Computers & Education最新文献_第8页

Effects of a human-robot collaborative teaching approach on preschoolers’ social-emotional competence and learning behaviors 人机协作教学方式对学龄前儿童社交情绪能力和学习行为的影响

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-30 DOI: 10.1016/j.compedu.2025.105469

Jian-Wen Fang , Ting-Ting Ji , Yun-Fang Tu , Gwo-Jen Hwang , Di Zou , Jing Chen

Preschoolers' social-emotional competence is key to their long-term academic success. Developing this competence requires meaningful social interactions and emotional support, which the conventional teaching (CT) approach may not fully provide. This study proposed a human-robot collaborative teaching (HRCT) approach to facilitate preschoolers' social-emotional learning (SEL). A human-robot collaborative teaching system was developed to foster preschoolers' social-emotional competence through collaboration between the humanoid intelligent robot and the teacher. To evaluate the effectiveness of this approach, 96 preschoolers with an average age of 4.6 years were recruited. Of these, 44 were randomly assigned to the experimental group, which utilized the HRCT approach, while 52 were assigned to the control group, which followed the conventional teaching approach. The results indicated that the experimental group outperformed the control group in terms of social interaction skills, emotion comprehension skills, and interpersonal problem-solving skills. Significant differences were also observed in the learning behaviors of preschoolers during activities related to social interaction, emotion comprehension, and interpersonal problem solving. Further analysis of the teacher's perceptions and reflections revealed that, despite some limitations of the robot, its anthropomorphic and embodied features effectively sparked preschoolers' interest and engagement. These features contributed to enhancing their social-emotional competence by simulating and practicing SEL processes.

学龄前儿童的社会情感能力是他们长期学业成功的关键。培养这种能力需要有意义的社会互动和情感支持，而传统的教学方法可能无法完全提供这些。本研究提出了一种促进幼儿社会情绪学习的人机协作教学方法。设计了一种人-机器人协作教学系统，通过类人智能机器人与教师的协作，培养幼儿的社交情感能力。为了评估这种方法的有效性，我们招募了96名平均年龄为4.6岁的学龄前儿童。其中，实验组44人，采用HRCT教学方法；对照组52人，采用常规教学方法。结果表明，实验组在社交能力、情绪理解能力和人际问题解决能力方面均优于对照组。学龄前儿童在社会交往、情绪理解和人际问题解决方面的学习行为也存在显著差异。进一步分析老师的感知和反思，发现尽管机器人有一些局限性，但它的拟人化和具体化的特征有效地激发了学龄前儿童的兴趣和参与。这些特征有助于通过模拟和实践SEL过程来提高他们的社会情感能力。

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引用次数: 0

Evaluating educational technology: Consolidating across multiple impact indicators and rating systems 评估教育技术：跨多个影响指标和评级系统的整合

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-29 DOI: 10.1016/j.compedu.2025.105467

Natalia Kucirkova , Per Henning Uppstad , Richard Holeton , Dan Lin , Alison Clark-Wilson , Antonie Chigeda

Procurement of educational technologies (EdTech) requires a research-based rubric with multiple quality indicators that reflect the technology’s impact across various settings. We outline the development of the Multiple EdTech Impact Index (MEII) and an impact benchmarking formula for EdTech tools designed for K12 education. MEII includes fifteen indicators of impact, categorized into three evidence weights (high, medium, low) across five domains: efficacy, effectiveness, ethics, equity, and environment. It calculates a total EdTech impact score, highlighting the strength and relevance of products. MEII integrates evaluations based on diverse national EdTech certification standards and proposes a unified approach for assessment. We demonstrate its value through two models: national EdTech certification systems and a comparative database ranking EdTech tools by impact weight.

教育技术的采购（EdTech）需要一个以研究为基础的标准，其中包含多个质量指标，以反映技术在各种环境中的影响。我们概述了多重教育技术影响指数（MEII）的发展以及为K12教育设计的教育技术工具的影响基准公式。MEII包括15个影响指标，分为三个证据权重（高、中、低），跨越五个领域：疗效、有效性、伦理、公平和环境。它计算EdTech影响总分，突出产品的实力和相关性。综合不同国家教育技术认证标准的评估，提出统一的评估方法。我们通过两个模型来证明它的价值：国家教育技术认证系统和根据影响权重对教育技术工具进行排名的比较数据库。

