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Exploring STEM educators’ perspectives on the integration of AI-enabled technologies in teaching and learning 探讨STEM教育工作者对人工智能技术在教学和学习中的整合的观点

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-10-24 DOI: 10.1016/j.caeo.2025.100304

Hulya Avci , Stephanie J. Lunn , Zahra Hazari

The innovation and proliferation of artificial intelligence (AI) technologies are transforming Science, Technology, Engineering, and Mathematics (STEM) disciplines and pedagogical practices, making it essential to prepare educators for this evolving landscape. This qualitative study explores STEM educators’ perceptions of how they developed proficiency with AI-enabled technologies, what motivated their adoption, and the challenges they faced in classroom integration. Using a cross-sectional survey design, we collected open-ended responses from 27 in-service secondary STEM educators in the United States and analyzed the data through the reflexive thematic analysis. Our findings revealed that STEM educators recognized AI as a cognitive scaffold that can support student understanding of complex content and a socio-affective tool that can help enhance teacher–student relationships. The participants highlighted that by streamlining routine tasks, AI allowed them to reclaim time for meaningful student interactions and responsive instruction. The participants also reported developing their AI proficiency through self-directed learning, peer support, and professional networks, driven by motivations to enhance instructional efficiency, support personalized learning, and prepare students for AI-driven futures. However, the participants emphasized several significant challenges, including lack of institutional support, the overwhelming abundance of AI tools, concerns about affordability, and students’ growing overreliance on AI systems. These insights highlight the need for structured, discipline-specific professional development for in-service educators to promote effective and human-centered integration of AI in STEM education. This study contributes to a growing body of research by centering STEM educators’ perspectives and offering novel insights into how to support their effective integration of AI technologies into STEM teaching and learning.

人工智能（AI）技术的创新和扩散正在改变科学、技术、工程和数学（STEM）学科和教学实践，因此教育工作者必须为这一不断变化的环境做好准备。这项定性研究探讨了STEM教育工作者对他们如何熟练使用人工智能技术的看法，他们采用人工智能技术的动机，以及他们在课堂整合中面临的挑战。采用横断面调查设计，我们收集了美国27名在职中学STEM教育工作者的开放式回答，并通过反身性主题分析对数据进行了分析。我们的研究结果表明，STEM教育工作者认为人工智能是一种认知支架，可以帮助学生理解复杂的内容，也是一种社会情感工具，可以帮助加强师生关系。参与者强调，通过简化日常任务，人工智能使他们能够腾出时间进行有意义的学生互动和响应式教学。参与者还报告说，他们通过自主学习、同伴支持和专业网络来提高人工智能水平，其动机是提高教学效率，支持个性化学习，并为学生为人工智能驱动的未来做好准备。然而，与会者强调了几个重大挑战，包括缺乏机构支持、人工智能工具的压倒性丰富、对负担能力的担忧以及学生对人工智能系统的日益过度依赖。这些见解强调了在职教育工作者需要结构化的、特定学科的专业发展，以促进人工智能在STEM教育中的有效和以人为本的整合。本研究通过集中STEM教育工作者的观点，并就如何支持他们有效地将人工智能技术整合到STEM教学和学习中提供新颖的见解，为越来越多的研究做出了贡献。

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引用次数: 0

Assessment of captions’ quality by students of a MOOC on accessibility of digital materials MOOC学生对数字材料可及性的字幕质量评估

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.2025.100279

J. Pérez-Arteaga , E. Letón , J. Pérez-Martín , E.M. Molanes-López , A. Rodriguez-Ascaso

Captions constitute one of the fundamental components of audiovisual accessibility. Ensuring that captions comply with applicable accessibility standards is an important and complex task that requires dedication and specific knowledge. It goes beyond checking whether or not the video has captions. This work aims to evaluate whether students can adequately assess the quality of captions for the deaf or hard of hearing. It analyses data from an activity of a MOOC on accessibility of digital materials, in which they assessed the quality of captions. It was a voluntary task within the course delivered through an Open edX platform. At the time of enrollment, the students were randomly divided into two groups (AB and BA) so that the cohort AB watched the well-captioned video first and then the poorly-captioned video (with identified errors only in relation to 11 requirements of the UNE 153010:2012 standard), and the cohort BA watched them the other way round. After watching each of the videos, 87 students responded to a survey of 18 items with a 5-point Likert scale. The experimental design was a randomized, triple-blind, crossover AB/BA study. The data were analyzed using a multilevel multiple ordinal regression model. The main conclusions are: (1) basic training on accessibility of multimedia learning materials enables students to perform a preliminary assessment of the accessibility of captions; (2) qualitative guidelines present fewer problems than quantitative ones when identifying accessibility problems; (3) novice evaluators tend to underscore some of the items in non-accessible captions, compared to accessible captions.

