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A Survey of Knowledge Tracing: Models, Variants, and Applications 知识追踪调查:模型、变体和应用
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-08 DOI: 10.1109/TLT.2024.3383325
Shuanghong Shen;Qi Liu;Zhenya Huang;Yonghe Zheng;Minghao Yin;Minjuan Wang;Enhong Chen
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In recent years, a substantial number of studies have concentrated on this rapidly growing field, significantly contributing to its advancements. In this survey, we will conduct a thorough investigation of these progressions. First, we present three types of fundamental KT models with distinct technical routes. Subsequently, we review extensive variants of the fundamental KT models that consider more stringent learning assumptions. Moreover, the development of KT cannot be separated from its applications, so we present typical KT applications in various scenarios. To facilitate the work of researchers and practitioners in this field, we have developed two open-source algorithm libraries: EduData that enables the downloading and preprocessing of KT-related datasets, and EduKTM that provides an extensible and unified implementation of existing mainstream KT models. Finally, we discuss potential directions for future research in this rapidly growing field. We hope that the current survey will assist both researchers and practitioners in fostering the development of KT, thereby benefiting a broader range of students.
现代在线教育有能力通过自动分析大量学生行为数据来提供智能教育服务。知识追踪(KT)是学生行为数据分析的基本任务之一,旨在监测学生在解决问题过程中不断发展的知识状态。近年来,大量研究都集中在这一快速发展的领域,极大地推动了该领域的进步。在本调查中,我们将对这些进展进行深入研究。首先,我们将介绍三种具有不同技术路线的基本 KT 模型。随后,我们回顾了基本 KT 模型的大量变体,这些变体考虑了更严格的学习假设。此外,KT 的发展离不开其应用,因此我们介绍了 KT 在各种场景中的典型应用。为了方便该领域的研究人员和从业人员开展工作,我们开发了两个开源算法库:EduData 可以下载和预处理 KT 相关数据集,而 EduKTM 则为现有的主流 KT 模型提供了可扩展的统一实现。最后,我们讨论了这一快速发展领域未来研究的潜在方向。我们希望当前的调查能够帮助研究人员和从业人员促进知识共享的发展,从而使更多的学生受益。
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引用次数: 0
Determinants of Teacher Attitudes and Innovative Use of Wearable Technology 教师对可穿戴技术的态度和创新使用的决定因素
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-08 DOI: 10.1109/TLT.2024.3386464
Hashem A. Almusawi;Christopher M. Durugbo
Digital technologies, such as wearables, offer immense potential for active and enhanced interactive, collaborative, and immersive learning. Wearable technologies are digital devices that can be worn on or near the human body as accessories or clothing. Interest and innovativeness in the educational use of such technologies depend on teacher attitudes, and a significant challenge for education and technology research is examining the factors that relate to these attitudes. The aim of this study is to examine the determinants of teacher attitudes toward wearables and their influence on personal innovativeness in the use of wearable technology. The study involves a cross-sectional survey of 346 physical education teachers. Using partial least squared structural equation modeling, the study provides new analytical insights into affectiveness, teacher beliefs, and perceived mattering, as a triad of determining factors for teacher attitudes and personal innovativeness in wearable technology use. Results reflect the need for institutional initiatives to foster positive attitudes and perceptions toward wearables and for teacher upskilling through training and development in innovative use of digital technologies.
