Journal of Computer Assisted Learning最新文献_第6页

Unlocking Augmented Reality Learning Design Based on Evidence From Empirical Cognitive Load Studies—A Systematic Literature Review 基于实证认知负荷研究证据的增强现实学习设计--系统性文献综述

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-12-02 DOI: 10.1111/jcal.13095

Jana Gonnermann-Müller, Jule M. Krüger

Background

Despite the numerous positive effects of augmented reality (AR) on learning, previous research has shown ambiguous results regarding the cognitive demand on the learner arising from, for example, the overlay of virtual elements or novel interaction techniques. At the same time, the number of evidence-based guidelines on designing AR is limited or focuses on global effects, primarily relying on media comparison studies, whose validity is criticised.

Objective

To guide the meaningful design of learning and training settings, this paper systematically reviews empirical research on AR design and synthesises the findings to develop evidence-based recommendations for designing AR systems considering cognitive load.

Methods

We conducted a systematic literature review, initially screening 810 distinct papers and ultimately analysing findings from 27 publications, which report on 29 distinct experimental studies. This selection was based on rigorously defined inclusion and exclusion criteria, adhering to the PRISMA guidelines.

Results and Conclusion

The central value of this paper is the aggregation of existing evidence from empirical studies, resulting in 15 recommendations for AR design based on six design dimensions: Spatiality-related, Interaction-related, Contextuality-related, Content-related, Guidance-related and Display Selection. Additionally, with three points for future research, this systematic literature review, first, stresses the need for more empirical evidence and value-added studies. Second, learner characteristics that might influence cognitive load in AR-based learning should be examined. Third, it advocates for the inclusion of measurements beyond the NASA-TLX, and including more physiological measurements (e.g., eye-tracking, EEG) to enhance the applicability of the results for learning and training situations.

尽管增强现实（AR）对学习产生了许多积极的影响，但以往的研究在虚拟元素的叠加或新的交互技术对学习者产生的认知需求方面显示出模糊的结果。与此同时，基于证据的AR设计指南数量有限或侧重于全球影响，主要依赖于媒体比较研究，其有效性受到批评。为了指导有意义的学习和培训环境设计，本文系统地回顾了AR设计的实证研究，并综合研究结果，为考虑认知负荷的AR系统设计提供循证建议。我们进行了系统的文献综述，最初筛选了810篇不同的论文，最终分析了27篇出版物的发现，这些出版物报告了29项不同的实验研究。这一选择是基于严格定义的纳入和排除标准，坚持PRISMA指南。本文的核心价值在于对现有实证研究的证据进行汇总，得出了基于六个设计维度的15条AR设计建议：空间相关、交互相关、情境相关、内容相关、引导相关和显示选择。此外，对于未来的研究，本系统的文献综述有三点，首先，强调需要更多的经验证据和增值研究。其次，应该研究可能影响基于ar学习认知负荷的学习者特征。第三，它主张在NASA-TLX之外纳入更多的测量，包括更多的生理测量（如眼动追踪、脑电图），以增强结果对学习和训练情况的适用性。

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引用次数: 0

Learning Programming With Augmented Reality-Based Editor: A Dynamic Code Visualisation Approach 基于增强现实的编辑器学习编程：一种动态代码可视化方法

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-28 DOI: 10.1111/jcal.13093

Merve Aydin, Ünal Çakiroğlu

Background

Students experience higher-order thinking skills by finding ways to solve the problem, debugging errors while applying the solution, and testing the solution in programming. However, the inability to create schemas that will characterise programming structures is one of the difficulties during this process.

Objectives

This study aimed to create an augmented reality-based programming editor and evaluate its contributions to learning programming. Text-based programming codes developed by the students on the editor were instantly visualised through a traffic metaphor in dynamic visualisation via augmented reality. The findings of this study highlight the significance of a novel usage of augmented reality in shaping cognitive processes during the programming learning process.

