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Exploring EFL Learners’ Integration and Perceptions of ChatGPT's Text Revisions: A Three-Stage Writing Task Study 探索 EFL 学习者对 ChatGPT 文本修订的整合与感知:三阶段写作任务研究
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-11-06 DOI: 10.1109/TLT.2024.3491864
Lifang Bai;Yijia Wei
ChatGPT can promptly reformulate a text and improve its quality in content and form while preserving the original meaning. Yet, little is known about how learners respond to such reformulations. Here, we employed a three-stage writing task (composing-comparison-rewriting) to investigate how learners notice, integrate, and perceive ChatGPT's reformulations as feedback in English as a foreign language (EFL) classroom context. We collected learners’ written notes made during the comparison of their original texts and the reformulations, categorizing them based on the language-related type of noticing (vocabulary, discourse, and form) and quality of noticing (depth of processing: low, intermediate, and high). We also analyzed the instances of reformulations integrated into learners’ rewriting and their answers to a questionnaire. The results showed that: 1) the reformulations directed learners’ attention to the gaps in their original writing, especially in word choice, and prompted them to integrate ChatGPT-generated changes in their rewriting; 2) the number of instances integrated into the rewriting was directly related to the quantity, type, and quality of noticing in the comparison stage; and 3) learners generally appreciated the pedagogical value of ChatGPT in EFL writing, particularly during the revision stage, although they believe occasionally ChatGPT might misinterpret their intentions. The study suggests that ChatGPT's reformulations should be complemented with peer and teacher feedback to create a comprehensive and personalized learning environment.
ChatGPT 可以及时重新表述文本,并在保留原意的前提下提高文本内容和形式的质量。然而,人们对学习者如何应对这种重新表述却知之甚少。在这里,我们采用了一个三阶段的写作任务(写作-比较-改写)来研究在英语作为外语(EFL)的课堂环境中,学习者是如何注意、整合和感知 ChatGPT 的改写作为反馈的。我们收集了学习者在比较原文和改写时所作的书面记录,并根据语言相关的注意类型(词汇、话语和形式)和注意质量(处理深度:低、中、高)对其进行了分类。我们还分析了学习者改写中的改写实例以及他们对问卷的回答。结果表明1)改写引导学习者关注原写作中的不足,尤其是选词方面的不足,并促使他们在改写中融入 ChatGPT 生成的修改;2)融入改写的实例数量与比较阶段注意到的数量、类型和质量直接相关;3)学习者普遍赞赏 ChatGPT 在 EFL 写作中的教学价值,尤其是在修改阶段,尽管他们认为 ChatGPT 偶尔会误解他们的意图。本研究建议,ChatGPT 的改写应与同伴和教师的反馈相辅相成,以创造一个全面和个性化的学习环境。
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引用次数: 0
Measuring the Effectiveness of Learning Economic Principles in a Sustainable Entrepreneurship Game-Based Setting: A Bootstrapping Approach 衡量在可持续创业游戏环境下学习经济原则的有效性:一种自举方法
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-11-05 DOI: 10.1109/TLT.2024.3492073
Clemens Drieschner;Ferdinand Xiong;Florian Bajraktari;Matthias C. Utesch;Jörg Weking;Helmut Krcmar
The growing demand for sustainable products and services has led to the emergence of a range of entrepreneurial opportunities for innovative business solutions. These new opportunities require novel entrepreneurial skills to design, grow, and maintain sustainable businesses. However, existing educational games do not address the specific skills needed for sustainable entrepreneurship. This work introduces an interactive business game that enables learning in an engaging and practical way to prepare learners to become the entrepreneurs of tomorrow. Our business game is intended to increase learners’ self-assessed skills and self-confidence by at least one point on the five-point Likert scale. The game is embedded into a didactic framework accompanied by a lecture and discussion part where learners manage their bike rental business and self-reflect on their decisions. The game scenario allows the players to guide their business through three growth stages: survival, growth, and expansion. In this study, 151 high school students participated in the evaluation across all stages. They assessed their knowledge in a pretest and a posttest and judged the developed game on its ease of use. The learners’ sustainable entrepreneurship knowledge and skills improved significantly. This study thus confirms the mixed approach as a viable teaching tool for this area of expertise. Furthermore, a holistic didactic framework with an introduction to the game and subsequent debriefing contributes to the success of the business game too. A sign test and bootstrapping with confidence intervals constituted a simple means of statistically quantifying the learners’ improvement.
