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The Impact of Humorous Pedagogical Agents on Student Engagement and Academic Performance in Science Education 幽默教学主体对科学教育中学生投入和学习成绩的影响
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-09-02 DOI: 10.1111/jcal.70107
Fateme Ashrafzade, Yousef Mahdavinasab, Nasrin Mohammadhasani, Mahsa Moradi

Background

The integration of pedagogical agents (PAs) into educational settings has become widespread, yet the impact of humorous versus non-humorous PAs on student academic performance and engagement remains underexplored. Although research highlights the benefits of PAs, the specific role of humour in enhancing educational outcomes is not well studied.

Objectives

This study evaluates the effectiveness of humorous PAs compared to non-humorous PAs in improving academic performance and student engagement among fifth-grade students in science education.

Methods

A quasi-experimental design with pre-test and post-test measures was used. A sample of 78 fifth-grade students from District 4 of Tehran during the 2022–2023 academic year participated in the study. Three classes, balanced by the school based on academic performance, were randomly selected, and each was assigned to one of three groups: humorous PA (n = 28), non-humorous PA (n = 25) and no PA (n = 25). Data were collected using a researcher-developed learning test and the Reeve Student Engagement Questionnaire (2013), and analysed using ANCOVA.

Results

The humorous PA group showed higher levels of student academic performance and engagement outcomes compared to the non-humorous PA and no PA groups. The ‘humorous PA’ group achieved the highest scores in both engagement and academic performance.

Conclusions

These findings suggest that incorporating humour into PAs can significantly enhance educational experiences and effectiveness. The study highlights the importance of considering the personality and style of PAs to optimise student engagement and academic performance.