引用次数: 0

Using eye tracking to explore differences and influencing factors of map reading ability in different problem situation among high school students 运用眼动追踪法探讨高中生在不同问题情境下地图阅读能力的差异及影响因素

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-26 DOI: 10.1016/j.compedu.2025.105466

Xinxin Li , Ping Li , Huiming You , Qiuwen Zhou , Ling Zhao , Yan Huang , Ya Luo

This study uses eye tracking to explore the differences in map-reading ability among high school students in the context of subject knowledge and real-life application. Unlike existing literature, which primarily emphasizes outcome-based assessments, this study integrates process- and outcome-based indicators to quantitatively evaluate high school students' map-reading abilities across different problem situations. Additionally, it comprehensively analyzes the internal and external factors influencing students' map-reading abilities and constructs a conceptual framework to illustrate the pathway through which these factors contribute to differences in performance among the students. The results reveal that in real-life scenarios, students exhibited longer reaction times, engaged in more extensive visual searches, processed information in a complex manner, and achieved low accuracy rates. However, despite these limitations, their cognitive load did not increase significantly. Furthermore, several limitations were highlighted in traditional geography education, particularly in fostering students' spatial reasoning and practical application skills. These findings contribute to the existing research on map-reading abilities, providing a new theoretical foundation and empirical support for advancements in geography education. Moreover, they can help educators better enhance students’ map-reading ability to meet diverse and complex practical needs.

本研究采用眼动追踪的方法，探讨了在学科知识背景和现实应用背景下高中生地图阅读能力的差异。与现有文献主要强调基于结果的评估不同，本研究整合了基于过程和结果的指标来定量评估高中学生在不同问题情境下的地图阅读能力。此外，本文还综合分析了影响学生地图阅读能力的内外部因素，并构建了一个概念框架来说明这些因素导致学生之间表现差异的途径。结果表明，在现实场景中，学生表现出更长的反应时间，参与更广泛的视觉搜索，以复杂的方式处理信息，并且准确率较低。然而，尽管有这些限制，他们的认知负荷并没有显著增加。此外，传统地理教育在培养学生的空间推理能力和实际应用能力方面也存在一定的局限性。这些研究结果对现有的地图阅读能力研究有一定的借鉴作用，为提高地理教育水平提供了新的理论基础和实证支持。此外，它们可以帮助教育者更好地提高学生的地图阅读能力，以满足多样化和复杂的实际需求。

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引用次数: 0

A systematic literature review on designing self-regulated learning using generative artificial intelligence and its future research directions 系统综述了利用生成式人工智能设计自我调节学习的相关文献及未来研究方向

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-22 DOI: 10.1016/j.compedu.2025.105465

Qi Xia , Qian Liu , Ahmed Tlili , Thomas K.F. Chiu

A growing body of research suggests that generative AI (GenAI) can significantly enhance self-regulated learning (SRL) through its immediacy and interactivity. Nevertheless, challenges remain, including the lack of clarity regarding the mechanisms by which generative AI influences SRL, as well as the difficulties teachers encounter when trying to incorporate it into their classrooms. This systematic review study investigates how to design SRL activities using GenAI. We examined 73 articles published over the past five years, drawn from four databases: Web of Science, ProQuest, ERIC, and Scopus. This study has three major empirical findings. First, six pedagogical affordances from GenAI across the three phases of SRL—forethought, Performance, and self-reflection—are (i) creating personalized learning objectives; (ii) searching for, analyzing, and integrating resources; (iii) monitoring and evaluating progress; (iv) recommending learning strategies; (v) recording progress and providing feedback; and (vi) generating new ideas and examples. Second, popular student learning activities using GenAI in each phase are information searching in the forethought; strategies for problem-solving in the performance, and obtaining feedback and conducting self-assessments in the self-reflection. Third, two major dimensions influencing student engagement in SRL using GenAI are individual and environmental. Finally, we visualize how the three empirical findings relate to each other. Our findings help us understand how AI as a human-machine collaborative tool affects the SRL process. This study provides practical recommendations for facilitating SRL in GenAI-enhanced environments and offers guidance for the design and development of personalized GenAI learning tools.