对可持续产品和服务日益增长的需求,带来了一系列创新商业解决方案的创业机会。这些新机遇需要新颖的创业技能来设计、发展和维持可持续企业。然而,现有的教育游戏并未涉及可持续创业所需的具体技能。本作品介绍了一种互动式商业游戏,它能以引人入胜和实用的方式促进学习,让学习者为成为未来的企业家做好准备。我们的商业游戏旨在将学习者的自我评估技能和自信心在李克特五点量表上至少提高一个点。游戏被嵌入到一个教学框架中,伴随着讲座和讨论部分,学习者在游戏中管理自己的自行车租赁业务,并对自己的决策进行自我反思。游戏场景允许玩家引导自己的企业经历三个成长阶段:生存、成长和扩张。在这项研究中,151 名高中生参与了所有阶段的评估。他们在前测和后测中评估了自己的知识,并根据游戏的易用性对开发的游戏进行了评判。学习者的可持续创业知识和技能有了显著提高。因此,这项研究证实了混合教学法是这一专业领域的可行教学工具。此外,包含游戏介绍和后续汇报的整体教学框架也为商业游戏的成功做出了贡献。符号检验和带置信区间的引导法是对学习者的进步进行统计量化的简单方法。
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引用次数: 0
Adaptive Question–Answer Generation With Difficulty Control Using Item Response Theory and Pretrained Transformer Models 利用项目反应理论和预训练变压器模型生成具有难度控制的自适应问题-答案
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-11-04 DOI: 10.1109/TLT.2024.3491801
Yuto Tomikawa;Ayaka Suzuki;Masaki Uto
The automatic generation of reading comprehension questions, referred to as question generation (QG), is attracting attention in the field of education. To achieve efficient educational applications of QG methods, it is desirable to generate questions with difficulty levels that are appropriate for each learner's reading ability. Therefore, in recent years, several difficulty-controllable QG methods have been proposed. However, conventional methods generate only questions and cannot produce question–answer pairs. Furthermore, such methods ignore the relationship between question difficulty and learner ability, making it challenging to ascertain the appropriate difficulty levels for each learner. To address these issues, in this article, we propose a method for generating question–answer pairs based on difficulty, defined using a statistical model known as item response theory. The proposed difficulty-controllable generation is achieved by extending two pretrained transformer models: bidirectional encoder representations from transformers and text-to-text transfer transformer. In addition, because learners' abilities are generally not knowable in advance, we propose an adaptive QG framework that efficiently estimates the learners' abilities while generating and presenting questions with difficulty levels suitable for their abilities. Through experiments involving real data, we confirmed that the proposed method can generate question–answer pairs with difficulty levels that align with the learners' abilities while efficiently estimating their abilities.
