Computers and Education Open最新文献_第7页

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

Research on the coupling of talent cultivation and reform practice of higher education in architecture 建筑专业人才培养与高等教育改革实践的耦合研究

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-06-16 DOI: 10.1016/j.caeo.2025.100268

Zhiwu Zhou , Qiong Tian , Julián Alcalá , Víctor Yepes

With the sustainable development of the global construction industry and the rapid development of the intelligent building industry, colleges and universities worldwide are stepping up the training of comprehensive talents in intelligent application in the construction profession. Therefore, establishing a cross-regional and perfect construction talent training system has become a critical research and practice topic for university researchers. This study uses computational procedures to fit mathematical theories, coupled model analysis, and other innovative training framework systems. It also analyzes the problems and shortcomings in talent training from three aspects: the current status of industrialization of higher education construction at home and abroad. Combined with the current status of talent training in higher education and the different needs of various countries for architectural talents, a Chinese-style "six-stage multi-module innovation optimization" training framework and a "construction talent training model" are proposed to improve the innovation system. Through in-depth research, a talent training goal system and improvement strategy adapted to the development of China's construction industrialization have been established. The research results effectively compensate for the shortcomings of higher vocational education in this field. The framework of this study can serve as a beacon for deepening education in the construction profession in various countries around the world, guiding higher vocational education to move towards the training of high-tech and high-skilled talents.

随着全球建筑业的持续发展和智能建筑产业的快速发展，世界各地的高校都在加大对建筑专业智能应用复合型人才的培养力度。因此，建立跨区域、完善建设的人才培养体系已成为高校科研工作者的重要研究和实践课题。本研究使用计算程序拟合数学理论、耦合模型分析及其他创新训练框架系统。并从国内外高等教育建设产业化现状三个方面分析了人才培养中存在的问题和不足。结合高等教育人才培养的现状和各国对建筑人才的不同需求，提出了中国式的“六阶段多模块创新优化”培养框架和“建筑人才培养模式”，以完善创新体系。通过深入研究，建立了适应中国建筑工业化发展的人才培养目标体系和提升策略。研究成果有效地弥补了高职教育在这方面的不足。本研究的框架可以作为世界各国深化建筑专业教育的灯塔，引导高等职业教育向培养高技术、高技能人才的方向发展。

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引用次数: 0

The Why and How prospective mathematics teachers want to employ digital mathematics tools in classrooms 未来的数学教师为什么以及如何在课堂上使用数字数学工具

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-06-16 DOI: 10.1016/j.caeo.2025.100269

Robert Weinhandl , Branko Anđić , Viktoria Riegler , Valentina Bleckenwegner , Selina Baldinger , Jonas Mayrhofer , Christoph Helm

Digital mathematics tools range from simple pocket calculators to computer algebra systems and dynamic geometry software up to AI applications for confirming mathematical proofs. Our study aims to identify what motivates prospective mathematics teachers to employ digital mathematics tools in their prospective teaching and how their behavioral intentions affect different forms of technology use. To achieve our research aim, we conducted a digital questionnaire study in which 489 prospective mathematics teachers participated. In terms of completeness, the data of 409 participants could be used for further analysis. The structural equation model analyses conducted in our study indicate that especially Performance Expectancy (β = 0.359) and Facilitating Conditions (β = 0.424) significantly influence the behavioral intentions of prospective mathematics teachers to use digital mathematics tools. In turn, behavioral intentions significantly influence how prospective mathematics teachers want to use digital mathematics tools in the classroom. Our findings highlight that Behavioral Intentions act as a key link between technology acceptance and Cognitive Engagement in prospective mathematics teachers. Additionally, demographic factors such as age, gender, and study progress moderate these relationships. These insights can inform teacher training programs by tailoring support to different groups to ensure more effective integration of digital tools in mathematics classrooms.

数字数学工具的范围从简单的袖珍计算器到计算机代数系统和动态几何软件，再到用于确认数学证明的人工智能应用程序。我们的研究旨在确定是什么激励未来的数学教师在他们的未来教学中使用数字数学工具，以及他们的行为意图如何影响不同形式的技术使用。为了达到我们的研究目的，我们进行了一项有489名准数学教师参与的数字问卷研究。在完整性方面，409名参与者的数据可用于进一步分析。本研究的结构方程模型分析表明，绩效期望（β = 0.359）和促进条件（β = 0.424）显著影响准数学教师使用数字数学工具的行为意向。反过来，行为意向显著影响未来数学教师在课堂上如何使用数字数学工具。我们的研究结果强调，行为意向在未来数学教师的技术接受和认知参与之间起着关键的作用。此外，年龄、性别和学习进度等人口因素会缓和这些关系。这些见解可以为教师培训计划提供信息，为不同群体提供量身定制的支持，以确保更有效地将数字工具整合到数学课堂中。

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引用次数: 0

Key CSCL research topics for K-12 practice: A modified Delphi study with practitioners and researchers CSCL在K-12实践中的主要研究课题：对从业者和研究者的修正德尔菲研究