越来越多的研究表明，生成式人工智能（GenAI）可以通过其即时性和交互性显著增强自我调节学习（SRL）。然而，挑战仍然存在，包括生成人工智能影响SRL的机制缺乏明确性，以及教师在试图将其纳入课堂时遇到的困难。本系统综述研究探讨了如何使用GenAI设计SRL活动。我们从Web of Science、ProQuest、ERIC和Scopus这四个数据库中选取了过去五年发表的73篇文章。本研究有三个主要的实证发现。首先，GenAI在srl的三个阶段（预见、表现和自我反思）中的六个教学启示是：(1)创建个性化的学习目标；（二）资源查找、分析、整合；监测和评价进展情况；（四）推荐学习策略；(v)记录进度并提供反馈；（六）产生新的想法和例子。第二，GenAI在各个阶段的流行的学生学习活动是预先的信息搜索；在绩效中解决问题的策略，在自我反思中获得反馈并进行自我评估。第三，影响学生在使用GenAI的SRL中投入的两个主要维度是个人和环境。最后，我们可视化三个实证结果如何相互关联。我们的发现有助于我们理解人工智能作为人机协作工具如何影响SRL过程。本研究为促进GenAI增强环境下的SRL提供了实用建议，并为个性化GenAI学习工具的设计和开发提供了指导。

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引用次数: 0

Developing an AI learning companion for mathematics problem solving in elementary schools 开发用于小学数学问题解决的人工智能学习伙伴

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-21 DOI: 10.1016/j.compedu.2025.105463

Bor-Chen Kuo, Zong-En Bai, Chia-Hua Lin

This study examined the impact of integrating the Taiwan Adaptive Learning Platform (TALP) with generative AI-based learning companion (TALPers) on fifth-grade students' mathematics learning performance. The integration was applied to both self-learning and remedial instruction, with both contexts incorporating Socratic dialogue and Pólya's problem-solving strategy. Results showed that video-based self-learning with TALPer support yielded the highest learning gains. In the remedial setting, students receiving TALPer support also demonstrated significantly better performance. Both approaches were particularly effective for low-achieving students. Lag Sequential Analysis (LSA) further revealed that high-achieving students engaged in more complex interaction patterns with TALPers, sustaining feedback cycles, whereas low-achieving students exhibited simpler interaction patterns. These findings provide empirical support for implementing AI-augmented learning systems in mathematics education and suggest that structured AI support can promote differentiated instruction and student engagement to help bridge achievement gaps.

本研究探讨台湾自适应学习平台（TALP）与生成式人工智能学习伙伴（TALPers）整合对五年级学生数学学习绩效的影响。整合应用于自学和补救教学，两种情况下都结合了苏格拉底对话和Pólya的问题解决策略。结果表明，在TALPer支持下，基于视频的自学取得了最高的学习效果。在补救设置中，接受TALPer支持的学生也表现出明显更好的表现。这两种方法对成绩差的学生都特别有效。滞后序列分析（LSA）进一步揭示了学习成绩高的学生与TALPers的互动模式更复杂，持续反馈循环，而学习成绩低的学生表现出更简单的互动模式。这些发现为在数学教育中实施人工智能增强学习系统提供了实证支持，并表明结构化的人工智能支持可以促进差异化教学和学生参与，从而帮助弥合成绩差距。

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引用次数: 0

Learner autonomy and mode selection in dual-mode chatbot: Students' interaction patterns and learning outcomes in an online course 双模式聊天机器人中的学习者自主与模式选择：在线课程中学生的互动模式与学习效果

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-19 DOI: 10.1016/j.compedu.2025.105464

Songhee Han (한송희)

While educational chatbots are increasingly used in online courses, most research has focused on single-mode chatbots, with little attention to how students engage with multi-mode chatbots. Limited empirical studies have examined how students exercise autonomy when choosing between a general large language model (LLM)-based mode and a reference-based mode powered by retrieval-augmented generation (RAG). This study examines how students in a large-scale online course engaged with a dual-mode chatbot that allowed them to choose between general (LLM-based) and reference-based modes (LLM-RAG). Grounded in a conceptual framework linking learner autonomy, user factors, and learning outcomes, the study employed a mixed-methods explanatory sequential design using chatbot interaction logs, learning management system logs, server data, and survey responses. Findings showed that 41.3 % of the participants were unaware of or indifferent to using the mode selection feature despite each interaction beginning with a system-generated message explaining each mode's functionality. Among those aware, general mode users prioritized convenience and open-ended use, while reference-based mode users emphasized course-aligned assistance and demonstrated greater hyperlink engagement. Hyperlink use was positively correlated with social presence, teaching and cognitive presence, self-regulation, and perceived ease of use. Course completion showed a modest positive correlation with perceived ease of use but not with other variables. Interaction behaviors differed between the two chatbot modes, with exploratory and socio-emotional talk more prevalent in the general mode, and course-related sentence questions dominating the reference-based mode. These findings highlight the need for intentional design that fosters learner autonomy and aligns chatbot functionality with instructional goals.

