Journal of Computer Assisted Learning最新文献_第7页

The Process of Undergraduates' Collaboration With a Generative Artificial Intelligence Chatbot: Insights From Conversation Content and Epistemic Network Analysis 大学生与生成式人工智能聊天机器人协作的过程：来自会话内容和认知网络分析的见解

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-16 DOI: 10.1111/jcal.70140

Weipeng Shen, Xiao-Fan Lin, Jiachun Liu, Xinxian Liang, Ruiqing Chen, Xiaoyun Lai, Xinwen Zheng

Background

Generative artificial intelligence (GenAI) chatbots extend transformative impact in higher education. Current research requires more comprehensive evaluations of the collaborative learning fostered by students and GenAI chatbots. However, existing articles have rarely explored the dynamic process of student–AI collaboration in higher education.

Objectives

This study aims to analyse and visualise the changes in the process of undergraduates' collaboration with a GenAI chatbot. The interaction patterns of the collaboration were explored under the perspective of social constructivist learning theory. The differences between student-AI interaction patterns at 5 time points (after 5 lessons) were further compared to show the dynamic collaboration process.

Method

A 9-week course was implemented for 40 Chinese undergraduates, who completed 5 rounds of collaboration with a GenAI chatbot named ERNIE Bot. Employing a designed coding scheme, a total of 6180 codes was collected from the conversation content of each round. Based on the interval data, content analysis and epistemic network analysis (ENA) were conducted.

Results

First, undergraduates gradually became more active and targeted in their collaboration with the GenAI chatbot. Second, the focal points of their collaboration changed from “Comprehension” (the first–third lessons) to “Generation” (the third–fifth lessons), along with different interaction patterns. Notably, the interaction patterns changed more rapidly and prominently during the “Comprehension” phase than the “Generation” phase.

Implications

The findings contribute to understanding the social constructivist learning process within student-AI collaboration in higher education. Practical recommendations for students and educators were offered as well.

生成式人工智能（GenAI）聊天机器人对高等教育产生了变革性影响。目前的研究需要对学生和GenAI聊天机器人培养的协作学习进行更全面的评估。然而，现有的文章很少探讨高等教育中学生与人工智能合作的动态过程。本研究旨在分析和可视化大学生与GenAI聊天机器人合作过程中的变化。在社会建构主义学习理论的视角下，探讨了合作的互动模式。进一步比较5个时间点（5节课后）学生与人工智能交互模式的差异，展示动态协作过程。方法对40名中国大学生进行为期9周的课程，与GenAI聊天机器人ERNIE Bot完成5轮合作。采用设计的编码方案，从每轮对话内容中共收集6180个编码。基于区间数据，进行了内容分析和认知网络分析（ENA）。首先，大学生在与GenAI聊天机器人的合作中逐渐变得更加活跃和有针对性。二是合作的重点从“理解”（第一节至第三节课）转变为“生成”（第三节至第五节课），互动模式也发生了变化。值得注意的是，交互模式在“理解”阶段比“生成”阶段变化得更快、更显著。研究结果有助于理解高等教育中学生与人工智能合作中的社会建构主义学习过程。报告还为学生和教育工作者提供了实用的建议。

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引用次数: 0

Concept Maps as a Content and Language Integrated Learning Facilitator in Digital Gaming Contexts: Triangulated Evidence From Students' Learning Achievements, Perceptions and Behavioural Patterns 概念地图在数字游戏环境中作为内容和语言整合学习促进者：来自学生学习成就、认知和行为模式的三角证据

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-13 DOI: 10.1111/jcal.70136

Shu-Fang Hsieh, Gwo-Jen Hwang

Background

While both Content and Language Integrated Learning (CLIL) and Digital Game-Based Learning (DGBL) are widely recognised as effective methods to enhance bilingual education, their combination often leads to cognitive overload and fragmented learning experiences. In Taiwan's bilingual education context, where integrating English into subject teaching is a national priority, finding effective instructional models remains a critical issue. To address this, the present study introduces the Concept Map-Facilitated Content and Language Integrated Digital Gaming (CM-CLDG) model, aiming to enhance bilingual science learning for elementary students by embedding concept mapping into a digital role-playing game.

