Rebecca Ng

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 : 2025-12-01 Epub 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

Does ChatGPT-enhanced collaborative learning foster critical thinking in education? A Bloom’s Taxonomy perspective chatgpt增强的协作学习在教育中培养批判性思维吗？Bloom的分类法透视图

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-11-29 DOI: 10.1016/j.caeo.2025.100316

Abdhy Aulia Adnans , Yithro Serang , Ixora Javanisa Eunike , Andri Dayarana K. Silalahi

This study examines how ChatGPT-supported collaborative learning influences critical thinking in health education using Bloom’s Taxonomy. Purposive sampling was used to collect data from 665 Indonesian health students through an online survey. Partial Least Square – Structural Equation Modelling (PLS-SEM) assessed the direct effects of cognitive processes on critical thinking. Necessary Condition Analysis (NCA) identified essential cognitive conditions, while fuzzy sets qualitative comparative analysis (fsQCA) explored different cognitive pathways leading to high or low critical thinking. Collaborative learning significantly enhances understanding, applying, and remembering. Understanding has the strongest effect on critical thinking, while applying and remembering have moderate effects. These findings suggest that deep comprehension drives analytical reasoning, whereas applying and remembering serve complementary roles. NCA confirms that understanding and applying are necessary for fostering critical thinking, while remembering plays a supporting role. fsQCA results indicate that students who combine deep understanding with memory retention exhibit strong critical thinking. In contrast, students who rely solely on remembering without comprehension or application struggle to develop higher-order reasoning. This study reveals that ChatGPT does not inherently enhance critical thinking but must be integrated into structured collaborative learning. Effective AI-assisted education requires active discussion, application, and critical evaluation of AI-generated insights. These findings offer a framework for optimizing AI-driven health education to support both knowledge acquisition and analytical reasoning in clinical decision-making.

本研究使用Bloom分类法考察了chatgpt支持的协作学习如何影响健康教育中的批判性思维。采用有目的抽样方法，对665名印尼卫生专业学生进行在线调查。偏最小二乘-结构方程模型（PLS-SEM）评估了认知过程对批判性思维的直接影响。必要条件分析（NCA）确定了必要的认知条件，而模糊集定性比较分析（fsQCA）探索了导致高批判性思维和低批判性思维的不同认知途径。协作学习可以显著提高理解、应用和记忆能力。理解对批判性思维的影响最大，而运用和记忆的影响一般。这些发现表明，深度理解驱动分析推理，而应用和记忆则起到互补的作用。NCA证实理解和应用对于培养批判性思维是必要的，而记忆起着辅助作用。fsQCA结果表明，将深刻理解与记忆保持相结合的学生表现出较强的批判性思维。相比之下，仅仅依靠记忆而不理解或应用的学生很难发展高阶推理。这项研究表明，ChatGPT本身并不能增强批判性思维，但必须将其整合到结构化的协作学习中。有效的人工智能辅助教育需要对人工智能产生的见解进行积极的讨论、应用和批判性评估。这些发现为优化人工智能驱动的健康教育提供了一个框架，以支持临床决策中的知识获取和分析推理。

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引用次数: 0

A review of computational thinking interventions in upper elementary education 小学高年级计算思维干预研究综述

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-08-08 DOI: 10.1016/j.caeo.2025.100252

María Eugenia Curi, Anaclara Gerosa, Marcos Viera, Alejandra Carboni

This review examines current trends in Computational Thinking (CT) educational interventions. Analyzing 54 studies from 2012 to 2024, the review identifies key trends in the implementation of CT interventions, including duration, number of participants, and programming tools. Most interventions with upper-elementary students span more than a month, involve between 20 and 100 children, and use unplugged activities and visual programming environments. The review also investigates the extent to which student context data, such as gender and socioeconomic background, are considered, highlighting the importance of these factors in CT interventions. The findings suggest that while some interventions account for gender and contextual differences, there is a potential for a greater focus on these aspects to address social inequalities. This study provides valuable insights into the potential impact and inclusiveness of CT educational strategies, serving as a resource for educators, researchers, and policy makers aiming to improve CT integration into educational frameworks.

