E-Learning

摘要： 传统的舞蹈教学模式主要有现场教学以及看视频教学两种方式,传统的教学模式有时间花费以及效率低等局限性(现场教学无法避免的时间花费、看视频教学的教学效率往往不高),但是E-Learning模式下的教学可以克服以上局限性。随着人机交互模式的发展,用户与计算机之间的交互已经被逐渐普及。Kinect作为一种动作捕捉设备被广泛用于虚拟现实人机交互中,由于Kinect V2通过其深度摄像机以及红外传感器就可以获得用户的深度图像以及人体骨骼关键点信息,因此利用Kinect设备来获取用户的相关数据,以Unity平台为主,开发了一款基于Kinect的、E-Learning模式下的舞蹈教学系统。

摘要： E-learning互动教学平台与PBL教学结合可弥补无法大范围开展金匮要略PBL教学的遗憾,但也对青年教师素养提出更高的要求。青年教师需要进一步加强教学基本功、加深中医基础及专业知识积累、丰富相关学科知识储备与临床经验,同时还需提高信息化素养与人文素养,才能顺利完成E-learning平台中的PBL案例教学,达到教学目的。

摘要： E-learning involves programs that use the internet to allow instructional material beyond classroom walls for interaction between educators and the learners.It is powerful tool in education if the right pedagogy is used.The purpose of the study was to interrogate types of e-learning modes,impact,success and challenges of e-learning at Bishop Hannington Institute of Theology and Development,Mombasa.The study adopted desk top research by observation of students and educators use of e-learning at BHI(Mombasa)and analyzed documents,books,journals on the patterns of e-learning in relation to BHI.The study reviewed the synchronous and asynchronous types of e-learning modes.Additionally,the study evaluated advantages and disadvantages of e-learning at BHI.The study aim was to give information to other universities,middle level colleges and secondary schools on the place of e-learning in modern education patterns and how best it can be improved.The study created awareness to the educators,students and the general public the need for e-learning.

摘要： E-Learning领域的推荐系统在满足学习者个性化学习需求方面发挥着重要作用。近年来,国际上围绕E-Learning推荐系统开展的研究迅速增多。采用文献计量分析方法对该领域的研究进行系统分析,有助于为E-Learning推荐系统的高水平研究和高质量应用提供镜鉴。综括而言,当前国际E-Learning领域的推荐系统研究热点及其演变趋势集中体现在6个方面:一是融合多种技术优势的混合推荐日益受到重视且逐渐成为主流。二是伴随技术支持下群体学习的多元发展,个性化推荐由关注个体推荐逐步转向关注群体推荐。三是随着大规模开放在线课程的流行,个性化推荐逐步突破小规模而面向大规模学习者群体,重视通过对海量学习资源和过程数据的搜集和挖掘而提供个性化推荐。四是从心理学层面关注学习者情绪变化,并据此构建上下文推荐系统,通过优化调整推荐内容不断促进学习者高效完成学习任务。五是在推荐功能上更加强调学习模型构建,重视提升学习者的深层次认知能力和促进有效学习。六是在先进技术的支持上,个性化推荐系统强调引入深度学习技术,不断优化其表征能力、融合效率和推荐效果。

摘要： In order to effectively prevent the spread of novel coronavirus pneumonia and ensure the orderly development of teaching tasks,colleges and universities have launched online teaching activities.As a new teaching method,how to reasonably carry out teaching design,teaching organization and ensure teaching quality has become a new problem in front of educators.Taking the“Subway”course as an example,this paper summarizes and introduces the online teaching methods and personal experience under the epidemic situation from the aspects of the overall framework design,specific implementation scheme,effect investigation and reflection of the online teaching mode based on MOOC platform,so as to enrich the experience of online teaching activities in colleges and universities during the epidemic period.

摘要： Internet of Things(IoT)with e-learning is widely employed to collect data from various smart devices and share it with other ones for efficient e-learning applications.At the same time,machine learning(ML)and data mining approaches are presented for accomplishing prediction and classification processes.With this motivation,this study focuses on the design of intelligent machine learning enabled e-learner non-verbal behaviour detection(IML-ELNVBD)in IoT environment.The proposed IML-ELNVBD technique allows the IoT devices such as audio sensors,cameras,etc.which are then connected to the cloud server for further processing.In addition,the modelling and extraction of behaviour take place.Moreover,extreme learning machine sparse autoencoder(ELM-SAE)model is employed for the detection and classification of non-verbal behaviour.Finally,the Ant Colony Optimization(ACO)algorithm is utilized to properly tune the weight and bias parameters involved in the ELM-SAE model.In order to ensure the improved performance of the IML-ELNVBD model,a comprehensive simulation analysis is carried out and the results highlighted the betterment compared to the recent models.