Objective

Although DGBL has demonstrated potential to increase motivation and engagement, prior studies suggest that without structured guidance, learning outcomes may vary. The CM-CLDG model was designed to scaffold knowledge construction and reduce cognitive overload by integrating concept maps directly into the gaming tasks. This study aims to evaluate the effects of the CM-CLDG approach on students' English and science learning achievements, motivation, flow experience, anxiety and behavioural patterns.

Method

A quasi-experimental design was adopted with 78 sixth-grade students from an elementary school in central Taiwan. Participants were divided into the CM-CLDG group and the conventional CLIL gaming (C-CLDG) group. Pre- and posttests, questionnaires, behavioural log analyses and interviews were conducted to collect triangulated data. Learning behaviours were examined using sequential analysis via GSEQ.

Results and Conclusions

The CM-CLDG group significantly outperformed the C-CLDG group in both English and science achievements. Although no significant differences were found in motivation or anxiety, the C-CLDG group experienced greater flow. Behavioural analysis revealed that the CM-CLDG group exhibited more reflective, structured and strategic learning patterns. Interview findings supported these results, highlighting better memory retention and self-directed learning in the CM-CLDG group. These findings confirm that concept maps, when embedded in digital gameplay, can enhance bilingual learning outcomes and support more effective learning behaviours in CLIL-based educational games.

虽然内容和语言整合学习（CLIL）和数字游戏学习（DGBL）被广泛认为是加强双语教育的有效方法，但它们的结合往往会导致认知过载和学习体验的碎片化。在台湾的双语教育背景下，将英语融入学科教学是国家的优先事项，寻找有效的教学模式仍然是一个关键问题。为了解决这个问题，本研究引入了概念地图促进内容和语言集成数字游戏（CM-CLDG）模型，旨在通过将概念地图嵌入到数字角色扮演游戏中来促进小学生的双语科学学习。虽然DGBL已经证明有可能增加动机和参与，但先前的研究表明，如果没有结构化的指导，学习结果可能会有所不同。CM-CLDG模型旨在通过将概念图直接集成到游戏任务中来支撑知识构建并减少认知超载。本研究旨在评估CM-CLDG方法对学生英语和科学学习成绩、动机、心流体验、焦虑和行为模式的影响。方法采用准实验设计，对中部某小学78名六年级学生进行问卷调查。参与者被分为CM-CLDG组和常规CLIL游戏（C-CLDG）组。进行了前后测试、问卷调查、行为日志分析和访谈，以收集三角数据。学习行为通过GSEQ进行序列分析。结果与结论CM-CLDG组在英语和科学成绩上均明显优于C-CLDG组。虽然在动机或焦虑方面没有发现显著差异，但C-CLDG组经历了更大的心流。行为分析显示，CM-CLDG组表现出更多的反思、结构化和战略性学习模式。访谈结果支持了这些结果，强调CM-CLDG组有更好的记忆保持和自主学习。这些发现证实，当概念图嵌入到数字游戏中，可以提高双语学习成果，并支持基于cll的教育游戏中更有效的学习行为。

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引用次数: 0

Boosting Student Engagement in STEM: Integrating Large Language Model-Based Virtual Agents Into Alternate Reality Games 促进学生对STEM的参与：将基于大型语言模型的虚拟代理集成到替代现实游戏中

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-09 DOI: 10.1111/jcal.70139

Minkai Wang, Jingdong Zhu, Gwo-Jen Hwang, Shao-Chen Chang, Qi-Fan Yang, Di Zhang

Background

STEM education aims to develop innovation and problem-solving skills through interdisciplinary learning, yet struggles to foster student engagement and interdisciplinary thinking. Whilst alternate reality games (ARGs) can boost motivation via game-based problem-solving, integrating large language models (LLMs) remains underexplored. LLM-based virtual agents offer new opportunities for adaptive support.

Objectives

This study aimed to investigate the effectiveness of an LLM-assisted ARG system (LLM-ARG) in enhancing academic performance, metacognitive awareness, and engagement.

Methods

A quasi-experimental study compared LLM-ARG with conventional ARG methods amongst primary school students. The experimental group used LLM-ARG with personalised virtual agent support, whilst the control group employed a conventional ARG with a traditional, rule-based virtual agent that offered only pre-scripted feedback. Data were collected through pre- and post-tests, metacognitive awareness questionnaires, and interaction logs. ANCOVA and correlation analyses were conducted.