本文回顾了当前计算机思维（CT）教育干预的趋势。该综述分析了2012年至2024年的54项研究，确定了CT干预措施实施的关键趋势，包括持续时间、参与者人数和编程工具。大多数对小学高年级学生的干预持续一个多月，涉及20到100名儿童，并使用不插电的活动和可视化编程环境。该综述还调查了学生背景数据（如性别和社会经济背景）被考虑的程度，强调了这些因素在CT干预中的重要性。研究结果表明，虽然一些干预措施可以解释性别和背景差异，但有可能更加关注这些方面，以解决社会不平等问题。本研究为CT教育策略的潜在影响和包容性提供了有价值的见解，为旨在提高CT融入教育框架的教育工作者、研究人员和政策制定者提供了资源。

引用次数: 0

Understanding use of evidence in AI ethics guidelines development through a PRISMA-ETHICS informed scoping review of guidelines 通过prism - ethics知情范围审查指南，了解人工智能伦理指南制定中证据的使用情况

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-08-07 DOI: 10.1016/j.caeo.2025.100281

Simon Knight

Objectives

There have been recent calls for new ethics guidelines regarding the use of artificial intelligence in research. How should we go about developing such ethics guidance documents with respect to emerging contexts such as new technologies, and established domains such as research in education? This paper provides a PRISMA-ETHICS informed scoping review of approaches to ethics guideline development, the structures of ethics guidelines, and their audiences and purposes drawing on the context of education and AI.

Search and synthesis approach

A search of scholarly and grey literature was conducted to identify both ethics guidelines and material discussing their development; n = 592 distinct items were identified, including 182 that identified via recent reviews of AI ethics guidelines. n = 47 guideline-sets were identified as ‘guidelines’.

Data extraction and analysis

Guidelines were analysed with respect to their development approach, audience and purpose, and structural elements through which guidance is delivered; most included statements regarding their development approach (79 %) and audience (72 %). Where evidence underpinning the guidance was discussed, it was largely at a global content level (69 %), rather than with respect to the specific context/domain of the guideline use, principles drawn on, or approaches and strategies one might adopt in navigating ethical issues (23, 29, and 21 % respectively). Across the guidelines the only universal feature was the provision of an overview statement. We conclude with recommendations regarding the development of ethics guidelines, and their structure.

Funding

No external funding was received.

Systematic review registration

The review was not pre-registered.

最近有人呼吁制定关于在研究中使用人工智能的新伦理准则。我们应该如何针对新兴背景（如新技术）和既定领域（如教育研究）制定这样的伦理指导文件？本文根据教育和人工智能的背景，对伦理准则制定的方法、伦理准则的结构及其受众和目的进行了prism - ethics知情范围审查。检索和综合方法：对学术文献和灰色文献进行检索，以确定伦理准则和讨论其发展的材料；n = 592个不同的项目被确定，其中182个是通过最近对人工智能伦理准则的审查确定的。N = 47个指南集被确定为“指南”。数据提取和分析对指南的制定方法、受众和目的以及提供指南的结构要素进行了分析；大多数都包含了关于他们的开发方法（79%）和受众（72%）的声明。在讨论支持指南的证据时，主要是在全球内容层面（69%），而不是在指南使用的特定背景/领域、所采用的原则或在处理伦理问题时可能采用的方法和策略（分别为23%、29%和21%）。在所有指导方针中，唯一的通用特征是提供概述声明。最后，我们提出了关于制定道德准则及其结构的建议。没有收到外部资金。系统综述注册该综述未进行预注册。

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引用次数: 0

Unraveling the mechanisms and effectiveness of AI-assisted feedback in education: A systematic literature review 揭示教育中人工智能辅助反馈的机制和有效性：系统的文献综述

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-08-24 DOI: 10.1016/j.caeo.2025.100284

Shen Ba , Lan Yang , Zi Yan , Chee Kit Looi , Dragan Gašević

Rapid advancements in Artificial Intelligence (AI) have prompted growing interest in leveraging AI for educational feedback. Yet, the centrality of the learner in this process is often overshadowed by technological excitement, and a broad understanding of AI-assisted feedback (AIFB) in education remains evolving. To address this gap, we conducted a systematic review of 129 peer-reviewed journal articles (2014–2023) based on widely used AI-related search terms to examine how AI, especially generative AI, supports feedback mechanisms and influences learner perceptions, actions, and outcomes. Our analysis identified a sharp rise in AIFB research after 2018, driven by modern large language models. We found that AI tools flexibly cater to multiple feedback foci (task, process, self-regulation, and self) and complexity levels (basic, intermediate, and elaborated). Our findings demonstrate that AIFB can effectively enhance targeted learning outcomes. By employing a transparent and field-aligned methodology, we synthesized recent advances and offers actionable insights for both research and practice. While the focus on widely recognized AI-related search terms ensures strong comparability and relevance, some specialized subfields (e.g., Automated Writing Evaluation), are less prominent in this synthesis. The study also highlights the ongoing need for clearer reporting of underlying AI algorithms. Building on these findings, we propose an original conceptual model that synthesizes current progress and offers a roadmap for future explorations. By illuminating the affordances and constraints of AIFB, we highlight the necessity for transparent methodological reporting and underscores the importance of integrating pedagogical and technological insights to promote meaningful, learner-centered feedback.