Methods

An exploratory case study was adopted in the study. Participants voluntarily selected 15 students in the same secondary school's 4th and 5th grades. The data to determine the programming performances were collected via a programming performance test and analysed with the rubric created by the authors. Interviews and screen recordings were employed to determine the factors that had a role in the programming learning process.

Results and Conclusions

The results indicated that teaching programming using the augmented reality-based editor has positively contributed to learning programming. The editor's scenario, animation, and error display features incorporated with an authentic dynamic visualisation were remarkable in this contribution. The editor also contributed to reducing students' efforts to create schemas for programming by bringing the context closer to reality throughout the programming process.

学生通过寻找解决问题的方法，在应用解决方案时调试错误，以及在编程中测试解决方案来体验高阶思维技能。然而，无法创建能够描述编程结构的模式是这个过程中的困难之一。本研究旨在创造一个基于扩增实境的程式设计编辑器，并评估其对程式设计学习的贡献。学生们在编辑器上开发的基于文本的编程代码，通过增强现实的动态可视化，通过交通隐喻立即可视化。本研究的发现强调了增强现实在编程学习过程中塑造认知过程的新用途的重要性。方法采用探索性案例研究方法。参与者自愿选择了同一所中学四年级和五年级的15名学生。通过编程性能测试收集了用于确定编程性能的数据，并用作者创建的标准进行了分析。采用访谈和屏幕录音来确定在编程学习过程中起作用的因素。结果与结论使用基于增强现实的编辑器进行编程教学对编程学习有积极的促进作用。编辑器的场景、动画和错误显示功能与真实的动态可视化相结合，在这方面的贡献是显著的。该编辑器还通过在整个编程过程中使上下文更接近现实，减少了学生为编程创建模式的工作量。

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引用次数: 0

The Effect of AI-Based Systems on Mathematics Achievement in Rural Context: A Quantitative Study 基于人工智能的系统对农村地区数学成绩的影响：定量研究

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-19 DOI: 10.1111/jcal.13098

Rashmi Khazanchi, Daniele Di Mitri, Hendrik Drachsler

<div> <section> <h3> Background</h3> <p>Despite educational advances, poor mathematics achievement persists among K-12 students, particularly in rural areas with limited resources and skilled teachers. Artificial Intelligence (AI) based systems have increasingly been adopted to support the diverse learning needs of students and have been shown to enhance mathematics achievement through personalized learning experiences by adapting to student's needs. Existing studies have documented the positive impact of AI-based systems on mathematics achievement. However, there is a lack of research that has studied AI-based systems on students' mathematics achievement and engagement in rural settings. The present study addresses the existing literature gap by focusing on the AI-based Edmentum Exact Path, analyzing its effectiveness in enhancing mathematics achievement and engagement among 8th-grade students in rural schools in the Southern United States. By examining both cognitive and affective engagement, along with students' mathematics achievement, this research explores the role of AI-based systems in student learning.</p> </section> <section> <h3> Objective</h3> <p>This study aims to explore the effectiveness of Edmentum Exact Path, an AI-based system, in improving 8th-grade students' mathematics achievement and affective and cognitive engagement in the Southern United States.</p> </section> <section> <h3> Methods</h3> <p>This study utilized a quasi-experimental design involving 78 students from socioeconomically disadvantaged backgrounds, comparing those receiving supplemental Edmentum Exact Path-led instruction and traditional teacher-led methods to a control group receiving only the teacher-led instructions. Mathematics achievement was measured through pre-tests and post-tests, while student engagement was assessed using the 5-point Student Engagement Instrument (SEI). Statistical analysis was performed using <i>t</i>-tests and ANOVA.</p> </section> <section> <h3> Results and Conclusions</h3> <p>The findings revealed statistically significant improvements in mathematics achievement for both the experimental and control groups. However, the group using teacher-led instruction showed a statistically significant improvement in affective engagement, while no statistically significant differences were observed in cognitive engagement between groups.</p> </section> <section> <h3> Implications</h3> <p>The findings suggest that integrating AI-based systems lik