Results and Conclusions

LLM-ARG significantly improved learning achievements and metacognitive awareness compared to conventional ARG. High-frequency interactions promoted exploration but did not consistently enhance problem-solving, whilst low-frequency interactions led to higher success via goal-directed strategies. Metacognitive competence emerged as a key predictor of academic performance, highlighting the need to balance exploration with efficiency. This study demonstrates how LLM-driven scaffolding supports diverse learning strategies and promotes adaptive learning in STEM education.

STEM教育旨在通过跨学科学习培养创新和解决问题的能力，但努力培养学生的参与度和跨学科思维。虽然虚拟现实游戏（arg）可以通过基于游戏的问题解决机制来激发玩家的动机，但整合大型语言模型（llm）仍未得到充分探索。基于llm的虚拟代理为自适应支持提供了新的机会。本研究旨在探讨llm辅助ARG系统（LLM-ARG）在提高学业成绩、元认知意识和参与度方面的有效性。方法对小学生进行准实验研究，比较LLM-ARG和传统ARG方法。实验组使用带有个性化虚拟代理支持的LLM-ARG，而对照组使用带有传统的基于规则的虚拟代理的传统ARG，该虚拟代理只提供预先编写的反馈。通过前后测试、元认知意识问卷调查和互动日志收集数据。进行方差分析和相关分析。结果与结论与常规ARG相比，LLM-ARG显著提高了学习成绩和元认知意识。高频率的互动促进了探索，但并不能始终如一地提高解决问题的能力，而低频率的互动通过目标导向的策略导致了更高的成功。元认知能力成为学业成绩的关键预测指标，强调了在探索与效率之间取得平衡的必要性。本研究展示了llm驱动的脚手架如何支持多样化的学习策略，并促进STEM教育中的适应性学习。

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引用次数: 0

The Impact of a Digital Game on Spatial Reasoning for Elementary School Students 数字游戏对小学生空间推理能力的影响

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-09 DOI: 10.1111/jcal.70138

Di Liu, Linxuan Yi, Rui Kang

Background

Spatial reasoning is a crucial factor in students' mathematics performance. Providing training to elementary students in spatial reasoning is a promising way to improve their performance in mathematics. The use of digital games to assist instruction has been found to have a positive impact on students' spatial reasoning.

Objective

This study incorporates digital games into mathematics classrooms to investigate their effects on fourth graders' spatial reasoning.

Methods

The participants were randomly assigned to the experimental group or the control group, with the experimental group using a blended learning approach and the control group still receiving regular instruction. Before and after four sessions of intervention, both groups took a pretest and a posttest on object observation and mental rotation skills.

Results and Conclusions

The Analysis of Covariance (ANCOVA) results revealed that the experimental group showed significantly greater improvement in the two tasks compared to the control group, even after accounting for initial differences. Furthermore, the hierarchical linear regression results indicated that students' performance in the game was predictive of their performance in the object observation task.

Implications

Overall, the results of this study highlight the potential of digital game environments in developing spatial reasoning. The incorporation of digital games into educational practice can be an effective way to develop and improve students' spatial reasoning.

空间推理是影响学生数学成绩的重要因素。对小学生进行空间推理训练是提高其数学成绩的有效途径。使用数字游戏辅助教学已被发现对学生的空间推理有积极影响。目的探讨数字游戏对四年级学生空间推理能力的影响。方法将参与者随机分为实验组和对照组，实验组采用混合式学习方式，对照组仍接受常规教学。在四次干预之前和之后，两组都进行了物体观察和心理旋转技能的前测和后测。结果与结论协方差分析（ANCOVA）结果显示，即使在考虑初始差异后，实验组在两个任务上的改善程度也明显高于对照组。此外，层次线性回归结果表明，学生在游戏中的表现可以预测他们在物体观察任务中的表现。总的来说，这项研究的结果强调了数字游戏环境在发展空间推理方面的潜力。将数字游戏融入教育实践是培养和提高学生空间推理能力的有效途径。

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引用次数: 0

The Effectiveness of Technology-Supported Learning in Improving Students' Digital Literacy—A Meta-Analysis of 56 Experimental and Quasi-Experimental Studies 技术支持学习对提高学生数字素养的有效性——56项实验和准实验研究的元分析

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-09 DOI: 10.1111/jcal.70137

Jin Wang, Wenxiang Fan

Background

For students, digital literacy is an essential competency, and technology-supported learning has become one of the most crucial methods for developing students' digital literacy. However, no academic consensus exists regarding whether technology-supported learning is effective in improving students' digital literacy.

