Thinking Skills and Creativity最新文献_第6页

A longitudinal study on pre-service teachers’ spatial thinking skills and spatial anxiety 职前教师空间思维能力与空间焦虑的纵向研究

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-12-05 DOI: 10.1016/j.tsc.2025.102101

Alaattin Arıkan

Spatial thinking skills are integral to understanding human nature and driving technological advancements. This research examined 41 pre-service teachers’ spatial thinking skills and spatial anxiety over four years using a longitudinal approach. The data were collected through the Santa Barbara Sense of Direction Scale (SBSOD), the Spatial Anxiety Scale (SAS), and a personal information form. Analyses were conducted using ANOVA, t-tests, correlation analysis, and two-level hierarchical linear modeling (HLM). ANOVA and temporal trends from HLM revealed that pre-service teachers’ environmental spatial skills and spatial anxiety did not follow a linear progression over the four years; however, environmental spatial skills peaked, and spatial anxiety was lowest, during the second year. Furthermore, HLM analyses identified spatial anxiety, preschool education background, GPA, and gender as significant predictors of environmental spatial thinking skills. Additionally, environmental spatial thinking skills, preschool education, and gender emerged as the key predictors of spatial anxiety. Given the absence of linear development, the research recommends revising the curriculum to adopt a progressive, reflective, and application-oriented structure that supports sustained growth. Furthermore, future research could prioritize affective and experiential factors, such as spatial anxiety and preschool education, over biological factors, such as gender, to better understand the mechanisms underlying differences in spatial thinking skills.

空间思维能力对于理解人性和推动技术进步是不可或缺的。本研究采用纵向方法对41名职前教师的空间思维能力和空间焦虑进行了为期四年的调查。数据通过圣巴巴拉方向感量表（SBSOD）、空间焦虑量表（SAS）和个人信息表收集。采用方差分析、t检验、相关分析和两级层次线性模型（HLM）进行分析。方差分析和时间趋势分析表明，职前教师的环境空间技能和空间焦虑在4年内不遵循线性进展；然而，环境空间技能在第二年达到顶峰，空间焦虑最低。此外，HLM分析发现空间焦虑、学前教育背景、GPA和性别是环境空间思维技能的显著预测因子。此外，环境空间思维能力、学前教育和性别是空间焦虑的关键预测因素。鉴于缺乏线性发展，该研究建议修改课程，采用渐进式、反思式和以应用为导向的结构，以支持持续增长。此外，未来的研究可能会优先考虑情感和经验因素，如空间焦虑和学前教育，而不是生物因素，如性别，以更好地了解空间思维技能差异的机制。

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引用次数: 0

Pattern creation strategies of preschool children 学龄前儿童模式创造策略

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-12-05 DOI: 10.1016/j.tsc.2025.102095

Betül Özkan , Ensar Yıldız

This study aimed to identify the strategies used by preschool children during the pattern creation process. In line with this aim, a concurrent design, one of the mixed-method research approaches, was employed. A semi-structured interview form, an observation form, and the Pattern Skills Scale developed by Yıldız (2022) were used as data collection tools. This study included a total of 65 children selected using the criterion sampling method. Kruskal-Wallis was used for quantitative data, and descriptive analysis was used for qualitative data. The results indicated that there was a positive correlation between children's age and pattern skills. This study revealed that children used the strategies of identifying the unit, following the order, one-to-one matching, overt speech (while vocalizing), using their fingers, covert (inner) speech, checking, random sequencing, planning, and trial-and-error while completing the pattern tasks. This study also revealed that four-year-old children also used the unit finding strategy. In addition to these strategies, this study revealed that they used the strategies of overt speech (while vocalizing), covert (inner) speech, using their fingers, trial-and-error, grouping colors first, planning, and checking. Among these strategies, using fingers, trial-and-error, and overt speech (while vocalizing) can be described as basic level strategies, covert (inner) speech, grouping colors first, making a plan, and checking can be described as high-level patterning strategies.

