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Application of Clustering Algorithm in the Evaluation of College Students' English Reading Ability Under the Framework of Big Data 大数据框架下聚类算法在大学生英语阅读能力评价中的应用
Q2 Social Sciences Pub Date : 2024-07-17 DOI: 10.4018/ijwltt.349132
Yanhui Wang
In recent years, China has accelerated the process of internationalization and made more and more achievements in transnational communication and cooperation. English learning is very important for contemporary college students. And English reading is an important means to acquire English language knowledge, understand external information and improve English language practice ability. Therefore, cultivating college students' English reading ability is a pivotal element in college English teaching. This study will focus on the application of clustering algorithm based on big data framework in the evaluation of college students' English reading ability, aiming at exploring and establishing an effective evaluation model to promote the improvement of college students' English reading ability and academic achievement.
近年来,中国加快了国际化进程,在跨国交流与合作方面取得了越来越多的成就。英语学习对于当代大学生来说非常重要。而英语阅读是获取英语语言知识、了解外部信息、提高英语语言实践能力的重要手段。因此,培养大学生的英语阅读能力是大学英语教学中至关重要的一环。本研究将重点探讨基于大数据框架的聚类算法在大学生英语阅读能力评价中的应用,旨在探索和建立有效的评价模型,促进大学生英语阅读能力和学习成绩的提高。
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引用次数: 0
A Survey on High School Students' Online Self-Regulated Learning Skills 高中生在线自我调节学习能力调查
Q2 Social Sciences Pub Date : 2024-07-17 DOI: 10.4018/ijwltt.347664
Bing Liu, Jing Liu, Qianrong Yang
This study explores online self-regulated learning skills among high school students in three schools in China's EAST City Y using questionnaires. Results reveal the online self-regulated learning skills of high school students are positioned at an intermediate level, showcasing noteworthy disparities across distinct cohorts of high school students. Specifically, female students, urban residents, high-achieving students, and senior students (Grade 12) manifest distinct advantages in terms of online self-regulated learning aptitude. Conversely, male students, rural residents, students with comparatively lower academic achievements, as well as students in Grade 10 and Grade 11, evince limitations in online self-regulated learning skills. Additionally, Moderate internet use enhances high school students' online self-regulated learning; excessive or insufficient use hampers skill development. Future research should expand the sample to diverse regions and cultures to enhance generalizability.
本研究采用问卷调查的方式,探讨了中国东隅 Y 市三所学校高中学生的在线自我调节学习技能。结果显示,高中生的网络自我调节学习能力处于中等水平,不同群体的高中生之间存在显著差异。具体来说,女生、城市居民、成绩优秀的学生和高年级学生(12 年级)在网络自我调节学习能力方面表现出明显的优势。相反,男生、农村居民、学习成绩相对较差的学生以及 10 年级和 11 年级的学生在网络自我调节学习技能方面则表现出局限性。此外,适度使用互联网能提高高中生的在线自我调节学习能力,而过度使用或不充分使用互联网则会阻碍技能的发展。未来的研究应将样本扩大到不同地区和文化,以增强普适性。
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引用次数: 0
A New Model of Vocal Music Teaching in the Context of Internet Distance Learning 网络远程学习背景下的声乐教学新模式
Q2 Social Sciences Pub Date : 2024-07-17 DOI: 10.4018/ijwltt.348336
Xiaochen Zhang, Junkai Zhang
As Internet technology evolves, distance learning emerges as a pivotal mode of education. In music education, vocal teaching faces limitations in traditional face-to-face methods. This paper explores the advantages of Internet-based remote vocal music teaching and proposes a new mode leveraging an online platform, multimedia technology, and real-time interaction. The study assesses its impact on theoretical knowledge, vocal skills, singing proficiency, satisfaction, and improvement. Results demonstrate the effectiveness of Internet-based remote teaching, overcoming geographical barriers and providing flexible learning opportunities. Multimedia tools enhance skill demonstration, making learning more intuitive. The study reveals that Internet distance vocal teaching rivals traditional methods in improving singing skills and outperforms in teaching music theory. Moreover, students express higher satisfaction with this innovative approach, establishing it as a promising mode in vocal music education.