背景尽管教育取得了进步，但 K-12 学生的数学成绩仍然很差，尤其是在资源和师资有限的农村地区。基于人工智能（AI）的系统已被越来越多地采用，以支持学生的不同学习需求，并通过适应学生需求的个性化学习体验来提高数学成绩。现有研究记录了人工智能系统对数学成绩的积极影响。然而，目前还缺乏关于人工智能系统对农村学生数学成绩和参与度的研究。本研究关注基于人工智能的 Edmentum Exact Path，分析了它在提高美国南部农村学校八年级学生数学成绩和参与度方面的有效性，从而弥补了现有的文献空白。通过考察认知和情感参与以及学生的数学成绩，本研究探讨了基于人工智能的系统在学生学习中的作用。目的本研究旨在探索 Edmentum Exact Path（一种基于人工智能的系统）在提高美国南部八年级学生数学成绩以及情感和认知参与方面的有效性。方法本研究采用准实验设计，涉及 78 名来自社会经济弱势背景的学生，将接受以 Edmentum Exact Path 为主导的补充教学和传统教师指导方法的学生与仅接受教师指导的对照组学生进行比较。数学成绩通过前测和后测进行测量，而学生参与度则通过 5 点学生参与度问卷（SEI）进行评估。统计分析采用 t 检验和方差分析。结果与结论研究结果显示，实验组和对照组的数学成绩均有显著提高。然而，使用教师指导的实验组在情感参与度方面有明显的统计意义上的提高，而在认知参与度方面，实验组和对照组之间没有统计意义上的显著差异。启示研究结果表明，整合 Edmentum Exact Path 等人工智能系统可提高农村地区学生的数学情感参与度。然而，对认知参与的影响仍不清楚，这表明需要进一步研究。这些结果支持了整合人工智能系统以提高农村地区数学成绩的潜力。

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引用次数: 0

Eye Movement Modelling Examples as Cues to Guide Attention and Improve Learning in Short or Long Animations 以眼动模型示例为线索，引导注意力并提高长短动画的学习效果

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-19 DOI: 10.1111/jcal.13094

Fuxing Wang, Xiaoxue Leng, Ziyi Kuang, Tingting Zhao

Background

Both eye movement modelling examples (EMMEs) and cues guide attention and improve learning in multimedia learning environments. EMME can act as a special form of cue. However, no studies have directly examined whether EMME would be superior to visual cues.

Objective

The study was to investigate whether there were advantages of EMME over cues on visual attention, learning outcomes and subjective perception in a multimedia environment.

Method

In Experiment 1, 67 college students were randomly assigned to the EMME group, cue group and control group and learned from animations explaining the synaptic transmission. In Experiment 2, we replicated Experiment 1 using longer learning material. Seventy-one college students were randomly assigned to three groups (EMME, cue and control) and learned from animations explaining the process of cell division.

Results and Conclusions

In Experiment 1, results indicated both EMMEs and cues guide attention and facilitate learning. Regarding learning outcomes and subjective perception, learners did not benefit more from EMMEs than cues. Eye movement indicators showed that EMMEs were better than cues. In Experiment 2, results were consistent with Experiment 1.

Implications

This study is the first to compare EMMEs and cues. We found that EMMEs and cues were equivalent in producing effects on learning outcomes and subjective perception. EMMEs were superior to cues in guiding attention and conveying strategies, as indicated by eye movements. Both theoretical and practical implications could be drawn.