本研究旨在了解学龄前儿童在模式创造过程中所使用的策略。为了达到这一目的，采用了混合方法研究方法之一的并行设计。采用半结构化访谈表、观察表和Yıldız（2022）开发的模式技能量表作为数据收集工具。本研究共纳入65名儿童，采用标准抽样方法。定量资料采用Kruskal-Wallis分析，定性资料采用描述性分析。结果表明，儿童的年龄与模式技能呈正相关。本研究发现，儿童在完成模式任务时使用了识别单元、顺序、一对一匹配、公开言语（发声时）、使用手指、隐藏言语（内心）、核对、随机排序、计划和试错等策略。本研究还发现，四岁儿童也使用单元寻找策略。除了这些策略外，这项研究还揭示了他们使用公开语言（发声时）、隐蔽语言（内心）、使用手指、试错、先分组颜色、计划和检查的策略。在这些策略中，使用手指、试错和公开言语（发声时）可被描述为初级策略，隐藏言语（内心）、先分组颜色、制定计划和检查可被描述为高级模式策略。

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引用次数: 0

Teacher support and adolescent creativity: The mediating effect of MAOB methylation 教师支持与青少年创造力：MAOB甲基化的中介作用

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-12-04 DOI: 10.1016/j.tsc.2025.102097

Jinghuan Zhang , Da Li , Zekun Shen , Xiaolei Yang , Shun Zhang

Although teacher support has been regarded as an important social contextual factor affecting adolescent creativity, the exact biological mechanism mediating this effect remains unknown. In a sample of Chinese male adolescents, by employing figural divergent thinking tasks as a measure of creativity, this study examined whether DNA methylation of the monoamine oxidase B gene (MAOB) mediated the effect of teacher support on adolescent creativity. The results showed that MAOB gene-body methylation partially mediated the relationship between teacher support and creativity. These findings demonstrate the first evidence for the biological mechanism mediating the link between social context and adolescent creativity. It is expected that the findings of this study could provide new insights in understanding how social context becomes biologically embedded in adolescent creativity development.

虽然教师的支持被认为是影响青少年创造力的重要社会环境因素，但介导这种影响的确切生物学机制尚不清楚。本研究以中国男性青少年为样本，采用图形发散性思维任务作为创造力的衡量标准，考察了单胺氧化酶B基因（MAOB）的DNA甲基化是否介导了教师支持对青少年创造力的影响。结果表明，MAOB基因体甲基化在教师支持与创造力的关系中起部分中介作用。这些发现为社会环境和青少年创造力之间的生物学机制提供了第一个证据。我们期望这项研究的发现能为理解社会环境如何在青少年创造力发展中发挥生物学作用提供新的见解。

引用次数: 0

Symbiosis or stagnation? Investigating the impact of AI on creativity in L1 Chinese writing 共生还是停滞？研究人工智能对母语汉语写作创造力的影响

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-12-04 DOI: 10.1016/j.tsc.2025.102096

Guangyuan Yao

The rapid integration of generative artificial intelligence (AI) into creative writing processes has sparked a critical debate about its impact on human creativity. This study investigates how varying levels of AI assistance influence creativity in L1 Chinese creative writing. Using a mixed-methods approach, the research examines three experimental groups: a control group (no AI), an AI brainstorming group (limited AI), and an AI co-writing group (full AI). The findings suggest a curvilinear relationship between AI intervention and creativity: while limited AI use enhances creativity, extensive AI assistance leads to diminished originality. Specifically, the AI brainstorming group exhibited the highest scores in creativity, particularly in originality, while the AI co-writing group produced highly elaborate but less original texts. Interviews revealed that AI functions both as a catalyst for creative expansion and as a potential crutch, leading to concerns about the loss of personal authorship. The findings expand the theoretical understanding of AI’s role in creative writing, highlighting how different levels of AI assistance influence the structural and linguistic qualities of written work. By investigating the psychological and perceptual aspects of AI-assisted creativity, this research advances theories of human-AI co-creativity and offers insights into how AI tools can be effectively integrated into creative writing practices.

生成式人工智能（AI）与创意写作过程的快速融合引发了一场关于其对人类创造力影响的激烈辩论。本研究探讨不同程度的人工智能辅助如何影响母语中文创意写作的创造力。该研究采用混合方法，研究了三个实验组：对照组（无人工智能）、人工智能头脑风暴组（有限人工智能）、人工智能共同写作组（完全人工智能）。研究结果表明，人工智能干预与创造力之间存在曲线关系：虽然有限的人工智能使用增强了创造力，但大量的人工智能帮助会削弱原创性。具体来说，人工智能头脑风暴组在创造力，尤其是原创性方面表现出了最高的得分，而人工智能共同写作组则制作了非常精致但缺乏原创性的文本。采访显示，人工智能既可以作为创造性扩展的催化剂，也可以作为潜在的拐杖，导致人们担心失去个人原创能力。研究结果拓展了对人工智能在创意写作中的作用的理论理解，突出了不同水平的人工智能辅助如何影响书面作品的结构和语言质量。通过研究人工智能辅助创造力的心理和感知方面，本研究推进了人类与人工智能共同创造力的理论，并为如何将人工智能工具有效地整合到创意写作实践中提供了见解。