虽然教育聊天机器人越来越多地用于在线课程，但大多数研究都集中在单模聊天机器人上，很少关注学生如何与多模聊天机器人互动。有限的实证研究考察了学生在基于一般大型语言模型（LLM）的模式和基于检索增强生成（RAG）的基于参考的模式之间进行选择时如何行使自主权。本研究考察了大型在线课程中的学生如何使用双模式聊天机器人，该聊天机器人允许他们在通用（基于llm的）和基于参考的模式（LLM-RAG）之间进行选择。在连接学习者自主、用户因素和学习成果的概念框架的基础上，该研究采用了混合方法的解释顺序设计，使用了聊天机器人交互日志、学习管理系统日志、服务器数据和调查反馈。调查结果显示，41.3%的参与者不知道或对使用模式选择功能漠不关心，尽管每次交互都以系统生成的消息开始，解释每种模式的功能。在这些意识到的用户中，一般模式用户优先考虑便利性和开放式使用，而基于参考的模式用户强调课程一致的帮助，并表现出更高的超链接参与度。超链接使用与社交在场、教学和认知在场、自我调节和感知易用性呈正相关。课程完成程度与感知易用性呈适度正相关，但与其他变量无关。两种聊天机器人模式之间的交互行为存在差异，一般模式中探索性和社会情感对话更为普遍，而基于参考的模式中与课程相关的句子问题占主导地位。这些发现强调了有意设计的必要性，以促进学习者的自主性，并使聊天机器人的功能与教学目标保持一致。

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引用次数: 0

Can virtual reality improve social-emotional learning among adolescents? An experimental study 虚拟现实能改善青少年的社交情感学习吗？实验研究

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-16 DOI: 10.1016/j.compedu.2025.105462

Qinna Feng , Gege Li , Yanbei Chen , Feng Zhang , Wenhao Li , Heng Luo

The potential of virtual reality (VR) to support social-emotional learning (SEL) has been widely acknowledged, but design precedents for VR-based SEL interventions are still lacking in the literature. The effectiveness of such interventions also remains uncertain due to insufficient empirical evidence. To bridge this research gap, the present study adopted a between-subjects design to explore the impact of a VR-based intervention on enhancing SEL and learning experience. A total of 297 seventh-grade students in China were randomly assigned to one of three conditions: VR (n = 101), face-to-face (n = 107), and control (n = 89). Participants in both the VR and face-to-face conditions engaged in collaborative tasks designed to promote SEL, while the control condition received no such intervention. The findings revealed significant improvement in overall social-emotional competencies in the VR condition, especially in the subscales of task performance, collaboration, and engagement with others. The VR intervention also promoted a stronger sense of group cohesion and enriched social experiences. These findings offer practical implications for the design and implementation of VR-based SEL interventions in formal education settings.

虚拟现实（VR）支持社交情绪学习（SEL）的潜力已得到广泛认可，但文献中仍缺乏基于VR的SEL干预的设计先例。由于经验证据不足，这些干预措施的有效性仍然不确定。为了弥补这一研究空白，本研究采用被试设计来探讨基于虚拟现实的干预对增强SEL和学习体验的影响。中国共有297名七年级学生被随机分配到三种条件中的一种：VR (n = 101)，面对面（n = 107）和对照组（n = 89）。虚拟现实和面对面条件下的参与者都参与了旨在促进SEL的协作任务，而控制条件下的参与者则没有这种干预。研究结果显示，在虚拟现实条件下，整体社交情绪能力有了显著提高，尤其是在任务表现、协作和与他人互动的子量表上。VR的介入也增强了群体凝聚力，丰富了社会体验。这些发现为在正规教育环境中设计和实施基于虚拟现实的SEL干预提供了实际意义。

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引用次数: 0

Structured briefing: Towards meaningful learning experiences with simulation games 结构化简报：通过模拟游戏获得有意义的学习体验

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-12 DOI: 10.1016/j.compedu.2025.105461