Objectives

This study conducts a meta-analysis to examine the effectiveness of technology-supported learning in improving students' digital literacy. In addition, the influence of moderator variables is tested. Examples of these variables include types of technology, ways of technology use, grade level, types of courses, learning environment, learning methods, duration and different digital literacy dimensions.

Methods

This meta-analysis follows the guidelines outlined in the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). For the 56 studies that met the specified criteria, a random effects model and Hedges' g are used to provide a comprehensive overview of the impact of technology-supported learning on students' digital literacy across different contexts. This study also uses a funnel plot, Begg's test and Egger's test to assess publication bias.

Results and Conclusions

The findings show that: (a) Technology-supported learning has a large positive impact on students' digital literacy (g = 0.612, p < 0.001). (b) Compared to GenAI, extended reality and digital platforms and applications are more effective in fostering digital literacy. (c) Compared to other ways of using technology, employing technology for digital creation and expression has the greatest effect in enhancing students' digital literacy. (d) Compared to other grade levels, technology-supported learning has the greatest effect in promoting kindergarten children's digital literacy. (e) Compared to other course types, technology-supported learning in interdisciplinary courses has the greatest effect in improving students’ digital literacy. (f) Compared to other contexts, technology-supported learning has the greatest effect in cultivating students’ digital literacy when implemented in a blended environment. (g) Compared to other learning methods, blended learning has the greatest effect in promoting students’ digital literacy when combined with technology-supported learning. (h) No significant difference exists in the impact of technology-supported learning on students’ digital literacy development across different intervention durations.

对学生来说，数字素养是一项基本能力，技术支持学习已成为培养学生数字素养的最重要方法之一。然而，关于技术支持的学习是否能有效提高学生的数字素养，学术界尚未达成共识。目的本研究通过荟萃分析来检验技术支持学习在提高学生数字素养方面的有效性。此外，还对调节变量的影响进行了检验。这些变量的例子包括技术类型、技术使用方式、年级水平、课程类型、学习环境、学习方法、持续时间和不同的数字素养维度。方法本荟萃分析遵循系统评价和荟萃分析首选报告项目（PRISMA）中概述的指南。对于符合指定标准的56项研究，使用随机效应模型和Hedges' g来全面概述不同背景下技术支持学习对学生数字素养的影响。本研究还使用漏斗图、Begg检验和Egger检验来评估发表偏倚。结果与结论研究结果表明：(a)技术支持学习对学生数字素养有显著的正向影响（g = 0.612, p < 0.001）。(b)与GenAI相比，扩展现实和数字平台及应用在培养数字素养方面更为有效。（三）与其他使用科技的方式相比，利用科技进行数码创作和表达，对提高学生的数码素养效果最大。（四）与其他年级相比，科技辅助学习对促进幼稚园儿童数码素养的效果最大。(e)与其他课程类型相比，跨学科课程中的技术支持学习对提高学生的数字素养效果最大。(f)与其他情况相比，在混合环境中实施的技术支持学习对培养学生的数字素养效果最大。(g)与其他学习方法相比，混合学习与技术支持学习相结合，对促进学生数字素养的效果最大。(h)技术支持学习对学生数字素养发展的影响在不同干预时间间无显著差异。这些发现为试图通过教育环境中的不同技术提高学生数字素养的教师和研究人员提供了有价值的见解。

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引用次数: 0

Demystifying School Leader Career Sustainability: The Role of Trust in Artificial Intelligence and Artificial Intelligence Collaboration 揭秘学校领导职业可持续发展：信任在人工智能和人工智能协作中的作用

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-09 DOI: 10.1111/jcal.70135

Masoumeh Kouhsari, Junjun Chen

Background

The increasing integration of artificial intelligence (AI) in education has highlighted the need for research on its role in fostering career sustainability among school leaders. Existing knowledge lacks a comprehensive understanding of how trust in AI relates to school leaders' performance and well-being amidst rapid technological changes. This study addresses this gap.

Objectives

This research aims to explore the relationship between trust in AI, AI collaboration and career sustainability among school leaders.

Methods

A sample of 553 school leaders from China participated in the study. Utilising multigroup structural equation modelling, the research analysed the associations among trust in AI, task performance, creative performance and well-being, with the mediating role of AI collaboration across different career stages.