教学代理(PAs)在教育环境中的整合已经变得普遍,然而幽默和非幽默的pa对学生学业成绩和参与的影响仍未得到充分探讨。尽管研究强调了pa的好处,但幽默在提高教育成果方面的具体作用还没有得到很好的研究。目的:本研究旨在评估幽默语习与非幽默语习在提高五年级学生科学教育学习成绩和学生参与度方面的效果。方法采用准实验设计,采用前测和后测相结合的方法。在2022-2023学年期间,来自德黑兰第四区的78名五年级学生参加了这项研究。根据学校的学习成绩,随机选择了三个班级,每个班级被分配到三组中的一个:幽默的PA (n = 28),非幽默的PA (n = 25)和没有PA (n = 25)。使用研究人员开发的学习测试和Reeve学生参与问卷(2013)收集数据,并使用ANCOVA进行分析。结果幽默PA组学生的学习成绩和敬业度高于非幽默PA组和无PA组。“幽默PA”组在参与和学习成绩上都取得了最高分。结论幽默教学可以显著提高教师的教学体验和教学效果。该研究强调了考虑私人助理的个性和风格以优化学生参与度和学习成绩的重要性。
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引用次数: 0
A Meta-Analysis of the Impact of Generative Artificial Intelligence on Learning Outcomes 生成式人工智能对学习结果影响的荟萃分析
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-09-01 DOI: 10.1111/jcal.70117
Nan Ma, Zhiyong Zhong
<div> <section> <h3> Background</h3> <p>With the rapid advancement of technology, the integration of Generative Artificial Intelligence (GAI) in education has gained considerable attention. Many studies have examined GAI's impact on learning outcomes, yet their conclusions are inconsistent, highlighting the need for a comprehensive review to clarify its overall effects and identify influential factors.</p> </section> <section> <h3> Objectives</h3> <p>This study aims to conduct a meta-analysis of the effects of GAI on student learning outcomes across cognitive, competency and affective dimensions. Additionally, it seeks to explore how various moderating factors, including subject discipline, instructional duration, knowledge type, prior knowledge and tool type, influence GAI's effectiveness.</p> </section> <section> <h3> Methods</h3> <p>A meta-analysis was performed on 34 experimental and quasi-experimental studies published internationally. Effect sizes were calculated for overall learning outcomes and categorised by dimension. Further analysis was conducted to assess the influence of moderating variables on the impact of GAI.</p> </section> <section> <h3> Results</h3> <p>The meta-analysis indicates that Generative Artificial Intelligence has a significant positive impact on overall learning outcomes, with a combined effect size of 0.68 (<i>p</i> < 0.001). The impact is particularly pronounced in the cognitive dimension (<i>g</i> = 0.795) and the competency dimension (<i>g</i> = 0.711), while its effect on the affective dimension (<i>g</i> = 0.507) is moderate but still significant. The analysis of moderating variables reveals that the effectiveness of GAI is influenced by discipline type but is not significantly affected by instructional period, knowledge type, prior knowledge level, or tool type. Specifically, GAI exhibits the highest positive effects in mathematics, science and humanities, whereas its impact is relatively lower yet still significant in computer science and medical/nursing education. Additionally, GAI's effectiveness does not significantly differ across various instructional periods, different knowledge types, learners with varying prior knowledge levels, or different AI tool versions.</p> </section> <section> <h3> Conclusions</h3> <p>To optimise GAI's use in education, the study suggests aligning GAI with specific subject needs, adapting tools for different student levels, integrating GAI with traditional teaching and establishing monitoring mechanisms. These strategies aim to maximise GAI's positive impact on learning efficienc
随着科技的飞速发展,生成式人工智能(GAI)在教育中的应用受到了广泛的关注。许多研究调查了GAI对学习成果的影响,但他们的结论不一致,突出表明需要进行全面审查,以澄清其总体影响并确定影响因素。本研究旨在从认知、能力和情感三个维度对GAI对学生学习成果的影响进行meta分析。此外,它试图探索各种调节因素,包括学科学科,教学时间,知识类型,先验知识和工具类型,如何影响GAI的有效性。方法对国际上发表的34篇实验和准实验研究进行meta分析。计算总体学习结果的效应量,并按维度分类。进一步分析了调节变量对GAI影响的影响。荟萃分析表明,生成式人工智能对整体学习结果有显著的积极影响,综合效应值为0.68 (p < 0.001)。对认知维度(g = 0.795)和胜任力维度(g = 0.711)的影响尤为显著,对情感维度(g = 0.507)的影响虽不明显,但依然显著。调节变量分析表明,GAI的有效性受学科类型的影响,而受教学时间、知识类型、先验知识水平和工具类型的影响不显著。具体而言,GAI在数学、科学和人文学科中表现出最高的积极影响,而在计算机科学和医学/护理教育方面的影响相对较低,但仍然显著。此外,GAI的有效性在不同的教学周期、不同的知识类型、不同先验知识水平的学习者或不同的人工智能工具版本之间没有显著差异。为了优化GAI在教育中的应用,该研究建议将GAI与特定学科需求相结合,为不同学生水平调整工具,将GAI与传统教学相结合,并建立监测机制。这些战略旨在最大限度地发挥GAI对整个教育环境的学习效率和质量的积极影响。
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引用次数: 0
Exploring the Factors That Promote a Balance Between Academic Integrity and the Effective Use of GenAI Tools in Higher Education: A Systematic Review 探索促进高等教育学术诚信与基因工具有效使用之间平衡的因素:系统综述
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-31 DOI: 10.1111/jcal.70109
Daniel Kangwa, Mgambi Msambwa Msafiri, Antony Fute

Background

This study explored the factors that influence the balance between academic integrity and the effective use of GenAI tools in higher education. It focused on the role of institutional guidelines in enhancing the responsible use of GenAI technologies to enhance academic integrity.

Objectives

The study was theoretically grounded in the Technology Acceptance Model and the Theory of Planned Behaviour to investigate the factors that promote academic integrity in using GenAI tools (RQ1), their impact and institutional strategies to effectively mitigate ethical risks (RQ2) and the model practices to support the ethical and effective use in higher education (RQ3).

Methods

The PRISMA framework was used to systematically review and thematically synthesise the results of 213 peer-reviewed articles published between January 2021 and May 2025.