背景在多媒体学习环境中，眼动模型（EMMEs）和提示都能引导注意力，提高学习效果。眼动模型可以作为一种特殊形式的线索。然而，目前还没有研究直接探讨眼动模型是否优于视觉线索。本研究的目的是探讨在多媒体环境中，EMME 在视觉注意力、学习效果和主观感知方面是否比视觉线索更有优势。方法在实验 1 中，67 名大学生被随机分配到 EMME 组、提示组和对照组，通过讲解突触传递的动画进行学习。在实验 2 中，我们用更长的学习材料重复了实验 1。71 名大学生被随机分配到三个组（EMME 组、提示组和对照组），通过讲解细胞分裂过程的动画进行学习。结果与结论在实验 1 中，结果表明 EMME 和提示都能引导注意力并促进学习。在学习结果和主观感受方面，学习者从电子学习媒体中获得的益处并不比从提示中获得的益处多。眼动指标显示，眼动监测仪比提示更好。实验 2 的结果与实验 1 一致。意义本研究是首次对眼动监测器和提示进行比较。我们发现，在对学习结果和主观感知产生影响方面，眼动监测仪和线索具有同等作用。在引导注意力和传达策略方面，从眼球运动的角度来看，教育监测媒体优于线索。这既有理论意义，也有实践意义。

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引用次数: 0

Uncovering adults' problem-solving patterns from process data with hidden Markov model and network analysis 利用隐马尔可夫模型和网络分析从过程数据中发现成人解决问题的模式

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-14 DOI: 10.1111/jcal.13089

Xiaoxiao Liu, Okan Bulut, Ying Cui, Yizhu Gao

Background

Process data captured by computer-based assessments provide valuable insight into respondents' cognitive processes during problem-solving tasks. Although previous studies have utilized process data to analyse behavioural patterns or strategies in problem-solving tasks, the connection between latent cognitive states and their theoretical interpretation in problem solving remains unclear.

Objectives

This research aims to investigate the connections between similar hidden response states and unfold respondents' transition paths in problem-solving processes. Analysing process data from the 2012 United States Programme for the International Assessment of Adult Competencies (PIAAC), this study seeks to discern patterns in problem solving among participants.

Methods

The hidden Markov model was first used to uncover the hidden states based on a sequence of observed actions. Next, Gaussian graphical network analysis was employed to analyse the relationships between hidden response states.

Results and Conclusions

Results indicated that correct responders had simpler, clearer state relationships, while incorrect responders displayed more complex connections. Respondents who solved the tasks correctly had clearer thoughts about the problem-solving process, whereas incorrect respondents struggled to understand the problem and failed to figure out solutions. Cognitive state changes during problem solving also varied between groups. The correct groups showed cohesive, logical transitions, in contrast to the emerged isolated, erratic patterns of the incorrect groups.

基于计算机的评估获取的过程数据为调查对象在解决问题任务期间的认知过程提供了有价值的见解。虽然以前的研究利用过程数据来分析问题解决任务中的行为模式或策略，但潜在认知状态与其在问题解决中的理论解释之间的联系尚不清楚。目的探讨相似隐藏反应状态之间的联系，揭示被调查者在问题解决过程中的转换路径。本研究分析了2012年美国成人国际能力评估项目（PIAAC）的过程数据，旨在辨别参与者解决问题的模式。方法首先利用隐马尔可夫模型，根据观察到的动作序列揭示隐藏状态。其次，采用高斯图网络分析方法分析了隐藏响应状态之间的关系。结果与结论结果表明，正确应答者的状态关系较为简单、清晰，错误应答者的状态关系较为复杂。正确解决任务的受访者对解决问题的过程有更清晰的想法，而不正确的受访者则难以理解问题，无法找到解决方案。在解决问题的过程中，认知状态的变化在不同的组之间也有所不同。正确的组呈现出连贯的、逻辑的过渡，而不正确的组则呈现出孤立的、不稳定的模式。

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引用次数: 0

The impact of frequency and stakes of formative assessment on student achievement in higher education: A learning analytics study 高等教育中形成性评估的频率和利害关系对学生成绩的影响：一项学习分析研究

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-13 DOI: 10.1111/jcal.13087

Okan Bulut, Guher Gorgun, Seyma Nur Yildirim-Erbasli

Background

Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress. Optional assessments may encourage voluntary engagement, potentially leading to a more genuine reflection of student understanding. Also, frequent assessments provide continuous opportunities for feedback and adjustment, which can keep students actively engaged in the learning process.