随着互联网技术的发展,远程学习成为一种重要的教育模式。在音乐教育中,声乐教学面临着传统面授方式的局限性。本文探讨了基于互联网的远程声乐教学的优势,并提出了一种利用网络平台、多媒体技术和实时互动的新模式。研究评估了其对理论知识、声乐技能、演唱水平、满意度和进步的影响。结果表明,基于互联网的远程教学克服了地域障碍,提供了灵活的学习机会,效果显著。多媒体工具加强了技能演示,使学习更加直观。研究表明,网络远程声乐教学在提高歌唱技能方面可与传统方法相媲美,在乐理教学方面也更胜一筹。此外,学生对这种创新方法的满意度较高,使其成为声乐教育中一种前景广阔的模式。
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引用次数: 0
Manual Label and Machine Learning in Clustering and Predicting Student Performance 人工标签和机器学习在聚类和预测学生成绩中的应用
Q2 Social Sciences Pub Date : 2024-07-17 DOI: 10.4018/ijwltt.347661
Mengjiao Yin, Hengshan Cao, Zuhong Yu, Xianyu Pan
This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a four-quadrant clustering technique. The AIM model delineates student investment into four quadrants based on their time and energy commitment to academic pursuits, distinguishing between result-oriented and process-oriented investments. The findings reveal that the four-quadrant method surpasses machine learning clustering in predictive accuracy, highlighting the robustness of manual feature engineering. The study's significance lies in its potential to guide educators in designing targeted interventions and personalized learning strategies, emphasizing the importance of process-oriented assessment in education. Future research is recommended to expand the sample size and explore the integration of deep learning models for validation.
本研究提出了 "学业投资模型"(AIM),将学习风格作为一种预测特征,作为预测学生学业成绩的新方法。研究利用来自中国 138 名市场营销专业学生的数据,通过四象限聚类技术,将机器学习聚类方法和人工特征工程相结合。AIM 模型根据学生在学业上投入的时间和精力,将学生的投资划分为四个象限,区分结果导向型投资和过程导向型投资。研究结果表明,四象限法在预测准确性上超过了机器学习聚类,凸显了人工特征工程的稳健性。这项研究的意义在于,它可以指导教育工作者设计有针对性的干预措施和个性化学习策略,强调了以过程为导向的评估在教育中的重要性。建议未来的研究扩大样本量,并探索整合深度学习模型进行验证。
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引用次数: 0
An Interactive Multimedia Model for Developing QOE-Enhanced E-Learning Platforms 开发 QOE 增强型电子学习平台的互动多媒体模型
Q2 Social Sciences Pub Date : 2024-07-17 DOI: 10.4018/ijwltt.347662
Edwin Mwosa Kivuti, Dennis Kaburu, Kennedy Ogada
This paper provides an approach to providing QOE enhancement for a multifaceted learning platform that includes streamed media content. We demonstrate how the QOE of a multifaceted platform can be enhanced using the Lighthouse tool. The Lighthouse tool helped improve the page load speed by 75%. We also demonstrate how the playback quality of the video streaming content can be enhanced using CMAF-formatted DASH content. When compared to single-bit rate media, DASH-based media provided better video playback quality. The study also evaluates the learners` preferences for specific interactive features of a learning platform. The least preferred feature uniquely had static content. The results of this study provide empirical data that would help instructional designers make feature selection choices that`s guided by empirical data and improve the QOE of their instructional learning platforms.
本文提供了一种为包含流媒体内容的多元学习平台提供 QOE 增强功能的方法。我们演示了如何利用 Lighthouse 工具增强多元平台的 QOE。在 Lighthouse 工具的帮助下,页面加载速度提高了 75%。我们还演示了如何利用 CMAF 格式的 DASH 内容提高视频流内容的播放质量。与单比特率媒体相比,基于 DASH 的媒体可提供更好的视频播放质量。研究还评估了学习者对学习平台特定互动功能的偏好。最不喜欢的功能是静态内容。这项研究的结果提供了经验数据,有助于教学设计人员在经验数据的指导下选择功能,并改善教学学习平台的 QOE。
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引用次数: 0
Promoting Mental Health Education Through Sunshine Sports Integration in the Context of New Curriculum Reform 新课改背景下通过阳光体育融合推进心理健康教育
Q2 Social Sciences Pub Date : 2024-07-16 DOI: 10.4018/ijwltt.345656
Shuo Wang
This paper attempts to test and analyze students' mental health status through the reform of physical education curriculum setting mode, reveal the changes and characteristics of individual mental health status, and then promote reasonable and effective physical education reform and the integration of psychological education. Furthermore, this article investigates people's mental health using the Apriori algorithm and the BP algorithm, and accurately presents the current condition using data graphs and other approaches, and its accuracy has grown by 20.32%. It also concludes that we should pursue the aims of social adaption and mental health, as well as support improved implementation of the new physical education curriculum. Physical education instruction must be engaging, but it cannot be done in isolation from sports and practice. As part of the new curriculum reform, physical education should be linked with psychological education.