可穿戴设备等数字技术为主动和强化互动、协作和沉浸式学习提供了巨大的潜力。可穿戴技术是可以作为配件或服装佩戴在人体上或人体附近的数字设备。在教育中使用此类技术的兴趣和创新性取决于教师的态度,而教育和技术研究的一个重大挑战就是研究与这些态度相关的因素。本研究旨在探讨教师对可穿戴设备态度的决定因素及其对个人使用可穿戴技术的创新性的影响。研究对 346 名体育教师进行了横截面调查。研究采用偏最小二乘法结构方程模型,对情感、教师信念和感知重要性作为教师态度和个人在可穿戴技术使用中的创新性的三重决定因素提供了新的分析见解。研究结果表明,有必要采取制度性措施来培养教师对可穿戴设备的积极态度和看法,并通过培训和发展来提高教师在创新使用数字技术方面的能力。
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引用次数: 0
ChatGPT for Learning HCI Techniques: A Case Study on Interviews for Personas 学习人机交互技术的 ChatGPT:角色访谈案例研究
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-08 DOI: 10.1109/TLT.2024.3386095
Jose Barambones;Cristian Moral;Angélica de Antonio;Ricardo Imbert;Loïc Martínez-Normand;Elena Villalba-Mora
Before interacting with real users, developers must be proficient in human–computer interaction (HCI) so as not to exhaust user patience and availability. For that, substantial training and practice are required, but it is costly to create a variety of high-quality HCI training materials. In this context, chat generative pretrained transformer (ChatGPT) and other chatbots based on large language models (LLMs) offer an opportunity to generate training materials of acceptable quality without foregoing specific human characteristics present in real-world scenarios. Personas is a user-centered design method that encompasses fictitious but believable user archetypes to help designers understand and empathize with their target audience during product design. We conducted an exploratory study on the Personas technique, addressing the validity and believability of interviews designed by HCI trainers and answered by ChatGPT-simulated users, which can be used as training material for persona creation. Specifically, we employed ChatGPT to respond to interviews designed by user experience (UX) experts. Two groups, HCI professors and professionals, then evaluated the validity of the generated materials considering quality, usefulness, UX, and ethics. The results show that both groups rated the interviews as believable and helpful for Personas training. However, some concerns about response repetition and low response variability suggested the need for further research on improved prompt design in order to generate more diverse and well-developed responses. The findings of this study provide insight into how HCI trainers can use ChatGPT to help their students master persona creation skills before working with real users in real-world scenarios for the first time.
在与真实用户互动之前,开发人员必须精通人机交互(HCI),以免耗尽用户的耐心和可用性。为此,需要大量的培训和练习,但制作各种高质量的人机交互培训材料成本高昂。在这种情况下,聊天生成预训练转换器(ChatGPT)和其他基于大型语言模型(LLMs)的聊天机器人提供了一个机会,既能生成质量可接受的培训材料,又不会放弃现实世界场景中存在的特定人类特征。角色是一种以用户为中心的设计方法,它包含虚构但可信的用户原型,帮助设计师在产品设计过程中了解目标受众并与之产生共鸣。我们对 Personas 技术进行了一项探索性研究,探讨了由人机交互培训师设计、由 ChatGPT 模拟用户回答的访谈的有效性和可信度,这些访谈可用作创建角色的培训材料。具体来说,我们使用 ChatGPT 来回答用户体验(UX)专家设计的访谈。然后,人机交互教授和专业人士组成的两组人分别从质量、实用性、用户体验和道德等方面对生成材料的有效性进行了评估。结果显示,两组人都认为访谈是可信的,对 Personas 培训有帮助。然而,一些人对回答重复和回答可变性低表示担忧,这表明有必要进一步研究如何改进提示设计,以生成更多样、更完善的回答。本研究的结果为人机交互培训师如何使用 ChatGPT 帮助学生掌握角色创建技能提供了启示,然后再与真实用户在真实场景中进行首次合作。
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引用次数: 0
3D-Printing Virtual Simulation Lab 3d 打印虚拟仿真实验室
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-08 DOI: 10.1109/TLT.2024.3384556
Ishant Singhal;Guru Ratan Satsangee;Lakshya Bhardwaj;Gaurang S. Sharma;Anand Swarup Chandrakar;Hritav Gupta;Gargi Malik;Bobby Tyagi;Ankit Sahai;Rahul Swarup Sharma
3D-printing (3DP) is a rapidly evolving sector and is advancing at an unmatched pace. Integrating digital-based approaches to disseminate knowledge within institutional curricula is crucial for mainstreaming knowledge. This work explores the development of a virtual lab (VL) for additive manufacturing (AM), using an interactive VL simulator. The VL's experiments encompass anatomy, assembly, techniques, preprocessing, and postprocessing modules on AM. The aim of this dedicated AM VL is to facilitate digital education on 3DP among educational institutions. A case study compares the efficacy of VL to physical experimentation. Two groups of 30 students each provided feedback before and after conducting experiments in the physical laboratory and on the VL, respectively. The comparison elucidates how integrating the VL with traditional teaching pedagogy can be a progressive step in teaching AM in educational institutions. The teaching pedagogy approach is both cost-effective and time efficient. The developed VL offers unlimited access and availability for students to learn at their own pace. The design of the 3DP virtual simulation lab incorporates an inclusive align–act–assess approach, wherein each module includes related theory, aim, procedure, simulator interface, pretest, and posttest to align with this approach.