字幕是视听无障碍的基本组成部分之一。确保标题符合适用的可访问性标准是一项重要而复杂的任务，需要奉献精神和特定的知识。它不仅仅是检查视频是否有字幕。这项工作旨在评估学生是否能够充分评估聋人或重听人的字幕质量。它分析了一项关于数字材料可访问性的MOOC活动的数据，在该活动中，他们评估了标题的质量。这是通过开放式edX平台提供的课程中的自愿任务。在入学时，学生被随机分为AB组和BA组，AB组先观看字幕较好的视频，然后观看字幕较差的视频（仅在UNE 153010:2012标准的11项要求中发现错误），BA组观看字幕较差的视频。在观看完每个视频后，87名学生对一项包含18个项目的5分李克特量表进行了回答。实验设计为随机、三盲、交叉AB/BA研究。采用多水平多元有序回归模型对数据进行分析。主要结论如下：(1)多媒体学习材料可及性基础训练使学生对字幕可及性进行初步评价；(2)定性指南在识别可达性问题时存在的问题少于定量指南；(3)与无障碍标题相比，新手评价者倾向于强调非无障碍标题中的某些项目。

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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 : 2025-12-01 Epub 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

The impact of generative AI on essay revisions and student engagement 生成式人工智能对论文修改和学生参与的影响

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-03-29 DOI: 10.1016/j.caeo.2025.100249

Noble Lo , Alan Wong , Sumie Chan

This study investigates the effect of AI-generated feedback on university students’ essay writing proficiency in Hong Kong. By integrating generative AI into the revision process, the research examines how automated feedback influences the quality of students’ written work, as well as their engagement, motivation, and emotional responses during revision. The study employs a randomized controlled design, comparing students who received AI feedback on their essays with those who did not. Both quantitative and qualitative data were collected to assess the impact of AI feedback on writing improvement and student experiences. Quantitative analysis shows significant improvements in essay quality for students who utilized AI feedback, while qualitative findings highlight increased engagement and motivation, though students exhibited mixed emotional responses to the revision process. The results suggest that generative AI has considerable potential to enhance writing skills in higher education by providing timely, individualized feedback. This research contributes to ongoing discussions on the role of AI in education, particularly in supporting language instruction and student development.

本研究旨在探讨人工智能对香港大学生论文写作能力的影响。通过将生成式人工智能集成到复习过程中，该研究考察了自动化反馈如何影响学生书面作业的质量，以及他们在复习过程中的参与度、动机和情绪反应。这项研究采用了随机对照设计，将论文收到人工智能反馈的学生与没有收到反馈的学生进行比较。收集了定量和定性数据，以评估人工智能反馈对写作改进和学生体验的影响。定量分析显示，使用人工智能反馈的学生在论文质量上有了显著提高，而定性研究结果强调了参与度和积极性的提高，尽管学生对修改过程表现出不同的情绪反应。研究结果表明，生成式人工智能通过提供及时、个性化的反馈，在提高高等教育学生的写作技能方面具有相当大的潜力。这项研究有助于正在进行的关于人工智能在教育中的作用的讨论，特别是在支持语言教学和学生发展方面。

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引用次数: 0

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 : 2025-12-01 Epub 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

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 : 2025-12-01 Epub 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

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 : 2025-12-01 Epub 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

User perception and anatomical understanding from use of 3D anatomy technology by exercise science students: A pilot study 运动科学学生使用3D解剖技术的用户感知和解剖理解：一项试点研究

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-10-01 DOI: 10.1016/j.caeo.2025.100295

Leesa Anne Grier , Anthony Leicht

Understanding anatomy poses a significant challenge for non-medical university students, particularly those without prior science knowledge, such as exercise science students. Technology-Enhanced Learning (TEL) resources, including 3D anatomy platforms, have been explored to support student engagement and improve academic outcomes with variable results.