Objectives

This study aims to investigate two crucial facets of formative assessments: frequency and the level of stakes involved (mandatory vs. optional). We examine how modifying the frequency of formative assessments affects students' course performance. Additionally, we evaluate the impact of mandatory versus optional formative assessments on students' course performance in higher education.

Methods

The sample of this study consisted of undergraduate students (n = 336) enrolled in three sections of a large asynchronous course at a Canadian university. We extracted features associated with online formative assessments (e.g., the number of attempts and average scores) from the learning management system. Next, we used these features to predict students' performance in summative assessments (two midterms and a final exam).

Results and Conclusions

Our findings indicated that increasing the frequency of online formative assessments did not consistently improve student performance. Also, participation frequency in online formative assessments seemed to vary depending on assessment stakes (i.e., optional vs. mandatory). We recommend that instructors examine what conditions can maximize the contribution of formative assessments to students' academic achievement before building predictive models.

研究表明，形成性评估的操作方式在塑造学生参与形成性评估的过程中起着至关重要的作用，从而影响其预测学业成绩的有效性。强制性评估可以确保学生的持续参与，从而更好地跟踪学习进度。可选的评估可能会鼓励自愿参与，可能会更真实地反映学生的理解。此外，频繁的评估为反馈和调整提供了持续的机会，这可以使学生积极地参与到学习过程中。本研究旨在探讨形成性评估的两个关键方面：频率和涉及的利害关系水平（强制性与可选性）。我们研究如何修改形成性评估的频率影响学生的课程表现。此外，我们评估了强制性和可选性形成性评估对学生在高等教育中的课程表现的影响。方法本研究的样本包括参加加拿大一所大学大型异步课程的三个部分的本科生（n = 336）。我们从学习管理系统中提取了与在线形成性评估相关的特征（例如，尝试次数和平均分数）。接下来，我们使用这些特征来预测学生在总结性评估中的表现（两次期中考试和一次期末考试）。结果和结论我们的研究结果表明，增加在线形成性评估的频率并不能持续提高学生的表现。此外，参与在线形成性评估的频率似乎因评估风险而异（即，可选与强制性）。我们建议教师在建立预测模型之前，检查哪些条件可以最大限度地发挥形成性评估对学生学业成绩的贡献。

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引用次数: 0

A systematic review and meta-analysis of AI-enabled assessment in language learning: Design, implementation, and effectiveness 人工智能辅助语言学习评估的系统回顾和荟萃分析：设计、实施和效果

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-12 DOI: 10.1111/jcal.13064

Angxuan Chen, Yuyue Zhang, Jiyou Jia, Min Liang, Yingying Cha, Cher Ping Lim

Background

Language assessment plays a pivotal role in language education, serving as a bridge between students' understanding and educators' instructional approaches. Recently, advancements in Artificial Intelligence (AI) technologies have introduced transformative possibilities for automating and personalising language assessments.

Objectives

This article aims to explore the design and implementation of AI-enabled assessment tools in language education, filling the research gaps regarding the impact of assessment type, intervention duration, education level, and first language learner/second language learner (L1/L2) on the effectiveness of AI-enabled assessment tools in enhancing students' language learning outcome.

Methods

This study conducted a systematic review and meta-analysis to examine 25 empirical studies from January 2012 to March 2024 from six databases (including EBSCO, ProQuest, Scopus, Web of Science, ACM Digital Library and CNKI).