Maria Freese , Heide K. Lukosch

Simulation gaming is an interactive method to simulate complex problems, allowing learners to experience, explore, and experiment with dynamic situations and processes. Simulation gaming sessions usually consist of three key phases – briefing, gameplay, and debriefing. Often, debriefing is seen as the most important part of such a session. Even though the briefing is supposed to have a similar significance as the debriefing, it is still an underrepresented, and underexplored phase in simulation gaming research. The briefing is in many cases the first point of contact between the facilitator(s) and the learner(s), and has an influence on the learning experience and outcomes. It is therefore important to understand how to implement a meaningful briefing to support the objectives of a simulation game. However, an agreed understanding of the briefing phase does not yet exist. To address this problem, we conducted a systematic literature review and analysed existing briefing approaches. The results show that the briefing phase within a simulation gaming session can be conceptualized along its structure and content, related both to the learner(s) and the facilitator(s). Furthermore, briefing can be differentiated into three phases: pre-, main-, and post-briefing. At all phases of the briefing, the facilitator is given a significant amount of responsibility for the success of the simulation gaming session. As conclusion, we propose a new briefing framework to be used by gaming researchers and practitioners to design and evaluate briefing activities.

模拟游戏是一种模拟复杂问题的互动方法，允许学习者体验、探索和实验动态情况和过程。模拟游戏通常包括三个关键阶段——简报、游戏玩法和汇报。通常情况下，汇报被视为此类会议中最重要的部分。尽管简报应该与述职报告具有相似的意义，但在模拟游戏研究中，它仍然是一个未被充分代表和探索的阶段。在许多情况下，简报是引导者和学习者之间的第一个接触点，对学习经验和结果有影响。因此，理解如何执行有意义的简报来支持模拟游戏的目标是很重要的。但是，目前还没有就简报阶段达成商定的谅解。为了解决这个问题，我们进行了系统的文献综述，并分析了现有的简报方法。结果表明，模拟游戏会话中的简报阶段可以根据其结构和内容进行概念化，这与学习者和促进者都有关。此外，简报可以分为三个阶段：简报前、简报中和简报后。在简报的所有阶段，主持人都要为模拟游戏会议的成功承担大量的责任。最后，我们提出了一个新的简报框架，供游戏研究人员和从业者设计和评估简报活动。

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引用次数: 0

Children's engagement with digital technology in educational spaces: A scoping review 儿童在教育空间中使用数字技术：范围审查

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-08 DOI: 10.1016/j.compedu.2025.105454

Jacquelyn Harverson , Chris Zomer , Celine Chu , Sharon Horwood , Marcus Horwood , Maria Nicholas , Louise Paatsch

Children's engagement in play and learning is becoming increasingly complex as educational spaces integrate digital experiences. While engagement is often seen as a multifaceted construct, there is often no clear and generally accepted definition or understanding of what is meant when the term ‘engagement’ is used. This scoping review synthesised the ways in which engagement has been conceptualised within young children's digital experiences in educational spaces. A systematic search of seven databases captured studies published between 2011 and September 2024. Studies reporting children's engagement with digital technology (e.g., in play or learning via any digital experience) that were conducted in a formal or semi-formal educational setting were included. A total of 2661 records were screened, resulting in the inclusion of 88 studies. The concept of engagement was explicitly defined in 18 studies (19.3 %), theorised in 8 studies (9.1 %), and measured in 31 studies (35.2 %). Theoretical foundations of engagement drew from digital and educational disciplines, primarily rooted in motivational theories. Thematic analysis demonstrated the multidimensional nature of engagement, synthesised through ten key themes drawn from the definitions and measures provided. The most prominent themes identified in definitions were participation (n = 8, 44.4 %), effort (n = 7, 38.9 %) and interpersonal skills and behaviour (n = 6, 33.3 %), while those found in measures of engagement were predominantly associated with enjoyment (n = 14, 45.2 %), participation (n = 11, 35.5 %), and interest (n = 8, 25.8 %). This review highlights the need for more consistent approaches in defining and measuring children's digital engagement.