Results and Conclusions

Findings suggest that trust in AI is positively related to task performance and well-being, particularly among novice and mid-career leaders. AI collaboration mediated the relationship between trust in AI and career sustainability across all career stages, highlighting the importance of fostering collaboration with AI in the educational setting in China to support school leaders' career sustainability.

人工智能（AI）在教育中的日益融合凸显了研究其在促进学校领导职业可持续发展方面的作用的必要性。在快速的技术变革中，对人工智能的信任与学校领导的表现和福祉之间的关系，现有的知识缺乏全面的理解。这项研究解决了这一差距。本研究旨在探讨学校领导对人工智能的信任、人工智能协作与职业可持续发展之间的关系。方法对全国553名学校领导进行问卷调查。利用多组结构方程模型，该研究分析了对人工智能的信任、任务绩效、创造性表现和幸福感之间的关系，以及人工智能协作在不同职业阶段的中介作用。结果和结论研究结果表明，对人工智能的信任与任务绩效和幸福感呈正相关，尤其是在新手和职业中期领导者中。人工智能协作调解了在所有职业阶段对人工智能的信任与职业可持续性之间的关系，强调了在中国教育环境中促进与人工智能合作以支持学校领导职业可持续性的重要性。

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引用次数: 0

Examining the Effectiveness of the Approach of Visual Metaphor Instructional Design for Management Education: A Multi-Aspect Theoretical View of Flow Experience and Perceived Task Value 检验视觉隐喻教学设计方法在管理教育中的有效性：流动体验与任务感知价值的多方位理论视角

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-09 DOI: 10.1111/jcal.70122

Ying-Lien Lin, Wei-Tsong Wang, Shih-Ying Kuang

Background

Visual metaphors (VMs) have gained significant attention from cognitive linguists for their ability to help learners understand linguistic structure. However, few studies have explored how incorporating a VM-supported instructional design can help instructors elucidate the abstract concepts of the business model canvas (BMC) to enhance student learning.

Objectives

This study aimed to investigate undergraduate students' learning of the BMC via the use of instructional videos that incorporate VM procedures, animations, texts and drawings.

Methods

This study applies flow theory to the development of the proposed research framework, and a quasi-experimental design was employed with 185 student participants. Data collected from the participants via a survey, as well as pretest and posttest were analysed via partial least squares.

Results and Conclusions

The results indicated that VM-supported instructional design significantly impacted students' self-efficacy, flow experience, perceived task value and perceived learning performance. However, those variables had no significant impact on actual learning performance (i.e., actual knowledge gain).

Implications

The implications for theory and practice are discussed to offer valuable suggestions to instructors and researchers regarding the application of VM-based tools/procedures to the teaching tasks of the BMC or other management-related learning subjects.

视觉隐喻因其帮助学习者理解语言结构的能力而受到认知语言学家的广泛关注。然而，很少有研究探讨整合虚拟机支持的教学设计如何帮助教师阐明业务模型画布（BMC）的抽象概念，以增强学生的学习。目的本研究旨在探讨大学生BMC的学习情况，包括教学视频、动画、文字和绘图。方法将心流理论应用于本研究框架的构建，采用准实验设计，共185名学生参与。通过调查以及前测和后测收集的参与者数据通过偏最小二乘法进行分析。结果与结论vm支持教学设计显著影响学生的自我效能感、心流体验、任务价值感知和学习绩效感知。然而，这些变量对实际学习绩效（即实际知识获得）没有显著影响。本文讨论了基于虚拟机的工具/程序在BMC或其他管理相关学习科目的教学任务中的应用对理论和实践的影响，为教师和研究人员提供有价值的建议。

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引用次数: 0

Effects of Fatigue Detection With Adaptive Feedback on Sustained Alertness and Learning Outcomes in Video-Based Learning 自适应反馈疲劳检测对视频学习中持续警觉性和学习效果的影响

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-10-09 DOI: 10.1111/jcal.70133

Zeng-Wei Hong, Che-Lun Liang, Ming-Chi Liu

Background

Online video-based learning often leads to fatigue, which detracts from engagement and learning outcomes. Previous studies have examined monitoring mental states like attention through electroencephalography (EEG) headsets, but limitations such as high costs, discomfort, and limited scalability persist.