本文试图通过体育课程设置模式的改革,对学生的心理健康状况进行检测和分析,揭示个体心理健康状况的变化和特点,进而促进体育教学改革与心理教育的合理有效结合。此外,本文利用 Apriori 算法和 BP 算法对人们的心理健康状况进行了调查,并利用数据图表等方法准确地呈现了现状,其准确率提高了 20.32%。报告还得出结论,我们应追求社会适应和心理健康的目标,并支持改进体育新课程的实施。体育教学必须引人入胜,但不能脱离运动和实践。作为新课程改革的一部分,体育应与心理教育相联系。
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引用次数: 0
The Teaching Mode Design and Effect Evaluation Method of Animation Course From the Perspective of Big Data 大数据视角下动漫课程教学模式设计与效果评价方法研究
Q2 Social Sciences Pub Date : 2024-05-16 DOI: 10.4018/ijwltt.343522
Zhongqiang Feng, Yi Zhang
OBE concept is a new teaching mode which emphasizes the improvement of students' subjective initiative and professional practice ability. The teaching of animation course is based on drawing and computer, which requires teachers to understand the OBE mode of animation course, carry out targeted teaching innovation of animation course, and adjust the traditional teaching methods, teaching contents and teaching assessment methods. Based on the MOOC platform from the perspective of big data, this paper analyzes the teaching status and innovation process of animation course, and puts forward a hybrid animation course teaching method. Through the research of 686 primary and secondary school teachers, the results show that the hybrid animation course teaching based on OBE and MOOC from the perspective of big data has a better effect than the traditional teaching method, which improves students' initiative in learning animation courses and greatly enhances students' acceptability in learning animation courses.
OBE理念是一种新的教学模式,强调学生主观能动性和专业实践能力的提高。动画课程的教学以绘画和计算机为主,这就要求教师了解动画课程的OBE模式,有针对性地进行动画课程的教学创新,调整传统的教学方法、教学内容和教学考核方式。本文基于大数据视角下的MOOC平台,分析了动漫课程的教学现状和创新过程,提出了混合式动漫课程教学方法。通过对686名中小学教师的调研,结果表明大数据视角下基于OBE和MOOC的混合动漫课程教学比传统教学方法效果更好,提高了学生学习动漫课程的主动性,大大增强了学生学习动漫课程的可接受性。
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引用次数: 0
DBGCN DBGCN
Q2 Social Sciences Pub Date : 2024-05-02 DOI: 10.4018/ijwltt.342848
Ping Hu, Zhaofeng Li, Pei Zhang, Jimei Gao, Liwei Zhang
Given the extensive use of online learning in educational settings, Knowledge Tracing (KT) is becoming increasingly essential. KT primarily aims to predict a student's future knowledge acquisition based on their past learning activities, thus enhancing the efficiency of student learning. However, the effective acquisition of dynamic and evolving student representations from their historical records presents a formidable challenge. This paper introduces a Knowledge Tracing methodology predicated on Dynamic Broadth Graph Convolutional Networks (DBGCN). DBGCN leverages the mechanisms of breadth graph convolutional networks to proficiently acquire representations of questions and knowledge points from dynamically constructed topological graphs. It employs student state information as an attention query vector to augment student representations, thereby partially mitigating the challenge of capturing the dynamic shifts in user states. The effectiveness of our proposed DBGCN method has been demonstrated through extensive experimentation.