人工智能（AI）的快速发展促使人们对利用AI进行教育反馈的兴趣日益浓厚。然而，学习者在这一过程中的中心地位往往被技术兴奋所掩盖，对教育中人工智能辅助反馈（AIFB）的广泛理解仍在不断发展。为了解决这一差距，我们基于广泛使用的人工智能相关搜索词，对129篇同行评议的期刊文章（2014-2023）进行了系统综述，以研究人工智能（尤其是生成式人工智能）如何支持反馈机制并影响学习者的感知、行动和结果。我们的分析发现，在现代大型语言模型的推动下，2018年之后AIFB研究急剧上升。我们发现人工智能工具灵活地迎合了多个反馈焦点（任务、过程、自我调节和自我）和复杂性水平（基本、中级和详细）。我们的研究结果表明AIFB可以有效地提高目标学习成果。通过采用透明和与领域一致的方法，我们综合了最近的进展，并为研究和实践提供了可操作的见解。虽然关注广泛认可的人工智能相关搜索词确保了很强的可比性和相关性，但一些专门的子领域（例如，自动写作评估）在这个综合中不太突出。该研究还强调了对底层人工智能算法进行更清晰报告的持续需求。在这些发现的基础上，我们提出了一个原始的概念模型，它综合了当前的进展，并为未来的探索提供了路线图。通过阐明AIFB的优点和局限性，我们强调了透明的方法报告的必要性，并强调了整合教学和技术见解以促进有意义的、以学习者为中心的反馈的重要性。

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引用次数: 0

Video game player profiles among university students: Impact of game preferences and academic background 大学生电子游戏玩家特征：游戏偏好和学术背景的影响

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-08-23 DOI: 10.1016/j.caeo.2025.100280

Emilio García-Cabrera , Francisco Luna-Perejón , Miguel Ángel Pertegal-Vega , Luis Muñoz-Saavedra , José Luis Sevillano-Ramos , Lourdes Miró-Amarante

Video games have become a widespread cultural and economic phenomenon, with Spain ranking among the top European countries in gaming consumption. This study examines the gaming habits and preferences of 440 university students at the University of Seville, classifying player profiles based on game preferences and academic background. A cross-sectional study was conducted using an anonymous online survey, and principal component analysis identified three distinct player profiles: Competitive, Explorer, and Socializer.

Findings indicate that gaming frequency varies significantly by academic discipline, with students in technical fields playing more frequently and preferring PC gaming, while those in social and health sciences favor mobile gaming. Moreover, the Explorer profile is associated with higher gaming frequency, whereas the Socializer profile is linked to lower engagement. Contrary to common concerns, gaming time does impact academic performance, particularly when exceeding five hours per day.

Findings suggest that gamification in higher education should align with students' gaming profiles to boost engagement and learning performance. While offering useful insights, the study's cross-sectional design and self-reported data limit its scope. Longitudinal research is needed to assess long-term academic and well-being impacts.

电子游戏已经成为一种广泛的文化和经济现象，西班牙在游戏消费方面位居欧洲前列。这项研究调查了塞维利亚大学440名大学生的游戏习惯和偏好，根据游戏偏好和学术背景对玩家进行了分类。通过匿名在线调查进行的横断面研究，主成分分析确定了三种不同的玩家特征：竞争型、探索型和社交型。研究结果表明，不同学科的学生玩游戏的频率差异很大，技术领域的学生更喜欢玩PC游戏，而社会和健康科学领域的学生更喜欢玩手机游戏。此外，Explorer用户的游戏频率较高，而Socializer用户的粘性较低。与人们普遍担心的相反，游戏时间确实会影响学习成绩，尤其是每天超过5小时的时候。研究结果表明，高等教育中的游戏化应该与学生的游戏特征相结合，以提高参与度和学习表现。虽然提供了有用的见解，但该研究的横截面设计和自我报告数据限制了其范围。需要进行纵向研究来评估长期的学术和福祉影响。