Objectives

This study evaluates the effectiveness of facial recognition technology in detecting fatigue levels during video-based learning. By using eyelid closure (PERCLOS) and mouth opening percentage (POM) indicators, it aims to provide adaptive feedback that supports engagement and reduces fatigue. Key research questions address the impact on learning outcomes, feedback accuracy, and technology acceptance across different learner groups.

Methods

Three groups were established in an experimental design: an experimental group receiving fatigue-responsive feedback, a control group with random feedback, and a second control group with no feedback. Post-experiment assessments measured learning outcomes, feedback accuracy, and technology acceptance.

Results

Findings reveal that adaptive, fatigue-based feedback significantly enhances engagement and learning outcomes compared to random or no feedback. The experimental group maintained higher alertness in learning, reflected in both quantitative data and learner feedback.

Conclusions

Facial recognition technology offers a scalable and non-intrusive solution to address fatigue in video-based learning. Adaptive feedback based on real-time fatigue detection improves learners' sustained focus, suggesting practical applications for future online education initiatives. Further research is recommended to optimise feedback mechanisms and explore long-term impacts on learning efficacy.

基于视频的在线学习往往会导致疲劳，从而降低参与度和学习效果。之前的研究已经通过脑电图（EEG）耳机检测了注意力等精神状态，但成本高、不舒服、可扩展性有限等局限性仍然存在。目的本研究评估面部识别技术在视频学习过程中检测疲劳程度的有效性。通过使用眼睑闭合（PERCLOS）和张嘴百分比（POM）指标，旨在提供自适应反馈，支持参与并减少疲劳。关键的研究问题解决了不同学习者群体对学习成果、反馈准确性和技术接受程度的影响。方法采用随机反馈组、随机反馈组和无反馈组，按实验设计分为三组。实验后评估测量了学习成果、反馈准确性和技术接受度。研究结果显示，与随机或无反馈相比，适应性的、基于疲劳的反馈显著提高了参与度和学习效果。实验组在学习中保持了较高的警觉性，这体现在定量数据和学习者反馈两方面。面部识别技术为解决视频学习中的疲劳问题提供了一种可扩展且非侵入性的解决方案。基于实时疲劳检测的自适应反馈提高了学习者的持续注意力，为未来的在线教育计划提供了实际应用。建议进一步研究以优化反馈机制并探索对学习效能的长期影响。

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引用次数: 0

Playing With Emotions: Evaluating a Serious Game to Promote Parents' Emotional Competencies Within the Family Context 玩情绪：评估一个严肃的游戏，以提高父母在家庭环境中的情绪能力

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-09-23 DOI: 10.1111/jcal.70126

Maria Priego-Ojeda, Gemma Filella-Guiu, Núria Pérez-Escoda

Background

Video games can be innovative, educational and therapeutic tools that have demonstrated positive outcomes in enhancing emotional skills. Many of these programmes have shown benefits in improving children and adolescents' emotional competencies, but there is a lack of research evidence on programmes that aim to intervene within the family context, putting the focus directly on parents.

Objectives

The present study aimed to evaluate the efficacy of Happy for Families, a serious game developed to work on families' emotional competencies.

Methods

A total of 129 Spanish parents, aged 34–60 (83.7% women), were evaluated to explore pretest and posttest measures of the competencies of emotional awareness and regulation, cognitive emotion regulation strategies, parental stress and life satisfaction. Parents were divided into three groups: parents who played with their children (PC), parents who played alone (P) and a control group.

Results and Conclusions

The results evidenced that after the interaction with Happy for Families, the PC group reported increments in emotional awareness and regulation, as well as in the use of refocus on planning and positive reappraisal strategies compared to the P and the control group. No significant differences were found related to parental stress and satisfaction. Although future implementations of the video game would need to work on increasing the engagement of parents individually and not only in interaction with their children, these findings suggest that video games can be promising and easy-to-use tools to nurture parents' emotional competencies within the family setting.