Results

Finding indicates that academic support, defined by structured training, technical scaffolding, and perceived usefulness, is critical to enabling ethical GenAI use. Additionally, student self-regulation, as influenced by behavioural control and goal setting, was associated with greater academic integrity in GenAI-mediated learning. Whereas institutional policies varied widely, those with transparent, adaptive and discipline-responsive governance frameworks more effectively mitigated academic misconduct. Indeed, the model practices included GenAI ethics committees, interactive GenAI literacy modules, and the developer-educator collaborations to promote algorithmic transparency.

Conclusions

A comprehensive systems-based approach that encompasses academic support, self-regulation and ethical guidelines is critical for the responsible use of GenAI tools in education. Hence, to preserve academic integrity while nurturing innovation, institutions should integrate GenAI ethics into curricular design, faculty development and cross-sectoral policy frameworks. Future research may expand into multilingual and longitudinal analyses to support equitable and sustainable GenAI integration across diverse educational settings.

本研究探讨了影响高等教育中学术诚信与GenAI工具有效使用之间平衡的因素。它侧重于机构准则在加强负责任地使用基因人工智能技术以加强学术诚信方面的作用。本研究以技术接受模型(Technology Acceptance Model)和计划行为理论(Theory of Planned behavior)为理论基础,探讨在使用GenAI工具时促进学术诚信的因素(RQ1)、它们的影响和有效降低伦理风险的制度策略(RQ2),以及支持伦理和有效地在高等教育中使用的模型实践(RQ3)。方法采用PRISMA框架对2021年1月至2025年5月发表的213篇同行评议文章进行系统综述和专题综合。研究结果表明,学术支持(由结构化培训、技术脚手架和感知有用性定义)对于伦理地使用GenAI至关重要。此外,受行为控制和目标设定影响的学生自我调节与基因人工智能介导的学习中更大的学术诚信有关。虽然机构政策差异很大,但那些具有透明、适应性强和符合学科的治理框架的机构更有效地减轻了学术不端行为。实际上,模型实践包括GenAI伦理委员会、交互式GenAI识字模块,以及促进算法透明度的开发者-教育者合作。一种全面的基于系统的方法,包括学术支持、自我监管和道德准则,对于在教育中负责任地使用GenAI工具至关重要。因此,为了在培育创新的同时保持学术诚信,各院校应将基因伦理纳入课程设计、师资发展和跨部门政策框架。未来的研究可能会扩展到多语言和纵向分析,以支持在不同教育环境中公平和可持续的GenAI整合。
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引用次数: 0
Evaluating the Efficacy of an Intelligent Tutoring System That Integrates Affective Supports Into Math Learning 评估将情感支持整合到数学学习中的智能辅导系统的效果
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-29 DOI: 10.1111/jcal.70106
Mingyu Feng, Natalie Brezack, Chunwei Huang, Yvonne Kao, Kelly Collins, Melissa Lee, Megan Schneider, Wynnie Chan

Background

Computer-assisted educational technologies that integrate affective supports into math practices could be particularly beneficial for addressing troubling declines in middle grade students' math achievement, affect, and motivation. MathSpring is a web-based intelligent tutor that offers personalised content, remedial tutoring, and affective support for students and diagnostic reports on students' progress and effort for teachers.

Objectives

This preregistered randomised control trial experiment sought to experimentally test the efficacy of the MathSpring platform in improving students' math achievement and dispositions towards math.

Methods

The final sample included 53 teachers and their 2003 10–12-year-old students from one U.S. state. Teachers were randomly assigned to either use MathSpring with their students (treatment condition) or continue business-as-usual math instruction (control condition) for one school year. Before and after the intervention, students' math achievement was measured with standardised math assessments and their dispositions towards math were measured with standardised surveys. Teachers completed logs, surveys, and interviews about their implementation.