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引用次数: 0

From rote learning to critical inquiry: fostering higher order thinking skills through collaborative questioning in a rural secondary English-medium science classroom 从死记硬背到批判性探究：在农村中学英语科学课堂中通过合作提问培养更高层次的思维技能

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-12-03 DOI: 10.1016/j.tsc.2025.102093

Harsha Dulari Wijesekera , Ruzaika Hameed

Fostering higher-order thinking for inquiry-driven learning is a critical priority in Sri Lanka’s English-Medium Instruction (EMI) science classrooms, where examination-oriented learning and English language barriers limit critical thinking and meaningful cognitive engagement. This practitioner interventionist action research (PIAR) examined how to foster higher-order thinking (HOT) in EMI science classrooms in Sri Lanka. Twenty-one eighth-grade students participated in a mixed-method, quasi-experimental single-group pre-test/post-test design. The intervention comprised two strategies: “What If” questioning and “Notice and Wonder” within collaborative groups. Findings revealed a significant improvement in HOT, with students' mean test scores increasing from pre- to post-test. Qualitative analysis of student perceptions and teacher reflections indicated enhanced deeper cognitive engagement by necessitating co-construction of knowledge through peer feedback and increased problem-solving autonomy - shifting students towards a more analytical mindset. Students also demonstrated greater curiosity and willingness to engage with complex scientific concepts. By showing how simple yet intentional strategies can expand learning opportunities in linguistically and resource-constrained EMI contexts, this study contributes to understanding how HOT can be cultivated in environments where rote memorization dominates. The study provides insights into effective pedagogic practices, curriculum design, and education policy. It also suggests that targeted interventions can transform classroom culture by bridging language, content, and thinking skills gaps in science education.

在斯里兰卡的英语教学（EMI）科学课堂中，培养探究驱动学习的高阶思维是一个关键的优先事项，以考试为导向的学习和英语语言障碍限制了批判性思维和有意义的认知参与。本实践者干预行动研究（PIAR）探讨了如何在斯里兰卡的EMI科学课堂中培养高阶思维（HOT）。21名八年级学生参加了混合方法、准实验的单组前测/后测设计。干预包括两种策略：在合作小组中提出“如果”问题和“注意和好奇”。研究结果显示，学生的平均测试分数从测试前到测试后显著提高。对学生认知和教师反思的定性分析表明，通过同伴反馈和提高解决问题的自主性，需要共同构建知识，从而增强了更深层次的认知参与——将学生转向更善于分析的心态。学生们也表现出更大的好奇心和参与复杂科学概念的意愿。通过展示简单而有意识的策略如何在语言和资源受限的EMI环境中扩大学习机会，本研究有助于理解如何在死记硬背占主导地位的环境中培养HOT。这项研究为有效的教学实践、课程设计和教育政策提供了见解。它还表明，有针对性的干预可以通过弥合科学教育中的语言、内容和思维技能差距来改变课堂文化。

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引用次数: 0

Revealing the association between challenging events encountered by students and their social regulation behaviors in GAI-supported collaborative learning 揭示在人工智能支持的协作学习中，学生遇到的挑战性事件与他们的社会调节行为之间的关系

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-12-03 DOI: 10.1016/j.tsc.2025.102100

Si Zhang, Wenying Zhang

While an increasing number of studies have emphasized the importance of social regulation, few have specifically examined the challenging events encountered by learners and their social regulation processes and patterns in collaborative learning. To address this gap, we adopted a network modeling approach to reveal the association between challenging events and social regulation in collaborative learning, in addition to traditional coding and counting methods. This study investigated the categories of challenging events encountered by 30 student teachers in GAI-supported collaborative learning activities and the social regulation behaviors used to address these challenging events through statistical analysis, epistemic network analysis, and thematic analysis. The results showed that student teachers encountered five categories of challenging events in GAI-supported collaborative learning: motivational challenges, socio-emotional challenges, cognitive challenges, metacognitive challenges, and environmental challenges. Student teachers employed various social regulation behaviors to address these challenges, resulting in 37 “challenge-social regulation” pairing patterns. Among them, the social regulation process patterns for motivational challenges, cognitive challenges, and metacognitive challenges were similar. Additionally, we supplemented the student teachers’ perceptions of challenging events in collaborative learning from interview data. Finally, we discussed the implications, limitations, and future research directions of the study to assist in the design and implementation of collaborative learning activities.