三维打印(3DP)是一个快速发展的行业,其发展速度无与伦比。在机构课程中整合基于数字的方法来传播知识对于知识主流化至关重要。这项工作利用交互式虚拟实验室模拟器,探索了增材制造(AM)虚拟实验室(VL)的开发。虚拟实验室的实验内容包括 AM 的解剖、装配、技术、预处理和后处理模块。该专用 AM VL 的目的是促进教育机构的 3DP 数字化教育。一项案例研究比较了 VL 与物理实验的功效。两组各 30 名学生分别在物理实验室和 VL 上进行实验前后提供了反馈意见。比较结果阐明了将 VL 与传统教学法相结合如何能成为教育机构 AM 教学的一个进步步骤。这种教学法既经济又省时。开发的虚拟实验室为学生提供了无限的访问和可用性,让他们按照自己的节奏学习。3DP 虚拟仿真实验室的设计采用了 "统一-行动-评估 "的方法,其中每个模块都包括相关理论、目的、程序、仿真器界面、前测和后测,以符合这一方法。
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引用次数: 0
Exploring Manifestations of Learners’ Self-Regulated Tactics and Strategies Across Blended Learning Courses 探索混合式学习课程中学习者自我调节策略的表现形式
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-05 DOI: 10.1109/TLT.2024.3385641
Esteban Villalobos;Mar Pérez-Sanagustín;Roger Azevedo;Cédric Sanza;Julien Broisin
Blended learning (BL) has become increasingly popular in higher education institutions. Despite its popularity and the advances in methodologies for the detection of learning tactics and strategies from trace data, little is known about how they apply to BL settings and, therefore, how students use them to plan, organize, monitor, and regulate their learning in these settings. To address this gap, we analyzed the manifestations of learning tactics and strategies of 267 students across three undergraduate-level BL courses with different course designs, instructional activities, and learning contexts. We employed a data-driven method that incorporates hidden Markov models to determine students’ learning tactics. Then, we employed optimal matching to identify the students’ strategies based on the sequences of tactics they deployed and how they relate to their self-reported self-regulated learning (SRL) skills. Our results indicate that students’ tactics and strategies varied significantly depending on the course design and learning context. Tactics with regard to the use of time management resources were common across courses. In contrast, tactics deployed when revisiting old material and interacting with an SRL support tool were course-specific. We identified strategies related to surface and deep learning and found that surface-level strategies manifested consistently across all courses. These findings contribute to a better understanding of student learning mechanisms in BL environments and have implications for instructional design and SRL support.
混合式学习(BL)在高等教育机构中越来越受欢迎。尽管混合式学习很受欢迎,而且从跟踪数据中检测学习策略和战术的方法也在不断进步,但人们对这些策略和战术如何应用于混合式学习环境,以及学生如何利用它们来计划、组织、监控和调节他们在混合式学习环境中的学习却知之甚少。为了填补这一空白,我们分析了 267 名学生在三门本科水平的基础教育课程中的学习策略和战略表现,这些课程具有不同的课程设计、教学活动和学习情境。我们采用了一种数据驱动的方法,结合隐马尔可夫模型来确定学生的学习策略。然后,我们采用最优匹配法,根据学生采用的策略序列以及这些策略与他们自我报告的自我调节学习(SRL)技能之间的关系来确定学生的策略。我们的研究结果表明,学生的策略和战略因课程设计和学习环境的不同而有很大差异。使用时间管理资源的策略在各门课程中都很常见。相比之下,在重温旧教材和与 SRL 支持工具互动时使用的策略则因课程而异。我们确定了与表层和深层学习相关的策略,并发现表层策略在所有课程中都有一致的表现。这些研究结果有助于更好地理解学生在基础学习环境中的学习机制,并对教学设计和自学能力支持具有重要意义。
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引用次数: 0
Challenges and Opportunities for the Web 3.0 Metaverse Turn in Education 教育领域 Web 3.0 Metaverse 转型的挑战与机遇
IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-05 DOI: 10.1109/TLT.2024.3385505
Shujia Fan;Brian Yecies;Zeyang Ivy Zhou;Jun Shen
The metaverse, along with its various Web 3.0 subdomains, represents a ground-breaking extension of both the physical and digital worlds. In this emerging landscape, the real and virtual worlds are integrating in a way that allows for seamless interactions, creating an immersive experience. This integration has significant implications for diverse fields, particularly in reshaping both online and traditional education methods. By analyzing 417 comprehensive white papers released in 2022 and 2023 from leading consulting firms and think tanks, and incorporating insights from academic articles, we have extracted key information about how metaverse technologies are influencing education over time. Our investigation unveils the key impacts of metaverse technologies on the educational landscape, contributing to a more profound understanding of the transformative effects of the metaverse on the educational terrain in flux. Moreover, our study provides a holistic perspective on the advantages and disadvantages associated with metaverse education, offering in-depth insights into the challenges involved in seamlessly integrating the metaverse into educational practices. Furthermore, our research also highlights the challenges and opportunities presented by the metaverse and its impact on new educational paradigms.