Results and Conclusions

The results indicated that students in the treatment group did not show evidence of improved achievement, affect, or dispositions towards math compared with students who received business-as-usual math instruction. Still, exploratory analyses indicated that students with high usage demonstrated greater achievement than those in the business-as-usual group. Though no overall effects of this intervention were detected, educational technology interventions with affective supports still hold potential for improving students' academic and dispositional outcomes.

计算机辅助教育技术将情感支持整合到数学实践中,对于解决初中学生数学成绩、情感和动机的令人不安的下降尤其有益。MathSpring是一个基于网络的智能家教,为学生提供个性化的内容、补习辅导和情感支持,并为教师提供学生进步和努力的诊断报告。本预注册随机对照试验旨在通过实验测试MathSpring平台在提高学生数学成绩和数学倾向方面的功效。方法最终样本包括来自美国一个州的53名教师及其2003名10 - 12岁的学生。教师们被随机分配到与学生一起使用MathSpring(治疗组)或继续照常进行数学教学(对照组)一学年。在干预前后,采用标准化数学评估测量学生的数学成绩,并采用标准化调查测量学生的数学倾向。教师们完成了关于实施的日志、调查和访谈。结果与结论结果表明,与接受常规数学教学的学生相比,治疗组的学生没有表现出成绩、情感或数学倾向的改善。尽管如此,探索性分析表明,高使用率的学生比那些一切照旧的学生表现出更大的成就。虽然没有检测到这种干预的总体效果,但具有情感支持的教育技术干预仍然具有改善学生学业和性格结果的潜力。
{"title":"Evaluating the Efficacy of an Intelligent Tutoring System That Integrates Affective Supports Into Math Learning","authors":"Mingyu Feng,&nbsp;Natalie Brezack,&nbsp;Chunwei Huang,&nbsp;Yvonne Kao,&nbsp;Kelly Collins,&nbsp;Melissa Lee,&nbsp;Megan Schneider,&nbsp;Wynnie Chan","doi":"10.1111/jcal.70106","DOIUrl":"https://doi.org/10.1111/jcal.70106","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Computer-assisted educational technologies that integrate affective supports into math practices could be particularly beneficial for addressing troubling declines in middle grade students' math achievement, affect, and motivation. MathSpring is a web-based intelligent tutor that offers personalised content, remedial tutoring, and affective support for students and diagnostic reports on students' progress and effort for teachers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This preregistered randomised control trial experiment sought to experimentally test the efficacy of the MathSpring platform in improving students' math achievement and dispositions towards math.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The final sample included 53 teachers and their 2003 10–12-year-old students from one U.S. state. Teachers were randomly assigned to either use MathSpring with their students (treatment condition) or continue business-as-usual math instruction (control condition) for one school year. Before and after the intervention, students' math achievement was measured with standardised math assessments and their dispositions towards math were measured with standardised surveys. Teachers completed logs, surveys, and interviews about their implementation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results and Conclusions</h3>\u0000 \u0000 <p>The results indicated that students in the treatment group did not show evidence of improved achievement, affect, or dispositions towards math compared with students who received business-as-usual math instruction. Still, exploratory analyses indicated that students with high usage demonstrated greater achievement than those in the business-as-usual group. Though no overall effects of this intervention were detected, educational technology interventions with affective supports still hold potential for improving students' academic and dispositional outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 5","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144915301","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
Exploring the Effects of the CER Model-Based GenAI Learning System to Cultivate Elementary School Students' Computational Thinking Core Skills in Science Courses 基于CER模型的GenAI学习系统在科学课程中培养小学生计算思维核心技能的效果探讨
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-29 DOI: 10.1111/jcal.70110
Jia-Hua Zhao, Shu-Tao Shangguan, Ying Wang

Background

Computational thinking (CT) is a fundamental ability required of individuals in the 21st-century digital world. Past studies show that generative artificial intelligence (GenAI) can enhance students' CT skills. However, GenAI may produce inaccurate output, and students who rely too much on AI may learn little and be unable to think independently. Besides, most research on CT mainly focused on Scratch or programming classes, but incorporating it into the K-12 science curriculum is better for students' deep learning and CT core skills development.