鉴于在线学习在教育领域的广泛应用,知识追踪(Knowledge Tracing,KT)变得越来越重要。知识追踪的主要目的是根据学生过去的学习活动预测其未来的知识获取情况,从而提高学生的学习效率。然而,如何从学生的历史记录中有效地获取动态的、不断变化的学生表征,是一项艰巨的挑战。本文介绍了一种基于动态宽图卷积网络(DBGCN)的知识追踪方法。DBGCN 利用广度图卷积网络的机制,从动态构建的拓扑图中熟练地获取问题和知识点的表征。它采用学生状态信息作为注意力查询向量来增强学生表征,从而部分缓解了捕捉用户状态动态变化所带来的挑战。我们提出的 DBGCN 方法已通过大量实验证明了其有效性。
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引用次数: 0
Measurement and Policy Optimization of Regional Preschool Education Development Level Based on Generalized Orthogonal Fuzzy Sets and Prospect Theory 基于广义正交模糊集和前景理论的区域学前教育发展水平测度与政策优化
Q2 Social Sciences Pub Date : 2024-04-02 DOI: 10.4018/ijwltt.341803
Qian Wang
Preschool education belongs to non-compulsory enlightenment education, and it is difficult to measure and analyze the development of preschool education in different regions because of its multiple attributes and diversity of influencing factors. In addition, decision makers will be limited by their own cognition when facing multi-attribute factors and uncertain factors, and there is a big gap between the decision results given and the actual situation. Therefore, this chapter introduces generalized orthogonal fuzzy sets and prospect theory into the measurement model of preschool education development level based on technique for order of preference by similarity to ideal solution (TOPSIS) method to improve the decision accuracy of decision makers. The experimental results show that the model can effectively deal with uncertain information and improve the analysis accuracy, and the results are more in line with the actual situation than other models. At the same time, it can intuitively compare and analyze the development of preschool education in different regions, and provide reliable data support for decision makers.
学前教育属于非义务启蒙教育,由于其属性的多重性和影响因素的多样性,很难对不同地区学前教育的发展进行衡量和分析。此外,决策者在面对多属性因素和不确定因素时,会受到自身认知的限制,给出的决策结果与实际情况存在较大差距。因此,本章将广义正交模糊集和前景理论引入到基于理想解相似度排序技术(TOPSIS)方法的学前教育发展水平测量模型中,以提高决策者的决策准确性。实验结果表明,该模型能有效处理不确定信息,提高分析精度,与其他模型相比,结果更符合实际情况。同时,它能直观地比较和分析不同地区学前教育的发展状况,为决策者提供可靠的数据支持。
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引用次数: 0
Network Ideological and Political Education System for College Students Based on Multimedia Service Architecture 基于多媒体服务架构的大学生网络思想政治教育系统
Q2 Social Sciences Pub Date : 2024-03-26 DOI: 10.4018/ijwltt.341265
Liangzhou Wu, Haley A. Tancredi
Today, the network society has become an integral part of human society, and the network life marked by digitization, informatization and networking has become a new state of existence; a new society marked by interactivity, virtuality and innovation A mode of operation has been created. A network, in simple terms, is to connect, and can be called a computer network. Such highest degree of social informatization in my country. It is a new idea designed by making full use of computer networks, multimedia technology and modern communication technology and closely combining the cognitive hotspots of contemporary college students. way of political education. In response to the above problems, this article uses deep learning technology to develop an intelligent education system based on detection technology. The system takes identifying whether the standard is met as the main goal, and gives comprehensive evaluation and improvement suggestions for the quality of action completion. It gets rid of the constraints of the venue.
今天,网络社会已经成为人类社会不可分割的一部分,以数字化、信息化、网络化为标志的网络生活已经成为一种新的生存状态,一个以交互性、虚拟性、创新性为标志的新社会已经形成。简单地说,网络就是连接,可以称为计算机网络。在我国,这种社会信息化程度最高。它是充分利用计算机网络、多媒体技术和现代通讯技术,紧密结合当代大学生的认知热点而设计的一种全新的思想政治教育方式。针对上述问题,本文利用深度学习技术开发了基于检测技术的智能教育系统。该系统以识别是否达标为主要目标,对行动完成质量给出综合评价和改进建议。摆脱了场地的束缚。
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引用次数: 0
期刊
International Journal of Web-Based Learning and Teaching Technologies
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