Computers and Education Open最新文献_第5页

Moderating effects of student heterogeneity on community of inquiry affective outcomes: A multigroup analysis 学生异质性对探究社区情感结果的调节作用：多组分析

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-08-05 DOI: 10.1016/j.caeo.2025.100276

Teng Seng Choo , Hazri Jamil , Lei Mee Thien

This study examines the influence of student background attributes on the relationships between Community of Inquiry (CoI) presences and affective learning outcomes in online courses. Using partial least squares structural equation modeling (PLS-SEM) and multigroup analysis, the study investigated how gender, prior online course experience, and degree level moderate the effects of teaching, cognitive, social, and metacognitive presence on perceived learning and satisfaction. Data were collected from 479 students at a Malaysian public university. Results show that gender and prior experience moderate some relationships between CoI presences and perceived learning, but not perceived satisfaction. Specifically, male students perceive greater learning benefits from metacognitive presence compared with females, while females perceive higher learning from cognitive presence. Students with prior online course experience report significantly higher perceived learning from metacognitive presence compared with inexperienced students. Degree level (undergraduate vs. postgraduate) does not significantly moderate most relationships, though measurement invariance issues were found for teaching presence across degree levels. The findings highlight the importance of considering student subgroup heterogeneity in online education research and practice. The result suggests tailored instructional strategies that consider gender differences and prior online learning experience. This study contributes to a more nuanced understanding of how diverse learners experience and benefit from different aspects of the online learning environment, with implications for course design and delivery.

本研究探讨了学生背景属性对在线课程探究社区（CoI）存在与情感学习成果之间关系的影响。采用偏最小二乘结构方程模型（PLS-SEM）和多组分析，研究了性别、在线课程经历和学位水平如何调节教学、认知、社会和元认知存在对感知学习和满意度的影响。数据收集自马来西亚一所公立大学的479名学生。结果表明，性别和先前经验调节了CoI存在与感知学习之间的关系，但不调节感知满意度。具体而言，男生比女生更能从元认知在场中获得学习收益，而女生则能从认知在场中获得更高的学习收益。与没有在线课程经验的学生相比，有在线课程经验的学生对元认知存在的感知学习显著提高。学位水平（本科与研究生）对大多数关系没有显著调节作用，尽管在不同学位水平的教学存在中发现了测量不变性问题。研究结果强调了在在线教育研究和实践中考虑学生亚群异质性的重要性。结果表明，考虑到性别差异和先前的在线学习经验，量身定制的教学策略。这项研究有助于更细致地了解不同的学习者如何体验和受益于在线学习环境的不同方面，并对课程设计和交付产生影响。

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引用次数: 0

Location-based augmented reality in education: A systematic literature review 基于位置的增强现实在教育中的应用：系统的文献综述

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-08-05 DOI: 10.1016/j.caeo.2025.100277

Xavier Fonseca , Pia Spangenberger , Manuel Baer , Rene Schmidt , Heinrich Söbke

The domain of Location-based Augmented Reality (LBAR) in education is growing rapidly with the increasing ubiquity of mobile devices and their advanced capabilities. LBAR enables the superimposition of digital content onto physical environments and has been recognized for its transformative potential in educational contexts. Despite its advantages, the adoption of LBAR in education remains limited, hindered by several challenges. This paper presents a systematic review of peer-reviewed literature from 2000 to 2023 to assess the current state of LBAR in education. It explores 1) the state of the art in LBAR research, 2) its use cases and reported impacts across educational levels, and 3) the challenges and limitations identified in existing studies. Among the 50 studies included in the review, 38 % of investigated studies indicate a positive acceptance of LBAR and evident enthusiasm regarding LBAR’s application for learning purposes. However, multidimensional complexities are revealed at the methodological, technological, pedagogical, and at content and organisational levels. While LBAR tools present strong potential to enhance learning experiences, that potential is not yet fully realized. Their long-term value depends on how well they are integrated into established pedagogical practices, learning content, and educational contexts.