Objectives

This study proposed a causal explanation and reflection (CER) model-based GenAI learning system in science courses to cultivate students' CT core skills.

Sample

One hundred and eighteen elementary school students in three different classes participated in this study.

Methods

A quasi-experiment was conducted in Fujian, China. Students in the experimental group learned with the CER model-based GenAI learning system; students learned with the CER model-based learning system in control group 1; students in control group 2 used the causal-explanation-based GenAI learning system. Students' learning achievement and CT core skills were examined.

Results

The results showed that the CER model-based GenAI learning system significantly improved students' science learning and CT core skills. Interview results further showed some students complained that GenAI only provided answers without encouraging them to comprehend the material.

Conclusions

CT should not exist only in computer courses. Instead, it is an approach to problem-solving that applies to all disciplines. Also, over-reliance on GenAI may hinder learning ability. The effectiveness of GenAI-based learning depends on its judicious use.

计算思维(CT)是21世纪数字世界中个人所需的基本能力。过去的研究表明,生成式人工智能(GenAI)可以提高学生的CT技能。然而,GenAI可能会产生不准确的输出,过于依赖AI的学生可能会学得很少,无法独立思考。此外,大多数关于CT的研究主要集中在Scratch或编程课程上,但将其纳入K-12科学课程更有利于学生的深度学习和CT核心技能的发展。目的在理科课程中建立基于因果解释与反思(CER)模型的GenAI学习系统,培养学生的CT核心技能。本研究以三个不同班级的118名小学生为研究对象。方法在福建省进行准实验。实验组学生使用基于CER模型的GenAI学习系统进行学习;对照组1采用基于CER模型的学习系统进行学习;对照组2使用基于因果解释的GenAI学习系统。考察学生的学习成绩和CT核心技能。结果基于CER模型的GenAI学习系统显著提高了学生的科学学习和CT核心技能。访谈结果进一步显示,一些学生抱怨GenAI只提供答案,而没有鼓励他们理解材料。结论CT不应只存在于计算机课程中。相反,它是一种适用于所有学科的解决问题的方法。此外,过度依赖GenAI可能会阻碍学习能力。基于基因人工智能的学习的有效性取决于它的明智使用。
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引用次数: 0
An Artificial Intelligence-Enabled Group Cognitive Diagnosis Approach With the Goal of Promoting Online Collaborative Learning 以促进在线协作学习为目标的人工智能支持的群体认知诊断方法
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-29 DOI: 10.1111/jcal.70113
Lanqin Zheng, Zichen Huang, Lei Gao, Yunchao Fan

Background

Online collaborative learning has been broadly applied in the field of higher education. Nevertheless, not all types of collaborative learning can produce the desired learning results.

Objectives

To facilitate online collaborative learning, the present study proposed an innovative artificial intelligence-enabled group cognitive diagnosis approach with the goal of improving online collaborative learning.

Methods

A total of 135 college students was included in the current study and divided into 45 groups. A total of 15 groups consisting of 45 students used the group cognitive diagnosis approach. An additional 15 groups were assigned to the group knowledge graph approach, while the remaining 15 groups were assigned to the traditional online collaborative learning approach.

Results and Conclusions

The findings of this research indicated that the group cognitive diagnosis approach had more significant and positive impacts on collaborative learning performance, knowledge elaboration, and higher-order cognitive engagement than did the group knowledge graph and traditional online collaborative learning approaches.

Implications

The current study deepens our understanding of group cognition and the corresponding complex interactions and provides a new method for improving online collaborative learning.