Results

The predominant design in AI-driven assessment tools is the structural AI architecture. These tools are most frequently deployed in classroom settings for upper primary students within a short duration. A subsequent meta-analysis showed a medium overall effect size (Hedges's g = 0.390, p < 0.001) for the application of AI-enabled assessment tools in enhancing students' language learning, underscoring their significant impact on language learning outcomes. This evidence robustly supports the practical utility of these tools in educational contexts.

Conclusions

The analysis of several moderator variables (i.e., assessment type, intervention duration, educational level and L1/L2 learners) and potential impacts on language learning performance indicates that AI-enabled assessment could be more useful in language education with a proper implementation design. Future research could investigate diverse instructional designs for integrating AI-based assessment tools in language education.

背景语言评估在语言教育中起着举足轻重的作用，是学生理解能力和教育者教学方法之间的桥梁。最近，人工智能（AI）技术的进步为语言评估的自动化和个性化带来了变革性的可能性。本文旨在探讨人工智能评估工具在语言教育中的设计和实施，填补有关评估类型、干预时间、教育水平和第一语言学习者/第二语言学习者（L1/L2）对人工智能评估工具提高学生语言学习效果的影响的研究空白。方法本研究采用系统综述和荟萃分析的方法，从六个数据库（包括 EBSCO、ProQuest、Scopus、Web of Science、ACM 数字图书馆和 CNKI）中选取了 2012 年 1 月至 2024 年 3 月期间的 25 项实证研究。结果人工智能驱动的评估工具的主要设计是结构性人工智能架构。这些工具最常用于小学高年级学生的课堂教学，使用时间较短。随后的荟萃分析表明，人工智能评估工具在提高学生语言学习方面的应用具有中等的总体效应（Hedges's g = 0.390，p < 0.001），强调了其对语言学习成果的显著影响。这些证据有力地证明了这些工具在教育环境中的实用性。结论对几个调节变量（即评估类型、干预持续时间、教育水平和 L1/L2 学习者）以及对语言学习成绩的潜在影响进行的分析表明，如果实施设计得当，人工智能评估在语言教育中可能会更有用。未来的研究可以探讨在语言教育中整合基于人工智能的评估工具的各种教学设计。

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引用次数: 0

Mining teacher informal online learning networks: Community commitment in unstructured learning environments 挖掘教师非正式在线学习网络：非结构化学习环境中的社区承诺

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-11 DOI: 10.1111/jcal.13090

Hanxiang Du, Gaoxia Zhu, Wanli Xing

Background

Social media provides new opportunities for teachers to learn, communicate and develop professional relationships. It has been proved to be a valid and helpful resource for teachers' professional learning purposes.

Objectives

While previous studies pursued questions like how participants feel, how to support interaction and why participants remain committed, we asked a more fundamental question: what is the structure of a massive informal online professional learning network and what dynamics can we expect regarding participants' commitment?

Methods

This work presents an empirical study of massive informal online professional networks to investigate the dynamics of learning communities and participants' commitment over time. We employed social network analysis and data mining techniques on a longitudinal data set of more than 400,000 tweets published with the hashtag “#edchat.”

Results and Conclusions

We found that around 30% of participants remained committed to the informal learning community over time. Meanwhile, as more and more people committed to the online learning community, participants tended to form smaller communities where the internal connection was stronger.

Takeaways

In informal online learning environments, participants can form stable connections. The 30% threshold can be used to measure massive informal online learning networks in terms of commitment or persistence.

社交媒体为教师提供了学习、交流和发展专业关系的新机会。事实证明，它是教师专业学习的有效和有益的资源。虽然之前的研究追求的是参与者的感受、如何支持互动以及参与者为何保持忠诚等问题，但我们提出了一个更基本的问题：大规模非正式在线专业学习网络的结构是什么？我们可以期待参与者的承诺有什么样的动态？方法本研究对大规模非正式在线专业网络进行实证研究，以调查学习社区和参与者承诺随时间的动态变化。我们采用了社交网络分析和数据挖掘技术，对40多万条以“#edchat”为标签发布的推文进行纵向数据集分析。结果和结论我们发现，随着时间的推移，大约30%的参与者仍然致力于非正式学习社区。同时，随着越来越多的人致力于在线学习社区，参与者倾向于形成更小的社区，内部联系更强。在非正式的在线学习环境中，参与者可以形成稳定的联系。30%的阈值可以用来衡量大规模的非正式在线学习网络的承诺或持久性。