随着移动设备及其先进功能的日益普及，基于位置的增强现实（LBAR）在教育领域的发展迅速。LBAR能够将数字内容叠加到物理环境中，并因其在教育环境中的变革潜力而得到认可。尽管有其优势，LBAR在教育中的应用仍然有限，受到一些挑战的阻碍。本文对2000年至2023年的同行评议文献进行了系统回顾，以评估LBAR在教育中的现状。它探讨了1)LBAR研究的现状，2)它的用例和报告的跨教育水平的影响，以及3)现有研究中确定的挑战和限制。在本次综述的50项研究中，有38%的研究对LBAR表示积极接受，并对LBAR应用于学习有明显的热情。然而，在方法、技术、教学、内容和组织层面上揭示了多维复杂性。虽然LBAR工具具有增强学习经验的强大潜力，但这种潜力尚未得到充分实现。它们的长期价值取决于它们与已建立的教学实践、学习内容和教育环境的整合程度。

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引用次数: 0

The chain mediating effect of academic anxiety and performance expectations between academic self-efficacy and generative AI reliance 学业焦虑、成绩期望在学业自我效能感与生成人工智能依赖之间的链式中介作用

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-07-31 DOI: 10.1016/j.caeo.2025.100275

Ting Huang , Chenze Wu

While Generative Artificial Intelligence (GenAI) tools have been used by an increasing number of students, many teachers and researchers recognized that excessive use of these tools may have adverse impacts on students’ academic development. However, the underlying mechanisms driving GenAI reliance and its consequences remain underexplored. This study aimed to address these gaps by investigating the relationships among academic self-efficacy, academic anxiety, performance expectations, and GenAI reliance, as well as examining the consequences of GenAI reliance and coping strategies to mitigate these issues. Data were collected from 337 university students in a Chinese university and analyzed using Pearson correlation, chain mediation effect, and thematic analysis. The results indicated no significant direct relationship between academic self-efficacy and GenAI reliance. However, academic anxiety and performance expectations were found to mediate this relationship. The most salient consequences of GenAI reliance were decreased independent thinking ability, reduced innovative thinking ability, restricted self-reflection, and limited critical thinking ability. Additionally, students’ self-initiated and expected teacher-initiated strategies to alleviate these consequences were recognized. This study contributes to the limited understanding of GenAI reliance and provides valuable insights for educators and academic institutions in directing students toward the appropriate and critical utilization of GenAI tools.

虽然越来越多的学生使用生成式人工智能（GenAI）工具，但许多教师和研究人员认识到，过度使用这些工具可能会对学生的学业发展产生不利影响。然而，驱动GenAI依赖的潜在机制及其后果仍未得到充分探索。本研究旨在通过调查学业自我效能、学业焦虑、成绩期望和基因依赖之间的关系，以及研究基因依赖的后果和缓解这些问题的应对策略，来解决这些差距。本研究以某高校337名大学生为研究对象，采用Pearson相关、连锁中介效应和主题分析法进行数据分析。结果表明，学业自我效能感与GenAI依赖之间没有显著的直接关系。然而，学业焦虑和成绩期望对这种关系起中介作用。依赖GenAI最显著的后果是独立思考能力下降、创新思维能力下降、自我反思受限和批判性思维能力受限。此外，学生的自我发起和期望教师发起的策略，以减轻这些后果得到认可。这项研究有助于对GenAI依赖的有限理解，并为教育工作者和学术机构指导学生适当和关键地使用GenAI工具提供了有价值的见解。

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引用次数: 0

Revisiting generalizability theory in the age of artificial intelligence: Implications for empirical educational research 人工智能时代对概括性理论的重新审视：对实证教育研究的启示

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-07-31 DOI: 10.1016/j.caeo.2025.100278

Peer-Benedikt Degen

The rise of AI in education presents both transformative opportunities and methodological challenges. This paper revisits Generalizability Theory (G-Theory) as a robust framework to assess the reliability and fairness of AI-driven tools across diverse educational contexts. It is argued that G-Theory’s variance decomposition logic is uniquely suited to disentangle the multifaceted sources of error introduced by evolving AI systems, user diversity, and complex learning environments. Through empirical use cases it is illustrated how G-Theory can support the design of equitable, scalable, and context-sensitive AI applications. We further A G-Theory Readiness Checklist to guide researchers in designing studies with AI as a methodological facet is proposed. Finally, conceptual, technical, ethical, pedagogical, and regulatory limitations and implications for study designs are highlighted. The paper concludes with suggestions for future research.