元宇宙及其各种 Web 3.0 子域代表了物理世界和数字世界的突破性延伸。在这一新兴领域,现实世界和虚拟世界正在以一种无缝互动的方式融为一体,创造出一种身临其境的体验。这种融合对各个领域都有重大影响,尤其是在重塑在线教育和传统教育方法方面。通过分析领先咨询公司和智库在 2022 年和 2023 年发布的 417 份综合白皮书,并结合学术文章中的见解,我们提取了有关元虚拟技术如何随着时间的推移影响教育的关键信息。我们的调查揭示了元世界技术对教育领域的关键影响,有助于人们更深刻地理解元世界对不断变化的教育领域的变革性影响。此外,我们的研究还从整体角度探讨了与元数据教育相关的优势和劣势,深入揭示了将元数据无缝融入教育实践所面临的挑战。此外,我们的研究还强调了元海外带来的挑战和机遇及其对新教育范式的影响。
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引用次数: 0
Revolutionizing Word Clouds for Teaching and Learning With Generative Artificial Intelligence: Cases From China and Singapore 利用生成式人工智能革新词云教学:中国和新加坡的案例
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-04 DOI: 10.1109/TLT.2024.3385009
Elizabeth Koh;Lishan Zhang;Alwyn Vwen Yen Lee;Hongye Wang
Generative artificial intelligence (AI) has the potential to revolutionize teaching and learning applications. This article examines the word cloud, a toolkit often used to scaffold teaching and learning for reflection, critical thinking, and content learning. Addressing the issues in traditional word clouds, semantic word clouds have been developed but they are technically challenging to develop and still problematic. However, generative AI has the potential to develop efficient, accurate, creative, and accessible word clouds. Three different methods representing three major approaches of word cloud generation were developed, implemented, and user evaluated—traditional (baseline), semantic (natural language processing enhanced), and generative AI (generative pretrained transformer based)—in two different language contexts—Chinese (China case) and English (Singapore case). The findings of the study show the technical robustness of the methods, as well as provide key pedagogical insights from the user perspective of instructors of higher education courses in China and Singapore. Implications to the design of word clouds and their application in teaching and learning are discussed.