虽然越来越多的研究强调了社会调节的重要性，但很少有研究专门研究学习者在协作学习中遇到的具有挑战性的事件及其社会调节过程和模式。为了解决这一差距，除了传统的编码和计数方法外，我们还采用了网络建模方法来揭示协作学习中挑战性事件与社会监管之间的关联。本研究通过统计分析、认知网络分析和专题分析，调查了30名实习教师在人工智能支持的协作学习活动中遇到的挑战性事件的类别，以及应对这些挑战性事件的社会调节行为。结果表明，在人工智能支持的协作学习中，实习教师遇到了五类挑战事件：动机挑战、社会情感挑战、认知挑战、元认知挑战和环境挑战。学生教师采用不同的社会调节行为来应对这些挑战，产生了37种“挑战-社会调节”配对模式。其中，动机挑战、认知挑战和元认知挑战的社会调节过程模式相似。此外，我们从访谈数据中补充了实习教师对协作学习中具有挑战性事件的看法。最后，我们讨论了本研究的意义、局限性和未来的研究方向，以协助合作学习活动的设计和实施。

{"title":"Revealing the association between challenging events encountered by students and their social regulation behaviors in GAI-supported collaborative learning","authors":"Si Zhang, Wenying Zhang","doi":"10.1016/j.tsc.2025.102100","DOIUrl":"10.1016/j.tsc.2025.102100","url":null,"abstract":"<div><div>While an increasing number of studies have emphasized the importance of social regulation, few have specifically examined the challenging events encountered by learners and their social regulation processes and patterns in collaborative learning. To address this gap, we adopted a network modeling approach to reveal the association between challenging events and social regulation in collaborative learning, in addition to traditional coding and counting methods. This study investigated the categories of challenging events encountered by 30 student teachers in GAI-supported collaborative learning activities and the social regulation behaviors used to address these challenging events through statistical analysis, epistemic network analysis, and thematic analysis. The results showed that student teachers encountered five categories of challenging events in GAI-supported collaborative learning: motivational challenges, socio-emotional challenges, cognitive challenges, metacognitive challenges, and environmental challenges. Student teachers employed various social regulation behaviors to address these challenges, resulting in 37 “challenge-social regulation” pairing patterns. Among them, the social regulation process patterns for motivational challenges, cognitive challenges, and metacognitive challenges were similar. Additionally, we supplemented the student teachers’ perceptions of challenging events in collaborative learning from interview data. Finally, we discussed the implications, limitations, and future research directions of the study to assist in the design and implementation of collaborative learning activities.</div></div>","PeriodicalId":47729,"journal":{"name":"Thinking Skills and Creativity","volume":"60 ","pages":"Article 102100"},"PeriodicalIF":4.5,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Making failure desired during learning – A quasi-experimental study 在学习过程中渴望失败-一项准实验研究

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-12-02 DOI: 10.1016/j.tsc.2025.102094

Tanmay Sinha

One hundred and nineteen ninth-grade students engaged in one of two preparatory interventions – growth mindset or utility value – aimed at increasing the desirability of failure in learning during a quasi-experimental study. An additional fifty-one students participated in a control condition that offered no such preparation. Everyone then underwent a standard productive failure learning task where they ideated to solve an open-ended math problem prior to receiving a formal lecture on the targeted concept. Following mixed-methods analysis, my empirical results for the growth mindset and utility value conditions showed improvements in students’ beliefs about failure and their math expectancies, and similar persistence behaviors during problem-solving (compared to the control condition). Posttest performance following the lecture did not differ across the three conditions. With this work, I bring together complementary lines of research on low-cost and scalable motivational interventions in learning, typically applied to improve engagement with learning content, to contemporary learning sciences pedagogies like productive failure, in the novel service of making failure desired for students.