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-06-01 DOI: 10.1016/j.caeo.2025.100265

Dalila Dragnić-Cindrić, Judi Fusco

Computer-supported collaborative learning (CSCL) is effective in improving students’ learning outcomes, yet CSCL research is rarely translated to classroom practice. To identify key CSCL research topics for K-12 STEM practice, we conducted a modified Delphi method study with a panel of practitioners and researchers. We relied on a knowledge mobilization framework to draw on expertise from both researchers, who produce new knowledge, and practitioners, who combine it with their pedagogical wisdom and use it in classrooms. We used the Delphi method because of its potential to address the power imbalances among panelists and modified it to facilitate knowledge mediation between knowledge production and use. The panelists identified seven key CSCL topics for translation from research into practice: Classroom discourse; Diversity, equity, and inclusion; Teacher preparation and professional development; Socially shared regulation of learning; Argumentation; Classroom orchestration and scripts; and Student and teacher identities. We also investigated panelists’ ideas on effective practitioner-researcher partnerships to inform the next stage of our project, where researchers and practitioners will jointly translate research from selected topics into practical guidance. We discuss our findings and the affordances and limitations of the Delphi method in knowledge mediation.

计算机支持的协作学习（CSCL）在提高学生的学习成果方面是有效的，但CSCL研究很少转化为课堂实践。为了确定K-12 STEM实践的关键CSCL研究主题，我们与一组从业人员和研究人员进行了改进的德尔菲法研究。我们依靠一个知识动员框架，从产生新知识的研究人员和将其与教学智慧结合起来并在课堂上使用的实践者中汲取专业知识。我们使用德尔菲法是因为它有可能解决小组成员之间的权力不平衡，并对其进行了修改，以促进知识生产和使用之间的知识中介。小组成员确定了从研究到实践翻译的七个关键CSCL主题：课堂话语；多样性、公平和包容；教师准备和专业发展；社会共享学习调节；论证;课堂编排和脚本；以及学生和教师的身份。我们还调查了小组成员关于有效的从业者-研究者伙伴关系的想法，以告知我们项目的下一阶段，研究人员和从业者将共同将选定主题的研究转化为实践指导。我们讨论了我们的发现和德尔菲方法在知识中介中的优点和局限性。

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引用次数: 0

“Teaching is basically feeling”: Unpacking EFL Teachers’ perceived emotions and regulatory strategies in AI-Powered L2 speaking and writing skills instruction “教学就是感觉”：解析英语教师在人工智能驱动的第二语言口语和写作技能教学中的感知情绪和调节策略

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-05-22 DOI: 10.1016/j.caeo.2025.100264

Haniye Seyri , Farhad Ghiasvand

The integration of Artificial Intelligence (AI) technologies into various aspects of second/foreign language (L2) education is recently gaining an unprecedented attention. However, teacher emotionality in light of using AI tools for teaching specific language skills has remained unaddressed, so far. To fill this void, the present qualitative study aimed to unveil English as a foreign language (EFL) teachers’ perceived AI-induced emotions and associated regulatory strategies used during their L2 speaking and writing instruction. A cohort of 21 Iranian EFL teachers were non-randomly picked up to attend a semi-structured interview and complete a written narrative frame. The results of thematic analysis through MAXQDA software divulged that the participants frequently experienced seven positive emotions including ‘excitement’, ‘confidence’, ‘joy’, ‘pride’, ‘satisfaction’, ‘passion’, and ‘engagement’. On the negative side, ‘anxiety’, ‘worry’, ‘stress’, ‘apprehension’, and ‘frustration’ were repeatedly induced by AI tools in L2 speaking and writing classes. Moreover, it was found that four ‘up-regulating’ and five ‘down-regulating’ strategies, either antecedent-focused or response-focused had been commonly employed by the teachers to manage their positive and negative AI-induced emotions. A discussion of the findings and practical implications for considering teacher emotionality when integrating AI technologies into L2 productive skills is provided.

最近，人工智能（AI）技术融入第二语言/外语（L2）教育的各个方面受到了前所未有的关注。然而，到目前为止，教师对使用人工智能工具教授特定语言技能的情绪仍未得到解决。为了填补这一空白，本定性研究旨在揭示英语作为外语（EFL）教师在他们的第二语言口语和写作教学中感知到的人工智能诱发的情绪和相关的调节策略。本研究非随机选取了21名伊朗英语教师进行半结构化访谈，并完成书面叙述框架。通过MAXQDA软件进行的主题分析结果显示，参与者经常体验七种积极情绪，包括“兴奋”、“自信”、“快乐”、“骄傲”、“满意”、“热情”和“投入”。在消极方面，人工智能工具在第二语言口语和写作课上反复引发“焦虑”、“担心”、“压力”、“忧虑”和“沮丧”。此外，我们还发现教师通常采用四种“上调”和五种“下调”策略来管理他们的积极和消极的人工智能诱发情绪，即以前事为中心或以反应为中心。本文讨论了将人工智能技术整合到第二语言生产技能时考虑教师情绪的研究结果和实际意义。

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引用次数: 0