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引用次数: 0

Generative AI chatbots in higher education: Student experiences and perceived ethical challenges 高等教育中的生成式AI聊天机器人：学生体验和感知到的伦理挑战

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-11-17 DOI: 10.1016/j.caeo.2025.100311

Neda Hadinejad , Katarina Sperling , Cormac McGrath

The integration of generative artificial intelligence (GAI) chatbots in higher education has introduced both opportunities and challenges for students’ academic practices. To date, most qualitative research has examined the implications of this phenomenon for teaching practices and the experiences of teachers. This explorative study investigates how students use GAI chatbots in their studies and how they evaluate AI generated text, particularly in relation to academic integrity, reliability, and ethical norms. Using a qualitative research approach, we conducted semi-structured interviews with higher education students to a) examine students’ experiences of using GAI chatbots in their academic studies, and b) to explore how students perceive the ethical impact of using chatbots on their studies. The findings reveal that while students use GAI chatbots to support writing, idea generation, and language improvement, they also face challenges related to plagiarism concerns, the reliability of AI-generated content, and the lack of clear institutional guidelines on responsible AI use. Additionally, the study highlights how students develop individual strategies to navigate these challenges, including seeking validation from educators and critically assessing AI-generated outputs. The findings emphasize the need for clearer academic policies and ethical frameworks to support students in making informed and responsible decisions about the use of GAI chatbots in higher education.

生成式人工智能（GAI）聊天机器人在高等教育中的整合为学生的学术实践带来了机遇和挑战。迄今为止，大多数定性研究都考察了这一现象对教学实践和教师经验的影响。这项探索性研究调查了学生如何在学习中使用人工智能聊天机器人，以及他们如何评估人工智能生成的文本，特别是在学术诚信、可靠性和道德规范方面。采用定性研究方法，我们对高等教育学生进行了半结构化访谈，以a)检查学生在学术研究中使用GAI聊天机器人的经历，以及b)探索学生如何看待使用聊天机器人对他们学习的道德影响。研究结果显示，虽然学生们使用人工智能聊天机器人来支持写作、创意产生和语言提高，但他们也面临着与剽窃问题、人工智能生成内容的可靠性以及缺乏明确的负责任的人工智能使用制度指南相关的挑战。此外，该研究还强调了学生如何制定个人策略来应对这些挑战，包括寻求教育工作者的认可和批判性地评估人工智能生成的输出。研究结果强调，需要制定更清晰的学术政策和道德框架，以支持学生在高等教育中使用GAI聊天机器人时做出明智和负责任的决定。

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引用次数: 0

Innovative leadership and sustainability in higher education management 高等教育管理的创新领导力和可持续性

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-07-25 DOI: 10.1016/j.caeo.2025.100272

Maria Flori , Elena-Cristina Raulea , Ciprian Raulea

This study proposes a sustainability-driven vector model designed to enhance adaptive governance and decision-making in higher education. Drawing from systems theory, sustainability science, and mathematical logic—including automorphic transformations and fractal reasoning—the model incorporates continuous feedback loops and vector-based structures to simulate institutional processes such as leadership, sensing, and strategic coordination. Unlike traditional linear management models, the proposed framework enables dynamic, data-informed responses to educational disruptions through recursive logic and commutative diagrams. A dual-scenario application demonstrates its relevance for optimizing digital infrastructure, improving resource allocation, and supporting anticipatory leadership in hybrid and technology-integrated environments. By aligning interdisciplinary theory with operational logic, this study contributes a replicable framework for advancing institutional agility, resilience, and sustainability in the context of digital transformation in higher education.

本文提出了一个可持续发展驱动的矢量模型，旨在提高高等教育的适应性治理和决策。该模型借鉴了系统理论、可持续性科学和数学逻辑（包括自同构变换和分形推理），结合了连续的反馈回路和基于向量的结构，以模拟领导、感知和战略协调等制度过程。与传统的线性管理模型不同，该框架通过递归逻辑和交换图实现对教育中断的动态、数据知情的响应。双场景应用证明了其在优化数字基础设施、改善资源分配以及支持混合和技术集成环境中的预期领导方面的相关性。通过将跨学科理论与操作逻辑结合起来，本研究为提高高等教育数字化转型背景下的制度敏捷性、弹性和可持续性提供了一个可复制的框架。

引用次数: 0