在线协作学习在高等教育领域得到了广泛的应用。然而,并不是所有类型的协作学习都能产生预期的学习结果。为了促进在线协作学习,本研究提出了一种创新的基于人工智能的群体认知诊断方法,旨在改善在线协作学习。方法将135名大学生分为45组。15组45名学生采用群体认知诊断方法。另外15组被分配到小组知识图方法,而其余15组被分配到传统的在线协作学习方法。结果与结论本研究结果表明,群体认知诊断方法对协作学习绩效、知识阐述和高阶认知投入的影响比群体知识图谱和传统的在线协作学习方法更为显著和积极。本研究加深了我们对群体认知及其复杂相互作用的认识,为改进在线协作学习提供了一种新的方法。
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引用次数: 0
Does Using Virtual Reality to Enhance Students' Presentation Skills Work? The Role of Feedback and Presence 利用虚拟现实提高学生的演讲技巧是否有效?反馈和在场的作用
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-18 DOI: 10.1111/jcal.70097
Roberta Di Palma, Simon Beausaert, Dominik Mahr, Jonas Heller, Tim Hilken

Background

Despite the recognised potential of Virtual Reality (VR) in education, the role of VR in enhancing presentation skills remains uncertain. Mixed findings, coupled with low adoption rates in educational settings, highlight the need to investigate how current VR applications are designed to facilitate effective learning outcomes for students.

Objectives

Grounded in constructivist and situated learning theories, which emphasise learning through active engagement and real-world contexts, this study examines how specific VR design features, namely, feedback mechanisms (feedback awareness and feedback usefulness) and presence types (social and spatial presence), relate to student motivation and performance in presentations.

Methods

In a one-group pre-test-post-test field study, 285 university students participated in 30-min individual VR training sessions focused on presentation skills refinement. Using structural equation modelling, this study assessed the relationships between feedback and presence elements with student motivation and performance outcomes.

Results and Conclusions

Analysis revealed that feedback awareness and social presence were positively associated with students' motivation to refine their presentation skills. Effective feedback mechanisms, particularly those that enhance feedback awareness and usefulness, were crucial for skill transfer, while increased social presence was associated with improved academic performance in the classroom. Conversely, spatial presence was unexpectedly negatively related to both motivation and performance, suggesting that how VR creates spatial elements may influence learning outcomes. By examining the nuances of these VR features, this study offers valuable insights for software developers and educators aiming to improve university students' presentation skills through VR training applications.

尽管虚拟现实(VR)在教育中的潜力得到了认可,但VR在提高演讲技巧方面的作用仍不确定。调查结果好坏参半,再加上教育环境中的采用率较低,突显出有必要调查当前的VR应用程序是如何设计的,以促进学生有效的学习成果。本研究以建构主义和情境学习理论为基础,强调通过积极参与和现实世界的背景来学习,研究了具体的VR设计特征,即反馈机制(反馈意识和反馈有用性)和存在类型(社会和空间存在)与学生在演讲中的动机和表现之间的关系。方法采用一组前测后测的实地研究方法,285名大学生参加了30分钟的个人VR训练课程,重点是提高演讲技巧。本研究采用结构方程模型,评估了反馈和在场因素与学生动机和成绩结果之间的关系。结果与结论分析表明,反馈意识和社会存在与学生改进演讲技巧的动机呈正相关。有效的反馈机制,特别是那些增强反馈意识和有用性的机制,对技能转移至关重要,而增加的社交存在与课堂上学习成绩的提高有关。相反,空间存在与动机和表现出乎意料地呈负相关,这表明VR如何创造空间元素可能会影响学习结果。通过研究这些VR功能的细微差别,本研究为旨在通过VR培训应用提高大学生演讲技能的软件开发人员和教育工作者提供了有价值的见解。
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引用次数: 0
Seventh-Grade Students' Views Regarding Enriched Algebra Instruction (EAI) Supported by Technology and Manipulatives 七年级学生对技术与教具支持下的丰富代数教学的看法
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-14 DOI: 10.1111/jcal.70100
Osman Birgin, Kayhan Demirören

Background

Previous research has shown that students often struggle to understand algebraic expressions and solve equations, and that traditional instructional approaches may not be sufficient to address these challenges. While the use of technology and physical manipulatives independently has been shown to support students' conceptual understanding in algebra, limited research has examined their combined use—particularly the integration of dynamic mathematics software and manipulatives—within the context of algebra instruction.