在一项准实验研究中，199名九年级学生参与了两种预备干预——成长心态或效用价值——中的一种，目的是增加对学习失败的渴望。另外51名学生参加了不提供这种准备的控制条件。然后，每个人都经历了一个标准的生产性失败学习任务，在接受关于目标概念的正式讲座之前，他们想要解决一个开放式的数学问题。在混合方法分析之后，我对成长心态和效用价值条件的实证结果显示，学生对失败的信念和他们的数学期望有所改善，在解决问题过程中也有类似的坚持行为（与控制条件相比）。讲座后的测试表现在三种情况下没有差异。通过这项工作，我将学习中的低成本和可扩展的动机干预研究（通常用于提高对学习内容的参与）与当代学习科学教学法（如生产性失败）结合起来，以新颖的服务使学生期望失败。

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引用次数: 0

Automated Scoring of Question Complexity with Transformer Language Models 使用转换语言模型的问题复杂性自动评分

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-11-28 DOI: 10.1016/j.tsc.2025.102090

Tuval Raz , Simone A. Luchini , Roger E. Beaty , Yoed N. Kenett

Question-asking, an essential yet understudied activity, holds significant implications for learning, creativity, and cognitive development. Research shows that asking complex, open-ended questions is better for learning than closed ones. Previous research has explored open-ended question complexity through Bloom’s taxonomy, but the measurement of complexity remains challenging. Recent advancements in natural language processing have enabled automated scoring of psychological tasks aligned to human-ratings. However, automatic assessment of open-ended questions remains understudied. We address this gap by fine-tuning transformer language models to predict human ratings of open-ended question complexity and comparing them to existing baseline measures (i.e., word count and semantic distance). Using previously collected human-rated responses and Bloom ratings from a creative question-asking task, we trained an encoder model (RoBERTa) and a Large Language Model (Llama-2-7B). Our results reveal that RoBERTa correlated strongly with human ratings of complexity (r = .73), exceeding baseline measures and offering an efficient, lightweight solution suitable for broad adoption. Our fine-tuned LLaMA 2 model achieved stronger performance (r = .84), establishing a new benchmark for predictive accuracy. Thus, we demonstrate how language models can be utilized to automatically score the complexity of open-ended questions. Importantly, LLaMA 2 demonstrates higher accuracy, while RoBERTa provides a replicable, accessible, and cost-effective option for everyday educational and psychological applications. Our work paves the way for automatic assessment of open-ended questions, which are critical across a wide range of cognitive domains.

提问是一项重要但尚未得到充分研究的活动，对学习、创造力和认知发展具有重要意义。研究表明，问复杂的、开放式的问题比封闭性的问题更有利于学习。以前的研究已经通过Bloom的分类法探索了开放式问题的复杂性，但复杂性的测量仍然具有挑战性。自然语言处理的最新进展使心理任务的自动评分与人类评分一致。然而，开放式问题的自动评估仍未得到充分研究。我们通过微调转换语言模型来预测人类对开放式问题复杂性的评分，并将其与现有的基线测量（即字数和语义距离）进行比较，从而解决了这一差距。利用之前收集的人类评分的回答和Bloom评分，我们训练了一个编码器模型（RoBERTa）和一个大型语言模型（Llama-2-7B）。我们的结果表明，RoBERTa与人类对复杂性的评价有很强的相关性（r = 0.73），超过了基线测量，并提供了一个有效的、轻量级的解决方案，适合广泛采用。我们的微调LLaMA 2模型获得了更强的性能（r = 0.84），为预测精度建立了新的基准。因此，我们演示了如何使用语言模型来自动对开放式问题的复杂性进行评分。重要的是，LLaMA 2显示出更高的准确性，而RoBERTa为日常教育和心理应用提供了可复制，可访问和成本效益高的选择。我们的工作为开放式问题的自动评估铺平了道路，这在广泛的认知领域至关重要。

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引用次数: 0

Qian Xuesen’s question Ⅱ: How and when does collectivism affect divergent thinking? 钱学森的问题Ⅱ：集体主义是如何以及何时影响发散思维的？

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-11-26 DOI: 10.1016/j.tsc.2025.102092

Yuxin Shi , Fangxing Chen , Ya Gao , Wanjun Zhou , Le Wang , Shou Wang , Qingbai Zhao , Quanlei Yu