自动生成阅读理解问题,即问题生成(QG),在教育领域备受关注。为了实现 QG 方法在教育领域的高效应用,最好能生成难度适合每个学习者阅读能力的问题。因此,近年来提出了几种难度可控的 QG 方法。然而,传统方法只能生成问题,无法生成问答对。此外,这些方法还忽视了问题难度与学习者能力之间的关系,因此要为每个学习者确定适当的难度具有挑战性。为了解决这些问题,我们在本文中提出了一种根据难度生成问题-答案对的方法,该方法使用一种称为 "项目反应理论"(item response theory)的统计模型来定义。所提出的难度可控生成方法是通过扩展两个预先训练好的转换器模型来实现的:转换器的双向编码器表征和文本到文本的转移转换器。此外,由于学习者的能力通常无法事先知晓,我们提出了一种自适应 QG 框架,它能有效地估计学习者的能力,同时生成和呈现难度适合学习者能力的问题。通过使用真实数据进行实验,我们证实所提出的方法可以生成难度与学习者能力相符的问答对,同时有效地估计学习者的能力。
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引用次数: 0
Empowering Instructors: Augmented Reality Authoring Toolkit for Aviation Weather Education 增强教员能力:航空气象教育的增强现实创作工具包
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-10-30 DOI: 10.1109/TLT.2024.3486630
Jiwon Kim;Jack Miller;Kexin Wang;Michael C. Dorneich;Eliot Winer;Lori J. Brown
This study introduces an augmented reality (AR) authoring tool tailored for flight instructors without technical expertise. While AR offers potential in aviation weather education and instructors desire to use it in the classroom, they face challenges due to limited digital proficiency and complexity of authoring tools. Many existing AR authoring tools prioritize technical aspects over user experience. To address these challenges, a no-programming-required AR authoring tool was developed based on instructor-informed requirements, such as incorporating features of flight waypoints and weather phenomena. A total of 41 participants tested the tool by crafting three AR learning modules. After using the tool, there was a significant increase in participants’ confidence in AR content creation (+30%), AR authoring process (+51%), and interactive AR development (+50%). In addition, there was a significant decrease in their concerns about technical complexity (–19%), mental effort (–30%), and time consumption (–30%). Participants rated the incorporated functions highly preferable and indicated the tool has high usability. Participants completed the most challenging task quickly and with a low cognitive load. The findings demonstrate the tool's effectiveness in enabling participants to competently and efficiently author AR content, reducing technical concerns. Such tools can facilitate the integration of AR technology into the classroom, offering students improved access to interactive 3-D visualizations of dynamic subjects, such as aviation weather, which require students to mentally visualize weather conditions and understand their manifestations.
本研究介绍了一种为没有专业技术知识的飞行教员量身定制的增强现实(AR)创作工具。虽然增强现实技术在航空气象教育方面具有潜力,教员们也希望在课堂上使用这种技术,但由于数字技术能力有限和制作工具的复杂性,他们面临着挑战。许多现有的 AR 制作工具都将技术方面的问题置于用户体验之上。为了应对这些挑战,我们根据教员提出的要求,开发了一种无需编程的 AR 创作工具,例如将飞行航点和天气现象的特征融入其中。共有 41 名学员通过制作三个 AR 学习模块对该工具进行了测试。使用该工具后,学员在 AR 内容创建(+30%)、AR 创作过程(+51%)和交互式 AR 开发(+50%)方面的信心有了显著提高。此外,他们对技术复杂性(-19%)、脑力劳动(-30%)和时间消耗(-30%)的担忧也明显减少。参与者对纳入的功能给予了很高的评价,并表示该工具具有很高的可用性。参与者以较低的认知负荷快速完成了最具挑战性的任务。研究结果表明,该工具能够有效地帮助参与者胜任并高效地编写 AR 内容,减少了技术方面的顾虑。这种工具可以促进 AR 技术与课堂的整合,为学生提供更好的机会,使他们能够获得动态主题的交互式三维可视化内容,例如航空天气,这需要学生在头脑中将天气状况可视化并理解其表现形式。
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引用次数: 0
The Impact of Artificial General Intelligence-Assisted Project-Based Learning on Students’ Higher Order Thinking and Self-Efficacy 人工通用智能辅助项目式学习对学生高阶思维和自我效能的影响
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-10-30 DOI: 10.1109/TLT.2024.3488086
Ruxin Zheng;Huifen Xu;Minjuan Wang;Jijian Lu
This study investigates the impact of artificial general intelligence (AGI)-assisted project-based learning (PBL) on students’ higher order thinking and self-efficacy. Based on input from 17 experts, four key roles of AGI in supporting PBL were identified: information retrieval, information processing, information generation, and feedback evaluation. An educational experiment was then conducted with 198 eighth-grade students from two middle schools in China, using a pretest and posttest design. The students were divided into three groups: Experimental Group A (AGI-assisted PBL), Control Group B (PBL without AGI assistance), and Control Group C (traditional teaching methods). A scale was administered to assess students’ higher order thinking and self-efficacy before and after the experiment. In addition, semistructured interviews were conducted with 12 students from Experimental Group A to gather qualitative data on their perceptions of AGI-assisted PBL. The results indicated that students in Experimental Group A had significantly higher scores in higher order thinking and self-efficacy compared to those in Control Groups B and C, demonstrating the positive impact of AGI in supporting PBL learning.