Objectives

This study aims to explore seventh-grade students' perceptions of an enriched algebra instruction (EAI) approach that integrates dynamic mathematics software and physical manipulatives to support and enhance their learning experiences.

Methods

A qualitative case study was conducted with 30 Turkish seventh-grade students (aged 12–13). The EAI approach integrated technological tools, concrete materials, collaborative group work, and classroom discussions. Data were collected through a survey comprising 22 items rated on a 5-point Likert-type scale and four open-ended questions, as well as through classroom observations. Quantitative data were analysed using descriptive statistics, while qualitative data were subjected to thematic content analysis.

Results and Conclusion

Most students reported that the use of EAI, which integrates dynamic software and manipulatives, enhanced their active engagement in classroom activities, enabled them to conduct multiple experiments and observations, and facilitated visual interaction with the content. They also indicated that EAI helped them explore relationships within algebraic expressions, which they perceived as contributing to the development of their algebraic thinking and conceptual understanding.

先前的研究表明,学生经常难以理解代数表达式和解方程,而传统的教学方法可能不足以解决这些挑战。虽然单独使用技术和物理教具已被证明可以支持学生对代数的概念理解,但有限的研究已经检查了它们在代数教学背景下的组合使用-特别是动态数学软件和教具的集成。目的本研究旨在探讨七年级学生对将动态数学软件和物理教具相结合的丰富代数教学方法的看法,以支持和增强他们的学习体验。方法对30名土耳其7年级学生(12-13岁)进行定性个案研究。EAI方法整合了技术工具、具体材料、合作小组工作和课堂讨论。数据是通过一项调查收集的,该调查包括22个项目(李克特5分制)和四个开放式问题,以及课堂观察。定量数据采用描述性统计进行分析,定性数据采用专题内容分析。结果与结论大多数学生报告说,使用集成了动态软件和教具的EAI,提高了他们对课堂活动的积极参与,使他们能够进行多种实验和观察,并促进了与内容的视觉交互。他们还表示,EAI帮助他们探索代数表达式中的关系,他们认为这有助于他们代数思维和概念理解的发展。
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引用次数: 0
A Learner-Centred Exploration of Teachers' Solution Pathways in K-12 Programming-Based Mathematical Problem-Solving 以学习者为中心的K-12基于规划的数学问题的教师解决途径探索
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-14 DOI: 10.1111/jcal.70102
Huiyan Ye, Biyao Liang, Oi-Lam Ng

Background

Empirical studies have revealed students' development of computational thinking (CT) and mathematical thinking (MT) during programming-based mathematical problem-solving, highlighting specific CT concepts or practices that serve as learning goals or outcomes. However, implementing programming-based mathematics instruction requires teachers to have sufficient knowledge about learners' thinking processes in such a context, while very little is known about multifaceted solution development from a learner-centred perspective.

Objectives

Viewing CT and MT as processes that go beyond specific skills or concepts, we conducted a qualitative study to investigate how participants develop computational solutions to mathematical problems and construct meaningful understandings of these solutions.

Methods

We adopted an interpretive approach to participants' solution pathways to reveal their diverse thinking processes underlying solution development. A constant comparative analysis approach was undertaken to guide the data analysis.

Results and Conclusions

We identified multiple solution pathways in developing programming-based mathematical solutions (PMS) and characterised four significant pathways comprising seven distinct sub-situations: (1) transition between personal MT and invalid PMS, (2) evolution from invalid PMS to valid PMS, (3) construction from non-meaningful PMS to meaningful PMS and (4) revision from suboptimal PMS to optimal PMS. The findings contribute to a deeper understanding of problem solvers' learning in programming-based mathematical problem-solving and offer implications for theory and practice in programming-rich mathematics education.