摘要： In most developing countries, governments attempt to enforce the movement from analogue to digital for all their sectors, from public to private. These technological advancements have been noted to bring necessary and unavoidable changes to businesses and learning environments. Higher learning institutions have adopted various e-learning systems to support learning, research, and publication activities to stay competitive in global academic systems. However, most public higher learning institutions in Tanzania lag behind in the adoption of these systems. Thus, research shows a failure of these institutions in utilising the full benefit that today’s Information and Communication Technology (ICT) can offer in learning environments. Thus, this study examines factors affecting the adoption of such a system in developing countries like Tanzania, taking the Institute of Accountancy Arusha (IAA) as a case study. The study used a mixed methodology where thematic and descriptive analysis was used to analyse both qualitative and quantitative research data. The study population was 187 teaching staff, a sample size of 126 was obtained, and 157 study participants were involved in the study. The study found that factors affecting the adoption of e-learning systems in public higher learning institutions in Tanzania include lack of ICT infrastructure, lack of technical and managerial support and lack of computers and e-learning knowledge among facilitators. Thus, the study recommended investments in adequate and reliable ICT facilities, high intermate speed and bandwidth, and policies that support e-learning and training programs about e-learning knowledge and use. Also, this study recommends the use of the Multi-Factors Adoption Model (MFAM11) for the successful adoption of an e-learning system in public higher learning institutions in Tanzania.

摘要： This paper proposes a novel,efficient and affordable approach to detect the students’engagement levels in an e-learning environment by using webcams.Our method analyzes spatiotemporal features of e-learners’micro body gestures,which will be mapped to emotions and appropriate engagement states.The proposed engagement detection model uses a three-dimensional convolutional neural network to analyze both temporal and spatial information across video frames.We follow a transfer learning approach by using the C3D model that was trained on the Sports-1M dataset.The adopted C3D model was used based on two different approaches;as a feature extractor with linear classifiers and a classifier after applying fine-tuning to the pretrained model.Our model was tested and its performance was evaluated and compared to the existing models.It proved its effectiveness and superiority over the other existing methods with an accuracy of 94%.The results of this work will contribute to the development of smart and interactive e-learning systems with adaptive responses based on users’engagement levels.

摘要： This paper discusses the strengths and drawbacks of blended language learning.There exists a great debate about what constitutes blended learning.By considering its advantages and disadvantages,we contend that there is a need for higher education to embrace blended learning in order to increase educational opportunities and improve learning outcomes.In order to support this argument,this paper addresses the transformative potential of blended learning based on recommendations for class redesign from previous studies.This paper then concludes by providing an agenda for further research.

摘要： 在e-Learning环境中,学习普遍存在"情感缺失"问题,该问题会导致学习效果和学习体验下降.在学习过程中及时识别学习者的情感状态是解决"情感缺失"的首要问题,情感识别技术在人机交互教学得到了广泛的应用,但仍然存在不少问题和挑战.随着眼动追踪技术的发展,将眼动信号引入情感识别成为研究的热点.针对当前国内外在e-Learning环境中基于眼动特征的相关研究进行综述,对相关研究中采用的眼动特征、机器学习方法以及涉及的学习过程进行分类、归纳及分析,归纳了五类学习过程研究中常用的眼动特征和识别算法.通过对应用在疲劳检测、健康医疗以及人机交互等相关领域中的眼动特征进行分析,对可借鉴至MOOC学习环境下情感识别的眼动特征进行汇总,并为下一步如何采用眼动特征在MOOC环境下进行情感识别研究提出建议.

摘要： 随着信息技术和传统教学方式的不断融合，E-learning 已经逐渐成为学者们研究的热点。他们从E-learning的系统构建、理论分析、绩效评估等方面对E-learning 进行了深入的探讨和研究，而对作为E-learning的一个重要组成部分的高校学生课堂上机学习却没有能够给予足够的关注。本文基本思路是以行为科学和行为理论为基础，采集和保存学生的E-learning 行为信息，应用统计学的方法分析与评价E-learning 行为新特征；分析出学生上机学习时的基本行为以及学习状态的变化规律，应用统计学的方法分析学生上机学习时的基本行为以及学习状态的变化规律，揭示E-learning 行为新特征，对现有的网络教育的过程设计无疑有着重要的参考价值。

摘要： 随着信息技术和传统教学方式的不断融合，E-learning 已经逐渐成为学者们研究的热点。他们从E-learning的系统构建、理论分析、绩效评估等方面对E-learning 进行了深入的探讨和研究，而对作为E-learning的一个重要组成部分的高校学生课堂上机学习却没有能够给予足够的关注。本文基本思路是以行为科学和行为理论为基础，采集和保存学生的E-learning 行为信息，应用统计学的方法分析与评价E-learning 行为新特征；分析出学生上机学习时的基本行为以及学习状态的变化规律，应用统计学的方法分析学生上机学习时的基本行为以及学习状态的变化规律，揭示E-learning 行为新特征，对现有的网络教育的过程设计无疑有着重要的参考价值。