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引用次数: 0

The effects of embedded quizzes on self-regulated processes and learning performance during a multimedia lesson 多媒体课程中嵌入测验对自我调节过程和学习表现的影响

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-11 DOI: 10.1111/jcal.13083

Camille Tordet, Jonathan Fernandez, Eric Jamet

Background

Previous research has demonstrated that quizzing can improve self-regulation processes and learning performances. However, it remains unclear whether quizzes in multimedia material bring similar benefits, and whether interindividual differences such as working memory capacity (WMC) modulate quizzing effects.

Aims

This study aimed to examine the effects of embedded quizzes (multiple quizzes within the learning sequence) with feedback during a multimedia learning sequence on self-regulated processing (monitoring and control) and learning performances on repeated (material already tested) and new (untested) questions, and possible WMC moderation on performances.

Sample and Methods

Participants were 59 students who learned a multimedia neuroscience course module in either a no-quiz or embedded quizzes condition. With regard to self-regulated processing, control was assessed with eye-tracking measures (fixation durations and transitions between texts and illustrations), and monitoring by comparing self-reported judgements of learning with actual performances (calibration). At the end, students' WMC was measured, and learning performances were assessed with repeated and new questions.

Results

Quizzing improved learning performances on repeated and new questions, and enhanced monitoring (better calibration). Students with low WMC benefited more from quizzing for new questions than those with high WMC. However, contrary to our hypothesis, the embedded quizzes group allocated less time to the learning than the no-quiz group.

Conclusions

Embedded quizzes are relevant tools to help students recalibrate their monitoring process and foster more effective self-regulated learning. Results confirm that the use of quizzes can be recommended to improve the learning of multimedia material, especially among students with low WMC.

背景以往的研究表明，测验可以改善自我调节过程和学习成绩。然而，多媒体材料中的测验是否会带来类似的益处，以及工作记忆能力（WMC）等个体间差异是否会调节测验效果，目前仍不清楚。研究目的本研究旨在探讨在多媒体学习序列中进行带反馈的嵌入式测验（在学习序列中进行多次测验）对自我调节加工（监测和控制）、重复（已测试过的材料）和新（未测试过的）问题的学习成绩的影响，以及工作记忆能力对学习成绩可能产生的调节作用。样本和方法参与者为59名学生，他们在无测验或嵌入测验的条件下学习了多媒体神经科学课程模块。在自我调节处理方面，通过眼动跟踪测量（定格持续时间以及文本和插图之间的转换）来评估控制情况，通过比较自我报告的学习判断和实际表现（校准）来评估监测情况。最后，对学生的 WMC 进行测量，并通过重复问题和新问题对学习表现进行评估。结果测验提高了重复问题和新问题的学习成绩，并加强了监测（更好的校准）。与 WMC 高的学生相比，WMC 低的学生从新问题测验中获益更多。然而，与我们的假设相反，嵌入式测验组分配给学习的时间少于无测验组。结论嵌入式测验是帮助学生重新调整其监控过程并促进更有效的自我调节学习的相关工具。结果证实，可以建议使用测验来提高多媒体材料的学习效果，尤其是对于学习能力差的学生。