人工智能在教育领域的兴起既带来了变革机遇，也带来了方法论上的挑战。本文将概括性理论（g理论）作为一个强大的框架来评估人工智能驱动的工具在不同教育背景下的可靠性和公平性。有人认为，g理论的方差分解逻辑非常适合于解决由不断发展的人工智能系统、用户多样性和复杂的学习环境引入的多方面的错误来源。通过实证用例，说明了G-Theory如何支持公平、可扩展和上下文敏感的人工智能应用程序的设计。我们进一步提出了一个g理论准备检查表，以指导研究人员设计人工智能作为方法学方面的研究。最后，强调了研究设计的概念、技术、伦理、教学和监管方面的限制和影响。最后，对今后的研究提出了建议。

引用次数: 0

Integrating artificial intelligence in higher education: perceptions, challenges, and strategies for academic innovation 高等教育中人工智能的整合：学术创新的认知、挑战和策略

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-07-30 DOI: 10.1016/j.caeo.2025.100274

Dusana Alshatti Schmidt, Bedour Alboloushi, Anisha Thomas, Rodrigo Magalhaes

In recent years artificial intelligence (AI) has emerged as a transformative force across various industries impacting the workforce dynamics. To ensure that graduates possess the necessary skills, higher education institutions are exploring new ways to align their approaches with labor market demands. This study examines how AI is being integrated in higher education institutions, aimed at gaining an understanding of how students and faculty perceive AI, how it is applied, its impact on performance, the challenges encountered, and the strategies used for its adoption. The study also aims to provide practical, evidence-based recommendations for effective integration of AI into curriculum. The research employs a qualitative approach, incorporating focus group interviews and open-ended questionnaires. Findings indicate that while both faculty and students recognize AI's transformative potential and benefits, they are also concerned about its impact on critical thinking and academic integrity. Faculty use AI tools for teaching and assessment, but face challenges with tool accuracy and integration. Students utilize AI for academic tasks but struggle with reliability and ethical issues. The study highlights the need for increased awareness, continuous professional development, and ethical guidelines to overcome these challenges. The findings of this study contribute to the successful adoption of AI in higher education in general, ensuring that both teaching and learning processes are enriched by the potential of AI.

近年来，人工智能（AI）已经成为影响劳动力动态的各个行业的变革力量。为了确保毕业生具备必要的技能，高等教育机构正在探索新的方法，使他们的方法与劳动力市场的需求保持一致。本研究考察了人工智能如何融入高等教育机构，旨在了解学生和教师如何看待人工智能、人工智能如何应用、人工智能对绩效的影响、遇到的挑战以及采用人工智能的策略。该研究还旨在为将人工智能有效整合到课程中提供实用的、基于证据的建议。该研究采用定性方法，结合焦点小组访谈和开放式问卷调查。研究结果表明，尽管教师和学生都认识到人工智能的变革潜力和好处，但他们也担心人工智能对批判性思维和学术诚信的影响。教师使用人工智能工具进行教学和评估，但面临工具准确性和集成方面的挑战。学生们利用人工智能完成学术任务，但却在可靠性和道德问题上苦苦挣扎。该研究强调了提高意识、持续专业发展和道德准则以克服这些挑战的必要性。这项研究的结果有助于在高等教育中成功采用人工智能，确保教学和学习过程都被人工智能的潜力所丰富。

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引用次数: 0

Path to intelligent evaluation: Utilizing power BI for enhanced performance insights 智能评估之路：利用电源BI增强性能洞察

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-07-25 DOI: 10.1016/j.caeo.2025.100271

Xiaojun Li, Yueke Dong, Zhi Ai

This paper aims to enhance the performance evaluation process for university faculty by tackling the shortcomings of current assessment methods, including the “one-size-fits-all” approach, the excessive focus on research over teaching, and the absence of automated and intelligent data analysis. The study utilizes performance data from 869 faculty members and employs Microsoft Power BI along with its various components to facilitate comprehensive and categorical assessments, improving both the intelligence of the evaluation process and the visualization of the assessment results.