电子游戏可以是创新的、教育的和治疗的工具，在提高情感技能方面已经证明了积极的结果。许多此类项目已显示出在改善儿童和青少年的情感能力方面的益处，但缺乏旨在在家庭背景下进行干预、将重点直接放在父母身上的项目的研究证据。本研究旨在评估《阖家欢乐》（Happy for Families）这款旨在培养家庭情感能力的严肃游戏的有效性。方法对129名34 ~ 60岁的西班牙父母（83.7%为女性）进行情绪意识和调节能力、认知情绪调节策略、父母压力和生活满意度的测前和测后测量。家长们被分成三组：和孩子一起玩的家长（PC），单独玩的家长(P)和对照组。结果与结论结果证明，与P组和对照组相比，PC组在与《家庭快乐》互动后，情绪意识和调节，以及重新关注计划和积极重新评估策略的使用方面都有所增加。父母压力与满意度无显著差异。尽管电子游戏的未来实施需要提高父母个人的参与度，而不仅仅是与孩子的互动，但这些发现表明，电子游戏可以成为培养父母在家庭环境中情感能力的有前途且易于使用的工具。

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引用次数: 0

Digital Competencies for Effective GenAI Use in Secondary Schools: A Longitudinal Exploration of Teachers' Perspectives and Classroom Practices 在中学有效使用GenAI的数字能力：教师观点和课堂实践的纵向探索

IF 4.6 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2025-09-23 DOI: 10.1111/jcal.70123

Liron Levy-Nadav, Tamar Shamir-Inbal, Ina Blau

Background

The rapid rise of Generative Artificial Intelligence (GenAI) is transforming education. At this stage, there is not yet a well-established and tested theoretical framework clarifying which competencies learners must possess to use GenAI effectively and safely. This study draws on three theoretical frameworks: Eshet-Alkalai's Digital Literacy Framework (2012), Long and Magerko's AI Literacy (2020) and DigComp 2.2.

Objectives

The study aims to explore teachers' perspectives regarding the digital competencies that students need for effective GenAI tool use, as well as the classroom learning activities that facilitate the development and practice of these competencies and how they evolve over time.

Methods

We conducted 34 semi-structured interviews at an interval of 6–8 months with 17 teachers who had begun utilising a variety of GenAI tools for teaching purposes. This mixed-methods study combines qualitative top-down and bottom-up thematic analysis with quantitative comparisons between the pre and post measurements. Additionally, for data triangulation, a large qualitative sample of 97 GenAI-enhanced learning activities conducted in classrooms was analysed.

Results and Conclusions

Findings revealed seven key competencies categorised into general digital literacies, emerging technology literacies and GenAI-specific competencies. Three categories of classroom activities that practiced these competencies emerged: proper use of tools, fostering personal expression and encouraging critical discussion. As expected in the beginning of new technology integration, declines were observed in most competencies in both interviews and learning activities, except for a significant increase in critical-thinking competencies and stable levels of managing-ongoing dialogue. The findings suggest expanding the digital literacy framework by incorporating ‘Learning New Technology’, which covers general competencies for integrating emerging technologies, and specific GenAI-related competencies. The study offers valuable insights into theory and practice AI-enhanced learning.

生成式人工智能（GenAI）的迅速兴起正在改变教育。在这个阶段，还没有一个完善的和经过测试的理论框架来阐明学习者必须具备哪些能力才能有效和安全地使用GenAI。本研究借鉴了三个理论框架：eset - alkai的《数字扫盲框架》（2012年）、Long和Magerko的《人工智能扫盲》（2020年）和DigComp 2.2。本研究旨在探讨教师对学生有效使用GenAI工具所需的数字能力的看法，以及促进这些能力发展和实践的课堂学习活动，以及它们如何随着时间的推移而演变。方法我们对17名教师进行了34次半结构化访谈，访谈间隔为6-8个月，这些教师已经开始使用各种GenAI工具进行教学。这项混合方法的研究结合了定性的自上而下和自下而上的专题分析以及前后测量之间的定量比较。此外，为了进行数据三角测量，分析了在教室中进行的97次genai增强学习活动的大量定性样本。结果和结论调查结果揭示了七大关键能力，分为一般数字素养、新兴技术素养和基因人工智能特定能力。实践这些能力的三类课堂活动出现了：正确使用工具，培养个人表达和鼓励批判性讨论。正如在新技术整合开始时所预期的那样，在面试和学习活动中，除了批判性思维能力和管理持续对话的稳定水平显著提高外，大多数能力都有所下降。研究结果建议通过纳入“学习新技术”来扩大数字扫盲框架，该框架涵盖了整合新兴技术的一般能力以及与genai相关的具体能力。该研究为人工智能增强学习的理论和实践提供了宝贵的见解。

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引用次数: 0

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