生成式人工智能(AI)有可能彻底改变教学应用。本文对词云进行了研究,词云是一种常用于为反思、批判性思维和内容学习提供教学支架的工具包。为了解决传统词云中存在的问题,人们开发了语义词云,但开发语义词云在技术上具有挑战性,而且仍然存在问题。然而,生成式人工智能有可能开发出高效、准确、有创意且易于使用的词云。在两种不同的语言环境中--中文(中国案例)和英文(新加坡案例)--开发、实施了代表词云生成三大方法的三种不同方法,并进行了用户评估--传统方法(基线)、语义方法(自然语言处理增强型)和生成式人工智能方法(基于生成式预训练转换器)。研究结果表明了这些方法在技术上的稳健性,并从中国和新加坡高等教育课程教师的用户角度提供了重要的教学见解。研究还讨论了词云设计及其在教学中应用的意义。
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引用次数: 0
Teaching Plan Generation and Evaluation With GPT-4: Unleashing the Potential of LLM in Instructional Design 利用 GPT-4 生成和评价教学计划:释放 LLM 在教学设计中的潜能
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-03 DOI: 10.1109/TLT.2024.3384765
Bihao Hu;Longwei Zheng;Jiayi Zhu;Lishan Ding;Yilei Wang;Xiaoqing Gu
This study explores and analyzes the specific performance of large language models (LLMs) in instructional design, aiming to unveil their potential strengths and possible weaknesses. Recently, the influence of LLMs has gradually increased in multiple fields, yet exploratory research on their application in education remains relatively scarce. In response to this situation, our research, grounded in pedagogical content knowledge theory, initially formulated an instructional design framework based on mathematical problem chains and corresponding prompt instructions. Subsequently, a comprehensive tool for assessing LLM's instructional design capabilities was developed. Utilizing Generative Pretrained Transformer 4, a high school mathematics teaching plan dataset was generated. Finally, the performance of LLMs in instructional design was evaluated. The evaluation results revealed that the teaching plans generated by LLMs excel in setting instructional objectives, identifying teaching priorities, organizing problem chains and teaching activities, articulating subject content, and selecting methods and strategies. Particularly commendable performance was noted in the modules of statistics and functions. However, there is room for improvement in aspects related to mathematical culture and interdisciplinary assessment, as well as in the geometry and algebra modules. Lastly, this study proposes initiatives, such as LLM prompt-based teacher training and the integration of mathematics-focused LLMs. These suggestions aim to advance personalized instructional design and professional development of teachers, offering educators new insights into the in-depth application of LLMs.
本研究探讨和分析了大语言模型(LLMs)在教学设计中的具体表现,旨在揭示其潜在的优势和可能的不足。近来,大型语言模型在多个领域的影响力逐渐增大,但有关其在教育领域应用的探索性研究仍然相对较少。针对这种情况,我们的研究以教学内容知识理论为基础,初步制定了一个基于数学问题链和相应提示指令的教学设计框架。随后,我们开发了一个用于评估 LLM 教学设计能力的综合工具。利用生成预训练变换器 4 生成了高中数学教案数据集。最后,对 LLM 在教学设计方面的表现进行了评估。评估结果显示,语文教师生成的教案在设定教学目标、确定教学重点、组织问题链和教学活动、阐明学科内容以及选择方法和策略方面表现出色。尤其值得称道的是统计和函数模块。然而,在数学文化和跨学科评估方面,以及在几何和代数单元中,仍有改进的余地。最后,本研究提出了一些倡议,如基于乐虎国际手机客户端提示的教师培训和以数学为重点的乐虎国际手机客户端整合。这些建议旨在推进个性化教学设计和教师专业发展,为教育工作者深入应用 LLM 提供新的见解。
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引用次数: 0
ADPS—A Prescreening Tool for Students With Dyslexia in Learning Traditional Chinese ADPS - 有阅读障碍学生学习繁体中文的预检工具
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-02 DOI: 10.1109/TLT.2024.3384290
Ka-Yan Fung;Kit-Yi Tang;Tze Leung Rick Lui;Kuen-Fung Sin;Lik-Hang Lee;Huamin Qu;Shenghui Song
Prescreening children for specific learning disabilities, e.g., dyslexia, is essential for effective intervention. With a quick and reliable prescreening result, special education coordinators (SENCOs) can provide students with early intervention and relieve their learning pressure. Unfortunately, due to the limited resources, many students in Hong Kong receive dyslexia assessments beyond the golden period, i.e., under the age of six. To this end, information technology could establish automatic prescreening tools to address this issue. However, dyslexia prescreening for children learning Chinese is challenging due to the lack of sound–script correlation in Chinese. In this article, an automatic dyslexia prescreening system (ADPS) is developed to provide a quick test to identify at-risk children. Through a two-stage approach, we first develop a gamified tool based on linguistic characteristics and then evaluate the result by a comparison study. Results from a pilot test on 30 students with dyslexia and 32 students without dyslexia indicate that the ADPS can effectively distinguish between two groups of students. Furthermore, the interactive design elements can motivate students to conduct the prescreening independently.