摘要： 随着信息技术和传统教学方式的不断融合，E-learning 已经逐渐成为学者们研究的热点。他们从E-learning的系统构建、理论分析、绩效评估等方面对E-learning 进行了深入的探讨和研究，而对作为E-learning的一个重要组成部分的高校学生课堂上机学习却没有能够给予足够的关注。本文基本思路是以行为科学和行为理论为基础，采集和保存学生的E-learning 行为信息，应用统计学的方法分析与评价E-learning 行为新特征；分析出学生上机学习时的基本行为以及学习状态的变化规律，应用统计学的方法分析学生上机学习时的基本行为以及学习状态的变化规律，揭示E-learning 行为新特征，对现有的网络教育的过程设计无疑有着重要的参考价值。

摘要： 随着信息技术和传统教学方式的不断融合，E-learning 已经逐渐成为学者们研究的热点。他们从E-learning的系统构建、理论分析、绩效评估等方面对E-learning 进行了深入的探讨和研究，而对作为E-learning的一个重要组成部分的高校学生课堂上机学习却没有能够给予足够的关注。本文基本思路是以行为科学和行为理论为基础，采集和保存学生的E-learning 行为信息，应用统计学的方法分析与评价E-learning 行为新特征；分析出学生上机学习时的基本行为以及学习状态的变化规律，应用统计学的方法分析学生上机学习时的基本行为以及学习状态的变化规律，揭示E-learning 行为新特征，对现有的网络教育的过程设计无疑有着重要的参考价值。

摘要： 知识管理是组织的知识沉淀、知识传递、知识应用和知识创新的一个循环过程,目的在于使组织成员实现经验传承和知识分享,进而提高组织绩效。而鉴于e-learning(电子化学习)在知识传递过程中发挥的作用,知识管理应该与e-learning进行有效整合,充分利用e-learning的教学设计理念,进而实现组织有效的知识管理。本文仅从信息重组的角度分析如何处理三者的关系。

摘要： 知识管理是组织的知识沉淀、知识传递、知识应用和知识创新的一个循环过程,目的在于使组织成员实现经验传承和知识分享,进而提高组织绩效。而鉴于e-learning(电子化学习)在知识传递过程中发挥的作用,知识管理应该与e-learning进行有效整合,充分利用e-learning的教学设计理念,进而实现组织有效的知识管理。本文仅从信息重组的角度分析如何处理三者的关系。

摘要： 知识管理是组织的知识沉淀、知识传递、知识应用和知识创新的一个循环过程,目的在于使组织成员实现经验传承和知识分享,进而提高组织绩效。而鉴于e-learning(电子化学习)在知识传递过程中发挥的作用,知识管理应该与e-learning进行有效整合,充分利用e-learning的教学设计理念,进而实现组织有效的知识管理。本文仅从信息重组的角度分析如何处理三者的关系。

摘要： 知识管理是组织的知识沉淀、知识传递、知识应用和知识创新的一个循环过程,目的在于使组织成员实现经验传承和知识分享,进而提高组织绩效。而鉴于e-learning(电子化学习)在知识传递过程中发挥的作用,知识管理应该与e-learning进行有效整合,充分利用e-learning的教学设计理念,进而实现组织有效的知识管理。本文仅从信息重组的角度分析如何处理三者的关系。

摘要： E-learning的应用在提高人们学习效率的同时也因学习内容本身、教学设计的不良等产生了各种各样的认知负荷，像内部认知负荷.外部认知负荷，关联认知负荷等。这些认知负荷在总量上如果超出了学习者工作记忆的认知加工资源范围，则会阻碍或者终止学习者的学习。因此，在E-learning的应用中，应注重采取各种策略降低其产生的认知负荷，确保各种认知负荷的总量在工作记忆认知加工的能力之内，从而提高E-learning应用中学习者学习的有效性。

摘要： E-learning的应用在提高人们学习效率的同时也因学习内容本身、教学设计的不良等产生了各种各样的认知负荷，像内部认知负荷.外部认知负荷，关联认知负荷等。这些认知负荷在总量上如果超出了学习者工作记忆的认知加工资源范围，则会阻碍或者终止学习者的学习。因此，在E-learning的应用中，应注重采取各种策略降低其产生的认知负荷，确保各种认知负荷的总量在工作记忆认知加工的能力之内，从而提高E-learning应用中学习者学习的有效性。

摘要： 移动互联网时代SAAS模式的Elearning体系。本发明涉及一种基于SAAS模式的移动互联网时代Elearning体系架构方法，用于提升在线学习平台Elearning用户的使用体验和学习效率，包括：SAAS云计算平台，用于保障整个系统的运维服务；应用层，包含学习内容管理系统LCMS（Learning Content Management System），能够高效地创建和发布E-Learning课程，并评测其效果；WEB展现层，用于展示所有格式的课件；移动客户端APP，用于展示特定的轻量文档课件和社交媒体信息。本发明还提供一种对应的方法。本发明对在线学习系统中移动客户端的价值进行了挖掘，可为用户提供更直接、便捷的信息获取，利用零碎时间学习，使用户活跃度与黏性迅速提升。