Objectives: This pilot study investigated the potential of the Complete Anatomy (CA) 3DTEL resource, combined with traditional blended learning methods, to enhance anatomy knowledge of first-year, undergraduate exercise science students.

Design: Cohort observational study.

Methods: The study followed 36 participants (46 % female, 54 % male) across two 13-week units. Guided implementation of CA was introduced during unit 1, while students engaged with the resource independently during unit 2. User satisfaction was assessed via surveys, and academic performance evaluated by comparing final unit grades with a 2022 cohort that did not use the resource.

Results: Results indicated stable student satisfaction and a significantly different academic performance for the 2023 cohort, with median grades increasing from a Pass (50.0–64.9 %) to a Credit (65.0–74.9 %).

Conclusion: These findings suggest that integrating 3DTEL resources with blended learning can positively support anatomy learning for science-naïve students.

理解解剖学对非医科大学的学生来说是一个巨大的挑战，特别是那些没有科学知识的学生，比如运动科学的学生。包括3D解剖平台在内的技术增强学习（TEL）资源已被探索，以支持学生的参与，并以不同的结果改善学术成果。目的：本初步研究探讨了完整解剖学（CA） 3DTEL资源与传统混合式学习方法相结合的潜力，以提高运动科学本科一年级学生的解剖学知识。设计：队列观察研究。方法：该研究对36名参与者（46%女性，54%男性）进行了为期13周的随访。第一单元引入了CA的指导实施，而学生在第二单元独立使用资源。通过调查来评估用户满意度，通过将最终单元成绩与未使用该资源的2022年队列进行比较来评估学习成绩。结果：结果表明，2023年的学生满意度稳定，学习成绩显著不同，成绩中位数从及格（50.0% - 64.9%）增加到学分（65.0% - 74.9%）。结论：将3DTEL资源与混合学习相结合，对science-naïve学生的解剖学学习具有积极的支持作用。

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引用次数: 0

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 : 2025-12-01 Epub 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

Social media discussions on educators: Selecting and appraisal of recent research using TF-IDF 社会媒体对教育者的讨论：使用TF-IDF选择和评价最近的研究

IF 5.7 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Education Open

Pub Date : 2025-12-01 Epub Date: 2025-09-30 DOI: 10.1016/j.caeo.2025.100293

Mateo R. Borbon Jr. , Ryan A. Ebardo

This systematic literature review, analyzing 36 peer-reviewed publications from 2019 to February of 2025, addresses a critical gap by examining the use of social media analytics (SMA) for faculty evaluation. Employing a novel methodological approach that combines machine learning-assisted screening (ASReview) with TF-IDF, the study finds that platforms like Twitter and Facebook are increasingly analyzed using sentiment analysis, machine learning, and text mining. These techniques provide real-time, unfiltered student feedback on teaching effectiveness, complementing traditional evaluation instruments and helping to monitor institutional reputation. While SMA offers valuable insights, the review highlights significant challenges, including data quality and credibility, algorithmic bias, ethical concerns, and generalizability. Effectively leveraging SMA's potential requires addressing these issues through robust theoretical frameworks, balanced institutional policies, and enhanced digital literacy to improve teaching practices while safeguarding academic integrity.

这篇系统的文献综述分析了2019年至2025年2月的36篇同行评审的出版物，通过研究社交媒体分析（SMA）在教师评估中的使用，解决了一个关键的差距。该研究采用了一种将机器学习辅助筛选（ASReview）与TF-IDF相结合的新方法，发现Twitter和Facebook等平台越来越多地使用情感分析、机器学习和文本挖掘进行分析。这些技术提供了实时的、未经过滤的学生对教学效果的反馈，补充了传统的评估工具，并有助于监测机构的声誉。虽然SMA提供了有价值的见解，但该综述强调了重大挑战，包括数据质量和可信度、算法偏见、伦理问题和可泛化性。有效利用SMA的潜力需要通过健全的理论框架、平衡的制度政策和增强数字素养来解决这些问题，以改善教学实践，同时维护学术诚信。

引用次数: 0