本文旨在通过解决当前评估方法的缺陷，包括“一刀切”的方法，过度关注研究而不是教学，以及缺乏自动化和智能的数据分析，来改进大学教师的绩效评估过程。该研究利用了来自869名教师的绩效数据，并采用Microsoft Power BI及其各种组件来促进全面和分类的评估，提高了评估过程的智能性和评估结果的可视化。

引用次数: 0

How, when and for what purpose 16 primary school teachers use ICT: A field study 16名小学教师如何、何时以及出于何种目的使用ICT：一项实地研究

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-07-25 DOI: 10.1016/j.caeo.2025.100270

Elena Ramírez Orellana , Inmaculada Martín Sánchez , Jorge Martín-Domínguez , Inés Rodríguez Martín

This article explores the way in which 16 primary school teachers use ICT resources in their classrooms. More specifically, the analysis seeks to discover whether there is a link between the ICT resources the teachers use and the types of activities involved in their classes. The premise underpinning this approach is that teachers adapt and adjust the use of ICT resources to suit the teaching methods they apply in the classroom. A multiple case study was conducted with 16 primary school teachers, who were recorded for three whole schooldays over three school years, furnishing a total of 159.5 h. The research design was based on a mixed methods approach. The results indicate that the teachers link ICT resources in the classroom to the now traditional use of analogue ones and to teaching approaches involving a wide range of different tasks and exercises. Digital resources are barely used in templates of activity related to pupil assessment or planning the school day. The results provide guidelines on teacher training that simultaneously address ICTs and didactic competencies that respond to the challenges of classroom practice. A further finding involves the need to adjust the design of educational ICT resources to the patterns of real classroom activity.

本文探讨了16名小学教师在课堂上使用信息通信技术资源的方式。更具体地说，分析旨在发现教师使用的信息和通信技术资源与其课堂所涉及的活动类型之间是否存在联系。支持这种方法的前提是教师适应和调整ICT资源的使用，以适应他们在课堂上应用的教学方法。本研究对16名小学教师进行了多案例研究，他们在三个学年中记录了三个完整的学日，总共159.5小时。研究设计基于混合方法。结果表明，教师将课堂上的ICT资源与现在传统的模拟资源使用以及涉及广泛不同任务和练习的教学方法联系起来。数字资源很少用于与学生评估或学校计划相关的活动模板中。研究结果为教师培训提供了指导方针，同时解决了应对课堂实践挑战的信息通信技术和教学能力问题。进一步的发现涉及到需要调整教育ICT资源的设计，以适应真实课堂活动的模式。

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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 : 2025-07-25 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

Computing education using generative artificial intelligence tools: A systematic literature review 使用生成式人工智能工具的计算教育：系统的文献综述

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-06-21 DOI: 10.1016/j.caeo.2025.100266

Friday Joseph Agbo , Chris Olivia , Godsalvation Oguibe , Ismaila Temitayo Sanusi , Godwin Sani

Recent advances in generative artificial intelligence (GenAI) are revolutionizing computing education, causing paradigm shifts from the traditional teaching and learning technique. Studies are exploring GenAI tools in computing classes from intro to advanced topics with the aim to showcase how to reshape computing education in this new era of GenAI. This study examined the computing education research landscape to unravel how GenAI tools have been used in that domain, what are the characteristics of those studies in terms of computing topics, context, and tools, offering insights into the pros and cons for integrating GenAI in computing education based on the performance indicators reported in the literature. This study employed a systematic literature review approach to identify and analyze 78 relevant articles. The findings of this study show that educators are exploring GenAI tools in computer sciences classes from K-12 through graduate levels. Beyond programming education, GenAI has also been explored in college upper-level computer science courses such as Computer Graphics and Human-Computer Interaction. The performance analysis of these tools are presented in this study, indicating a progressive advancement from when the technology was introduced. This study also discusses learning outcomes, good practices, and potential risks to avoid when exploring GenAI, as reported in the studies, which could guide how computing educators design their instructional strategies using GenAI. This study contributes to broadening the understanding of exploring, adapting, or using GenAI in computer science education and may spark interest among educators who are unwilling to explore GenAI or may not understand how or what strategies to adopt.