随着教育空间整合了数字体验，儿童参与游戏和学习变得越来越复杂。虽然粘性通常被视为一个多层面的结构，但对于“粘性”一词的含义，通常没有明确且普遍接受的定义或理解。这一范围审查综合了幼儿在教育空间的数字体验中参与的概念化方式。对七个数据库的系统搜索捕获了2011年至2024年9月期间发表的研究。包括在正式或半正式教育环境中进行的报告儿童参与数字技术（例如，通过任何数字体验进行游戏或学习）的研究。总共筛选了2661份记录，纳入了88项研究。18项研究（19.3%）明确定义了敬业度的概念，8项研究（9.1%）将其理论化，31项研究（35.2%）对其进行了测量。参与的理论基础来自数字和教育学科，主要植根于动机理论。专题分析显示了参与的多层面性质，通过从所提供的定义和措施中得出的十个关键主题进行综合。定义中确定的最突出的主题是参与（n = 8, 44.4%），努力（n = 7, 38.9%）以及人际交往技巧和行为（n = 6, 33.3%），而在参与措施中发现的主题主要与享受（n = 14, 45.2%），参与（n = 11, 35.5%）和兴趣（n = 8, 25.8%）相关。本次审查强调了在定义和衡量儿童数字参与方面需要更一致的方法。

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引用次数: 0

Exploring characteristics of primary school students’ self-regulated learning (SRL) behaviors in human-GenAI collaborative programming learning environments: Insights from a proposed framework 人类-基因人工智能协同编程学习环境下小学生自我调节学习行为特征研究：基于框架的洞察

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-07 DOI: 10.1016/j.compedu.2025.105453

Xuechun Ma , Cuixin Li , Jie Xu , Shiyun Zhu , Yan Li

Programming education in primary school is vital for nurturing future-ready talents, yet primary school students often struggle with self-regulated learning (SRL), particularly in resource utilization and strategy regulation. Although human-generative AI (GenAI) collaborative programming learning might have the potential to enhance personalized programming education, GenAI's interplay with SRL processes remains underexplored. To address this gap, this study first proposed a SRL Behavior Analysis Framework for human-GenAI collaborative programming learning environments and then examined SRL behaviors of a group of sixth-grade students (n = 36) in such an environment using this framework, along with various learning analytics methods including cluster analysis, descriptive statistics and lag sequential analysis. The analysis yielded the following results: (1) Based on their learning performance, primary school students were identified as three distinct clusters: programming specialized unit (PSU), high performance unit (HPU), and low performance unit (LPU). (2) Regarding SRL behaviors, students prioritized self-control (65.8 %), followed by self-observation (19 %), task analysis (12.1 %), and behavior stagnation (3.2 %). (3) Students in PSU and HPU consistently adopted goal-oriented SRL strategies, whereas students in LPU exhibited passive dependence and fragmented strategy use. GenAI's facilitative effect in supporting learning correlated with users' SRL capabilities. (4) Students in PSU and HPU exhibited frequent transitions between SRL behaviors, whereas students in LPU had insufficient ability to switch strategies when facing programming difficulties. Based on these findings, this study proposed four forward-looking design recommendations: effectively integrating GenAI with the programming environment, utilizing multimodal data and AI for learning assessment and feedback, building a cluster-driven early warning mechanism, and conducting dynamic SRL analysis and guidance based on fine-grained time-series data.

小学编程教育对于培养面向未来的人才至关重要，但小学生往往存在自我调节学习（SRL）的困难，尤其是在资源利用和策略调节方面。尽管人类生成人工智能（GenAI）协作编程学习可能具有增强个性化编程教育的潜力，但GenAI与SRL过程的相互作用仍未得到充分探索。为了解决这一差距，本研究首先提出了一个用于人类- genai协作编程学习环境的SRL行为分析框架，然后使用该框架研究了一组六年级学生（n = 36）在该环境中的SRL行为，以及各种学习分析方法，包括聚类分析、描述性统计和滞后序列分析。分析结果显示：(1)根据小学生的学习表现，将小学生划分为编程专业单元（PSU）、高性能单元（HPU）和低性能单元（LPU）三个不同的集群。(2)在SRL行为方面，学生优先选择自我控制（65.8%），其次是自我观察（19%）、任务分析（12.1%）和行为停滞（3.2%）。(3) PSU和HPU学生普遍采用目标导向的SRL策略，而LPU学生表现出被动依赖和碎片化策略使用。GenAI在支持学习方面的促进作用与用户的SRL能力相关。(4) PSU和HPU的学生在面对编程困难时表现出频繁的SRL行为转换，而LPU的学生在面对编程困难时转换策略的能力不足。基于这些发现，本研究提出了四项前瞻性设计建议：将GenAI与编程环境有效集成，利用多模态数据和AI进行学习评估和反馈，建立集群驱动的预警机制，以及基于细粒度时间序列数据进行动态SRL分析和指导。

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