The relationship between culture and divergent thinking has received extensive attention from scholars, but its internal mechanism is still unclear. Although our previous studies suggest that the characteristics of divergent thinking in collectivist cultural tendency may be due to the structural properties of its semantic network, direct evidence is lacking. Therefore, this study aims to explore the internal mechanism of the influence of collectivist cultural tendency on divergent thinking by measuring semantic network structure. A total of 151 participants were assessed by measuring collectivism-individualism tendencies, fluid intelligence, semantic network, and divergent thinking. The results indicated that fluid intelligence moderates the relationship between collectivism and semantic network, meanwhile, the interaction between collectivism and fluid intelligence influences the originality of divergent thinking through semantic network. These findings enhance our theoretical understanding of creative differences across various cultural tendencies.

文化与发散思维的关系受到学者们的广泛关注，但其内在机制尚不清楚。虽然我们以往的研究认为集体主义文化倾向的发散性思维特征可能与其语义网络的结构特性有关，但缺乏直接证据。因此，本研究旨在通过测量语义网络结构来探讨集体主义文化倾向对发散思维影响的内在机制。共有151名参与者通过测量集体主义-个人主义倾向、流动智力、语义网络和发散思维进行了评估。结果表明，流体智力调节了集体主义与语义网络的关系，集体主义与流体智力的交互作用通过语义网络影响发散思维的原创性。这些发现增强了我们对不同文化倾向的创造性差异的理论理解。

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引用次数: 0

Effects of troubleshooting robotics learning on students’ engagement, computational thinking, and programming skills 机器人故障排除学习对学生参与、计算思维和编程技能的影响

IF 4.5 2区教育学 Q1 Social Sciences

Thinking Skills and Creativity

Pub Date : 2025-11-26 DOI: 10.1016/j.tsc.2025.102068

Yang Wang

Learning engagement is an important indicator of active learning outcomes. Computational thinking is a basic competency required in the 21st century. Troubleshooting learning is helpful to enhance students’ computational thinking and engagement, as its targeted error analysis addresses traditional learning’s limitation of insufficient guidance on error-prone points. However, the role of troubleshooting in students’ engagement and computational thinking in robotics programming learning is to be explored. To fill in this gap, the current study explored the effects of troubleshooting robotics programming learning on students’ engagement, computational thinking, and programming skills. A quasi-experimental study was conducted to explore the effects of troubleshooting learning on students’ robotics programming learning by comparing students’ learning results in two courses instructed by the same instructor (one instructed with a problem-based method, the other instructed with a troubleshooting method). The participants were seventy-nine students from a university in China. Questionnaires, tests, and work analyses were used to measure students’ engagement, computational thinking, and programming skills. The results indicated that troubleshooting learning is more effective in enhancing students’ engagement (i.e., behavioral, cognitive, and emotional engagement), computational thinking (i.e., cooperativity, critical thinking, and creativity) and programming learning (i.e., data representation). The findings provide insight into troubleshooting-supported robotics programming learning. Different types of troubleshooting tasks with progressive difficulty are effective in enhancing students’ learning. Troubleshooting could be used in the early stages of programming learning to help students master the error prone areas of programming.

学习投入是积极学习成果的重要指标。计算思维是21世纪所需要的基本能力。故障诊断学习有助于增强学生的计算思维和参与，因为它的针对性错误分析解决了传统学习对易出错点指导不足的局限性。然而，在机器人编程学习中，故障排除在学生参与和计算思维中的作用有待探讨。为了填补这一空白，本研究探讨了故障排除机器人编程学习对学生参与度、计算思维和编程技能的影响。采用准实验研究的方法，通过比较学生在同一位教师的两门课程（一门课程采用问题教学法，另一门课程采用故障排除教学法）上的学习结果，探讨故障排除学习对学生机器人编程学习的影响。参与者是来自中国一所大学的79名学生。问卷调查、测试和工作分析被用来衡量学生的参与度、计算思维和编程技能。结果表明，故障排除学习在提高学生的参与（即行为、认知和情感参与）、计算思维（即合作、批判性思维和创造力）和编程学习（即数据表示）方面更有效。这些发现为故障排除支持的机器人编程学习提供了见解。难度渐进式的不同类型的故障排除任务能有效地促进学生的学习。故障排除可以用于编程学习的早期阶段，以帮助学生掌握编程中容易出错的领域。

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引用次数: 0