本研究调查了人工智能(AGI)辅助项目式学习(PBL)对学生高阶思维和自我效能的影响。根据 17 位专家的意见,确定了 AGI 在支持项目式学习中的四个关键作用:信息检索、信息处理、信息生成和反馈评估。随后,对来自中国两所中学的 198 名八年级学生进行了教育实验,实验采用前测和后测设计。学生被分为三组:实验组 A(AGI 辅助的 PBL)、对照组 B(无 AGI 辅助的 PBL)和对照组 C(传统教学方法)。实验前后对学生的高阶思维和自我效能进行了量表评估。此外,还对实验组 A 的 12 名学生进行了半结构式访谈,以收集他们对 AGI 辅助 PBL 的看法的定性数据。结果表明,与对照组 B 和 C 的学生相比,实验组 A 的学生在高阶思维和自我效能感方面的得分明显更高,这证明了 AGI 在支持 PBL 学习方面的积极影响。
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引用次数: 0
Embedding Test Questions in Educational Mobile Virtual Reality: A Study on Hospital Hygiene Procedures 在教育移动虚拟现实中嵌入测试问题:医院卫生程序研究
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-10-29 DOI: 10.1109/TLT.2024.3487898
Fabio Buttussi;Luca Chittaro
Educational virtual environments (EVEs) can enable effective learning experiences on various devices, including smartphones, using nonimmersive virtual reality (VR). To this purpose, researchers and educators should identify the most appropriate pedagogical techniques, not restarting from scratch but exploring which traditional e-learning and VR techniques can be effectively combined or adapted to EVEs. In this direction, this article explores if test questions, a typical e-learning technique, can be effectively employed in an EVE through a careful well-blended design. We also consider the active performance of procedures, a typical VR technique, to evaluate if test questions can be synergic with it or if they can instead break presence and be detrimental to learning. The between-subject study we describe involved 120 participants in four conditions: with/without test questions and active/passive procedure performance. The EVE was run on a smartphone, using nonimmersive VR, and taught hand hygiene procedures for infectious disease prevention. Results showed that introducing test questions did not break presence but surprisingly increased it, especially when combined with active procedure performance. Participants’ self-efficacy increased after using the EVE regardless of condition, and the different conditions did not significantly change engagement. Moreover, participants who had answered test questions in the EVE showed a reduction in the number of omitted steps in an assessment of learning transfer. Finally, test questions increased participants’ satisfaction. Overall, these greater-than-expected benefits support the adoption of the proposed test question design in EVEs based on nonimmersive VR.
教育虚拟环境(EVE)可以利用非沉浸式虚拟现实技术(VR),在包括智能手机在内的各种设备上实现有效的学习体验。为此,研究人员和教育工作者应找出最合适的教学技术,而不是从头开始,而是探索哪些传统的电子学习和 VR 技术可以有效地结合或适用于 EVE。在这个方向上,本文探讨了试题作为一种典型的电子学习技术,能否通过精心的混合设计在电子游戏中得到有效应用。我们还考虑了程序(一种典型的虚拟现实技术)的积极表现,以评估测试问题是否能与之协同增效,或者它们是否会打破存在感并不利于学习。在我们描述的主体间研究中,120 名参与者在四种条件下进行了学习:有/无测试问题和主动/被动程序表现。EVE在智能手机上运行,使用非沉浸式VR,教授预防传染病的手部卫生程序。结果表明,引入测试问题并没有破坏存在感,反而出人意料地提高了存在感,尤其是在与主动程序表现相结合时。无论在什么条件下,参与者在使用 EVE 后的自我效能感都有所提高,而不同的条件并没有显著改变参与度。此外,在学习迁移评估中,在电子学习环境中回答过测试问题的参与者减少了遗漏步骤的数量。最后,测试问题提高了参与者的满意度。总之,这些超出预期的益处支持在基于非沉浸式 VR 的 EVE 中采用建议的测试问题设计。
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引用次数: 0
Comparing the Effects of Instructor Manual Feedback and ChatGPT Intelligent Feedback on Collaborative Programming in China's Higher Education 比较教师手动反馈与 ChatGPT 智能反馈对中国高校协作编程的影响
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-10-25 DOI: 10.1109/TLT.2024.3486749
Fan Ouyang;Mingyue Guo;Ning Zhang;Xianping Bai;Pengcheng Jiao