生成式人工智能（GenAI）的最新进展正在彻底改变计算机教育，导致传统教学技术的范式转变。研究人员正在探索GenAI工具在计算机课程中的应用，从入门到高级主题，目的是展示如何在GenAI的新时代重塑计算机教育。本研究考察了计算机教育研究的前景，以揭示GenAI工具如何在该领域中使用，这些研究在计算主题、背景和工具方面的特点是什么，并根据文献中报告的绩效指标，提供了将GenAI整合到计算机教育中的利弊。本研究采用系统文献回顾的方法，对78篇相关文献进行识别和分析。这项研究的结果表明，教育工作者正在从K-12到研究生阶段的计算机科学课程中探索GenAI工具。除了编程教育，GenAI也被用于大学高级计算机科学课程，如计算机图形学和人机交互。本研究提出了这些工具的性能分析，表明该技术自引入以来一直在进步。本研究还讨论了在探索GenAI时要避免的学习结果、良好实践和潜在风险，这些研究报告可以指导计算机教育者如何使用GenAI设计他们的教学策略。本研究有助于拓宽对在计算机科学教育中探索、适应或使用GenAI的理解，并可能激发那些不愿探索GenAI或可能不知道如何或采用何种策略的教育者的兴趣。

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引用次数: 0

Exploring the association between digital storytelling and self-regulated learning: a review of claims 探索数字叙事与自我调节学习之间的关系：对相关主张的回顾

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-06-18 DOI: 10.1016/j.caeo.2025.100267

Dinaol Urgessa Gita , Bekalu Ferede , Jo Tondeur

Following the advancement of digital technology, digital storytelling has increasingly evolved in fostering various aspects of students' learning, including self-regulated learning. However, there is a deficiency in studies regarding how digital storytelling is related to self-regulated learning and its specific domains. This review of claims explored the association between digital storytelling and self-regulated learning. Systematic searches in Scopus, Web of Science, and Google Scholar databases were employed. After utilizing inclusion-exclusion criteria, 28 studies were selected for review. A qualitative conceptual review design was employed. Claims were carefully collected from each study. Thematic analysis was employed to analyze data. Our analysis reveals that digital storytelling enhances (meta-) cognitive, motivational, emotional, and behavioral regulations of students, though some domains received little attention. Moreover, to create digital storytelling successfully, students’ use of the (meta-) cognitive strategies such as planning, goal setting, researching, imagination, and reflection contribute vital role. In conclusion, while it's clear that digital storytelling and self-regulated learning are associated, this association is rudimentary; more research is needed to explore how digital storytelling improves all domains of self-regulated learning and how self-regulated learning also influences digital storytelling.

随着数字技术的进步，数字讲故事在促进学生学习的各个方面，包括自我调节学习方面，越来越得到发展。然而，关于数字讲故事与自我调节学习及其特定领域之间的关系的研究存在不足。这篇综述探讨了数字讲故事和自我调节学习之间的关系。系统检索Scopus、Web of Science和谷歌Scholar数据库。采用纳入-排除标准后，选择28项研究进行综述。采用定性概念回顾设计。从每项研究中都仔细收集了声明。采用主题分析法对数据进行分析。我们的分析表明，数字讲故事增强了学生的（元）认知、动机、情感和行为规范，尽管有些领域很少受到关注。此外，要成功地创作数字故事，学生对计划、目标设定、研究、想象和反思等（元）认知策略的使用也起着至关重要的作用。综上所述，虽然数字叙事和自我调节学习之间存在明显的联系，但这种联系还很初级；需要更多的研究来探索数字讲故事如何改善自我调节学习的所有领域，以及自我调节学习如何影响数字讲故事。

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引用次数: 0