对儿童进行特殊学习障碍(如阅读障碍)预检对有效干预至关重要。有了快速可靠的预检结果,特殊教育协调员就可以为学生提供早期干预,减轻他们的学习压力。遗憾的是,由于资源有限,香港很多学生在接受读写困难评估时已过了黄金期,即六岁以下。为此,信息技术可以建立自动预检工具来解决这一问题。然而,由于中文缺乏音标相关性,为学习中文的儿童进行读写障碍预检具有挑战性。本文开发了一种自动读写困难预选系统(ADPS),为识别高危儿童提供快速测试。通过两个阶段的方法,我们首先开发了基于语言特点的游戏化工具,然后通过对比研究对结果进行评估。对 30 名有读写困难的学生和 32 名没有读写困难的学生进行的试点测试结果表明,ADPS 能有效区分两类学生。此外,交互式设计元素还能激励学生独立进行预检。
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引用次数: 0
ChatGPT for Educational Purposes: Investigating the Impact of Knowledge Management Factors on Student Satisfaction and Continuous Usage 用于教育目的的 ChatGPT:调查知识管理因素对学生满意度和持续使用的影响
IF 3.7 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-04-01 DOI: 10.1109/TLT.2024.3383773
Thi Thuy An Ngo;Thanh Tu Tran;Gia Khuong An;Phuong Thy Nguyen
The growing prevalence of advanced generative artificial intelligence chatbots, such as ChatGPT, in the educational sector has raised considerable interest in understanding their impact on student knowledge and exploring effective and sustainable implementation strategies. This research investigates the influence of knowledge management factors on the continuous usage of ChatGPT for educational purposes while concurrently evaluating student satisfaction with its use in learning. Using a quantitative approach, a structured questionnaire was administered to 513 Vietnamese university students via Google Forms for data collection. The partial least squares structural equation modeling statistical technique was employed to examine the relationships between identified factors and evaluate the research model. The results provided strong support for several hypotheses, revealing significant positive effects of expectation confirmation on perceived usefulness and satisfaction, as well as perceived usefulness on user satisfaction and continuous usage of ChatGPT. These findings suggest that when students recognize the usefulness of ChatGPT for their learnings, they experience higher satisfaction and are more likely to continue using it. In addition, knowledge acquisition significantly impacts both satisfaction and continuous usage of ChatGPT, while knowledge sharing and application influence satisfaction exclusively. This indicates that students prioritize knowledge acquisition over sharing and applying knowledge through ChatGPT. The study has theoretical and practical implications for ChatGPT developers, educators, and future research. Theoretically, it contributes to understanding satisfaction and continuous usage in educational settings, utilizing the expectation confirmation model and integrating knowledge management factors. Practically, it provides insights into comprehension and suggestions for enhancing user satisfaction and continuous usage of ChatGPT in education.
随着先进的生成式人工智能聊天机器人(如 ChatGPT)在教育领域的日益普及,人们对了解其对学生知识的影响以及探索有效和可持续的实施策略产生了浓厚的兴趣。本研究调查了知识管理因素对将 ChatGPT 持续用于教育目的的影响,同时评估了学生对使用 ChatGPT 学习的满意度。研究采用定量方法,通过谷歌表格对 513 名越南大学生进行了结构化问卷调查,以收集数据。研究采用偏最小二乘法结构方程模型统计技术来检验已识别因素之间的关系,并对研究模型进行评估。研究结果为几个假设提供了强有力的支持,揭示了期望确认对感知有用性和满意度的显著正效应,以及感知有用性对用户满意度和持续使用 ChatGPT 的显著正效应。这些研究结果表明,当学生认识到 ChatGPT 对他们的学习有用时,他们会体验到更高的满意度,并更有可能继续使用 ChatGPT。此外,知识获取对 ChatGPT 的满意度和持续使用都有显著影响,而知识共享和应用则只影响满意度。这表明,通过 ChatGPT,学生优先获取知识,而不是分享和应用知识。这项研究对 ChatGPT 开发人员、教育工作者和未来研究具有理论和实践意义。从理论上讲,它有助于理解教育环境中的满意度和持续使用情况,利用了期望确认模型并整合了知识管理因素。在实践中,它为提高教育领域用户对 ChatGPT 的满意度和持续使用提供了理解见解和建议。
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引用次数: 0
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IEEE Transactions on Learning Technologies
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