Artificial general intelligence (AGI) has gained increasing global attention as the field of large language models undergoes rapid development. Due to its human-like cognitive abilities, the AGI system has great potential to help instructors provide detailed, comprehensive, and individualized feedback to students throughout the educational process. ChatGPT, as a preliminary version of the AGI system, has the potential to improve programming education. In programming, students often have difficulties in writing codes and debugging errors, whereas ChatGPT can provide intelligent feedback to support students’ programming learning process. This research implemented intelligent feedback generated by ChatGPT to facilitate collaborative programming among student groups and further compared the effects of ChatGPT with instructors’ manual feedback on programming. This research employed a variety of learning analytics methods to analyze students’ computer programming performances, cognitive and regulation discourses, and programming behaviors. Results indicated that no substantial differences were identified in students’ programming knowledge acquisition and group-level programming product quality when both instructor manual feedback and ChatGPT intelligent feedback were provided. ChatGPT intelligent feedback facilitated students’ regulation-oriented collaborative programming, while instructor manual feedback facilitated cognition-oriented collaborative discussions during programming. Compared to the instructor manual feedback, ChatGPT intelligent feedback was perceived by students as having more obvious strengths as well as weaknesses. Drawing from the results, this research offered pedagogical and analytical insights to enhance the integration of ChatGPT into programming education at the higher education context. This research also provided a new perspective on facilitating collaborative learning experiences among students, instructors, and the AGI system.
随着大型语言模型领域的快速发展,人工通用智能(AGI)越来越受到全球的关注。由于具有类似人类的认知能力,AGI 系统在帮助教师在整个教学过程中为学生提供详细、全面和个性化的反馈方面具有巨大潜力。ChatGPT 作为 AGI 系统的初级版本,具有改善编程教育的潜力。在编程过程中,学生往往在编写代码和调试错误时遇到困难,而 ChatGPT 可以提供智能反馈,支持学生的编程学习过程。本研究利用 ChatGPT 生成的智能反馈来促进学生小组之间的协作编程,并进一步比较了 ChatGPT 与教师手动反馈对编程的影响。本研究采用了多种学习分析方法来分析学生的计算机编程表现、认知和调节话语以及编程行为。结果表明,在教师手动反馈和 ChatGPT 智能反馈的情况下,学生在编程知识掌握和小组编程产品质量方面没有发现实质性差异。ChatGPT 智能反馈促进了学生以规则为导向的协作编程,而教师手动反馈则促进了编程过程中以认知为导向的协作讨论。与教师手动反馈相比,学生认为 ChatGPT 智能反馈有更明显的优点和缺点。根据研究结果,本研究为加强 ChatGPT 与高等教育编程教育的整合提供了教学和分析见解。这项研究还为促进学生、教师和 AGI 系统之间的协作学习体验提供了新的视角。
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引用次数: 0
Guest Editorial Intelligence Augmentation: The Owl of Athena 特约编辑 智能增强:雅典娜的猫头鹰
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-10-21 DOI: 10.1109/TLT.2024.3456072
Chris Dede
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引用次数: 0
Designing Learning Technologies: Assessing Attention in Children With Autism Through a Single Case Study 设计学习技术:通过单一案例研究评估自闭症儿童的注意力
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-10-07 DOI: 10.1109/TLT.2024.3475741
Yussy Chinchay;César A. Collazos;Javier Gomez;Germán Montoro
This research focuses on the assessment of attention to identify the design needs for optimized learning technologies for children with autism. Within a single case study incorporating a multiple-baseline design involving baseline, intervention, and postintervention phases, we developed an application enabling personalized attention strategies. These strategies were assessed for their efficacy in enhancing attentional abilities during digital learning tasks. Data analysis of children's interaction experience, support requirements, task completion time, and attentional patterns was conducted using a tablet-based application. The findings contribute to a comprehensive understanding of how children with autism engage with digital learning activities and underscore the significance of personalized attention strategies. Key interaction design principles were identified to address attention-related challenges and promote engagement in the learning experience. This study advances the development of inclusive digital learning environments for children on the autism spectrum by leveraging attention assessment.