{"title":"The effects of embedded quizzes on self-regulated processes and learning performance during a multimedia lesson","authors":"Camille Tordet, Jonathan Fernandez, Eric Jamet","doi":"10.1111/jcal.13083","DOIUrl":"https://doi.org/10.1111/jcal.13083","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Previous research has demonstrated that quizzing can improve self-regulation processes and learning performances. However, it remains unclear whether quizzes in multimedia material bring similar benefits, and whether interindividual differences such as working memory capacity (WMC) modulate quizzing effects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>This study aimed to examine the effects of embedded quizzes (multiple quizzes within the learning sequence) with feedback during a multimedia learning sequence on self-regulated processing (monitoring and control) and learning performances on repeated (material already tested) and new (untested) questions, and possible WMC moderation on performances.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Sample and Methods</h3>\u0000 \u0000 <p>Participants were 59 students who learned a multimedia neuroscience course module in either a no-quiz or embedded quizzes condition. With regard to self-regulated processing, control was assessed with eye-tracking measures (fixation durations and transitions between texts and illustrations), and monitoring by comparing self-reported judgements of learning with actual performances (calibration). At the end, students' WMC was measured, and learning performances were assessed with repeated and new questions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Quizzing improved learning performances on repeated and new questions, and enhanced monitoring (better calibration). Students with low WMC benefited more from quizzing for new questions than those with high WMC. However, contrary to our hypothesis, the embedded quizzes group allocated less time to the learning than the no-quiz group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Embedded quizzes are relevant tools to help students recalibrate their monitoring process and foster more effective self-regulated learning. Results confirm that the use of quizzes can be recommended to improve the learning of multimedia material, especially among students with low WMC.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860848","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

Impacts of interacting with an AI chatbot on preservice teachers' responsive teaching skills in math education 与AI聊天机器人互动对数学教育中职前教师响应式教学技能的影响

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning

Pub Date : 2024-11-08 DOI: 10.1111/jcal.13091

Dabae Lee, Taekwon Son, Sheunghyun Yeo

Background

Artificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real-time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain.

Objectives

The primary objective of this study is to examine whether interaction with a responsive AI-based chatbot that acts as a virtual student improves pre-service teachers' noticing abilities. The second objective is to compare how the presence or absence of chatbot responses affects changes in PSTs' questioning practices. Finally, the third objective is to investigate how the experience of interacting with the responsive virtual student affects PSTs' perceptions of the effectiveness of their questioning, their satisfaction with the interactions, and their confidence about interacting with a real student compared to the non-responsive chatbot.

Methods

A randomised controlled pre- and post-test design was used with 50 PSTs. PSTs' noticing, interaction with the chatbot, and post-survey data were collected, and a t-test was conducted to examine significant differences by group.

Results and Conclusion

In the experimental group, the virtual student responded to PSTs' questions, while in the control group, she did not. Notable differences were observed in their questioning practices.

Takeaways

Overall, AI-based chatbots hold promise for enhancing PSTs' responsive teaching skills. Future research is needed to examine the long-term impact of responsive chatbot use on PSTs' noticing skills.

人工智能（AI）技术为职前教师（pst）提供了独特的能力，使他们能够使用自然语言进行真实和实时的互动。然而，人工智能技术对pst响应式教学技能的影响仍不确定。本研究的主要目的是研究与响应式人工智能聊天机器人（作为虚拟学生）的互动是否能提高职前教师的注意能力。第二个目标是比较聊天机器人反应的存在或不存在如何影响pst提问实践的变化。最后，第三个目标是调查与响应性虚拟学生互动的体验如何影响pst对提问有效性的看法，他们对互动的满意度，以及他们对与真实学生互动的信心，而不是与无响应的聊天机器人。方法采用随机对照试验前后设计，共50例pst。收集pst的注意、与聊天机器人的互动以及调查后的数据，并进行t检验以检验组间的显著差异。结果与结论实验组虚拟学生回答了PSTs的问题，而对照组虚拟学生没有回答PSTs的问题。他们的提问方式存在显著差异。总的来说，基于人工智能的聊天机器人有望提高pst的响应性教学技能。未来的研究需要检验响应式聊天机器人对pst注意技能的长期影响。

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引用次数: 0