经验研究揭示了学生在基于编程的数学问题解决过程中计算思维(CT)和数学思维(MT)的发展,突出了作为学习目标或结果的特定CT概念或实践。然而,实施基于编程的数学教学需要教师对学习者在这种背景下的思维过程有足够的了解,而从以学习者为中心的角度来看,对多方面的解决方案开发知之甚少。将CT和MT视为超越特定技能或概念的过程,我们进行了一项定性研究,以调查参与者如何开发数学问题的计算解决方案并构建对这些解决方案的有意义的理解。方法通过对参与者解决方案路径的解释,揭示他们在解决方案开发过程中的不同思维过程。采用了不断比较分析的方法来指导数据分析。结果与结论我们在基于规划的数学解(PMS)的开发过程中发现了多种解路径,并描述了四个重要的解路径,包括七个不同的子情形:(1)从个人MT到无效PMS的过渡;(2)从无效PMS到有效PMS的演变;(3)从无意义PMS到有意义PMS的构建;(4)从次优PMS到最优PMS的修正。这些发现有助于更深入地理解问题解决者在基于编程的数学问题解决中的学习,并为编程丰富的数学教育的理论和实践提供启示。
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引用次数: 0
ChatGPT in Education: An Effect in Search of a Cause 教育中的聊天:寻找原因的结果
IF 4.6 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Pub Date : 2025-08-12 DOI: 10.1111/jcal.70105
J. Weidlich, D. Gašević, H. Drachsler, P. Kirschner

Background

As researchers rush to investigate the potential of AI tools like ChatGPT to enhance learning, well-documented pitfalls threaten the validity of this emerging research. Issues of media comparison research, where the confounding of instructional methods and technological affordances is unrecognised, may render effects uninterpretable.

Objectives

Using a recent meta-analysis by Deng et al. (Computers & Education, 227, 105224) as an example, we revisit key insights from the media/methods debate to highlight recurring conceptual challenges in ChatGPT efficacy studies.

Methods

This conceptual article contrasts nascent ChatGPT research with the more established literature on Intelligent Tutoring Systems to identify three non-negotiable considerations for interpretable effects: (1) descriptions of the precise nature of the experimental treatment and (2) the activities of the control group, as well as (3) outcome measures as valid indicators of learning. To provide some initial evidence, we audited a subset of primary experiments included in Deng et al.'s meta-analysis, demonstrating that only a small minority of studies satisfied all three non-negotiable considerations.

Results and Conclusions

Loosely defined treatments, mismatched or opaque controls, and outcome measures with unclear links to durable learning obscure causal claims of this emerging literature. Observed gains cannot, at this time, be confidently attributed to ChatGPT, and meta-analytics effect sizes may over- or understate its benefits. Progress, we argue, will require rigorous designs, transparent reporting, and a critical stance toward “fast science.”

随着研究人员急于研究像ChatGPT这样的人工智能工具在增强学习方面的潜力,有充分记录的陷阱威胁着这一新兴研究的有效性。媒体比较研究的问题是,教学方法和技术支持的混淆没有被认识到,可能导致无法解释的影响。利用Deng等人最近的一项荟萃分析(Computers &;以教育,227,105224)为例,我们重新审视媒体/方法辩论的关键见解,以突出ChatGPT功效研究中反复出现的概念挑战。这篇概念性的文章将新生的ChatGPT研究与更成熟的智能辅导系统文献进行了对比,以确定三个不可协商的因素来解释效果:(1)实验治疗的精确性质描述;(2)对照组的活动;以及(3)作为学习有效指标的结果测量。为了提供一些初步证据,我们审核了Deng等人荟萃分析中包含的一组主要实验,表明只有少数研究满足所有三个不可协商的考虑因素。结果和结论定义松散的治疗,不匹配或不透明的对照,以及与持久学习不明确联系的结果测量模糊了这一新兴文献的因果关系。目前,观察到的收益不能自信地归因于ChatGPT,而元分析的效应大小可能高估或低估了它的好处。我们认为,进步需要严格的设计、透明的报告和对“快速科学”的批判立场。
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引用次数: 0
期刊
Journal of Computer Assisted Learning
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