这项研究的重点是评估注意力,以确定自闭症儿童优化学习技术的设计需求。在一项包含基线、干预和干预后三个阶段的多基线设计的单一案例研究中,我们开发了一款支持个性化注意力策略的应用程序。我们对这些策略在数字学习任务中提高注意力能力的效果进行了评估。我们使用基于平板电脑的应用程序对儿童的互动体验、支持要求、任务完成时间和注意力模式进行了数据分析。研究结果有助于全面了解自闭症儿童如何参与数字学习活动,并强调了个性化注意力策略的重要性。研究还确定了关键的交互设计原则,以应对与注意力相关的挑战并促进学习体验的参与度。这项研究通过利用注意力评估,推动了自闭症谱系儿童包容性数字学习环境的发展。
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引用次数: 0
Investigating the Efficacy of ChatGPT-3.5 for Tutoring in Chinese Elementary Education Settings 研究 ChatGPT-3.5 在中国小学教育环境中的辅导效果
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-19 DOI: 10.1109/TLT.2024.3464560
Yu Bai;Jun Li;Jun Shen;Liang Zhao
The potential of artificial intelligence (AI) in transforming education has received considerable attention. This study aims to explore the potential of large language models (LLMs) in assisting students with studying and passing standardized exams, while many people think it is a hype situation. Using primary education as an example, this research investigates whether ChatGPT-3.5 can achieve satisfactory performance on the Chinese Primary School Exams and whether it can be used as a teaching aid or tutor. We designed an experimental framework and constructed a benchmark that comprises 4800 questions collected from 48 tasks in Chinese elementary education settings. Through automatic and manual evaluations, we observed that ChatGPT-3.5’s pass rate was below the required level of accuracy for most tasks, and the correctness of ChatGPT-3.5’s answer interpretation was unsatisfactory. These results revealed a discrepancy between the findings and our initial expectations. However, the comparative experiments between ChatGPT-3.5 and ChatGPT-4 indicated significant improvements in model performance, demonstrating the potential of using LLMs as a teaching aid. This article also investigates the use of the trans-prompting strategy to reduce the impact of language bias and enhance question understanding. We present a comparison of the models' performance and the improvement under the trans-lingual problem decomposition prompting mechanism. Finally, we discuss the challenges associated with the appropriate application of AI-driven language models, along with future directions and limitations in the field of AI for education.
人工智能(AI)在改变教育方面的潜力已受到广泛关注。本研究旨在探索大型语言模型(LLM)在帮助学生学习和通过标准化考试方面的潜力,而很多人认为这是一种炒作情况。本研究以小学教育为例,探讨 ChatGPT-3.5 是否能在中国小学考试中取得令人满意的成绩,以及是否可用作教学辅助工具或辅导工具。我们设计了一个实验框架,并构建了一个基准,其中包括从中国小学教育环境中的 48 个任务中收集的 4800 道题。通过自动和人工评估,我们发现 ChatGPT-3.5 的通过率在大多数任务中都低于要求的准确率,而且 ChatGPT-3.5 的答案解释正确率也不尽如人意。这些结果表明,实验结果与我们最初的预期存在差异。不过,ChatGPT-3.5 和 ChatGPT-4 的对比实验表明,模型性能有了显著提高,这证明了使用 LLM 作为教学辅助工具的潜力。本文还研究了如何使用反向提示策略来减少语言偏差的影响并增强对问题的理解。我们比较了模型的性能以及在跨语言问题分解提示机制下的改进情况。最后,我们讨论了适当应用人工智能驱动的语言模型所面临的挑战,以及人工智能教育领域的未来发展方向和局限性。
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