电子信息类核心课程线上教学模式改革与探索

新冠肺炎疫情给课程教学的信息化改革提出巨大挑战。针对特殊时期停课不停学的要求,分析了信号与系统的课程目标和课程内涵,结合线上教学特点,从课程建构、线上教学组织与教学效果评价等方面形成了完整的线上教学设计模式。经过疫情期间的线上教学实践发现,线上教学模式集成慕课、直播教学工具、移动端平台的优势,切实提升了线上教学效果,基本达成了既定教学目标。后疫情时代,构建线上线下相结合的混合式教学将是课堂教学改革的重要趋势。     

疫情常态下信号与系统双线融合教学实践

新冠疫情防控常态化下，线上线下“双线融合”逐渐成为主要教学模式。西电“信号与系统”课程组依托中国大学MOOC平台上“信号与系统”“工程信号与系统”两门国家级精品在线开放课程，提出 “MOOC课程平台自学+任课教师线下线上同步讲授”相结合的教学模式。经过一个学期的实践，借助大数据分析表明，“双线融合”教学模式保证了与传统的线下课堂教学质量“实质等效”。     

常态化疫情防控期线上线下融合教学探索

疫情常态化防控期间,针对返校学生和未返校学生两个群体,教师探索线上线下融合教学方式,发挥线上互动、线下投影及板书的优点进行融合教学。针对实验教学,教师充分发挥科研和教学经验,将传统硬件电路实验箱升级改造为虚实一体实验系统,返校学生和未返校学生均可进行实验,实验场景突破时空限制。针对在线考试,教师精选考试内容,调整考试时间,创新监考方式,保证考试内容合理和考试过程公平。     

新冠疫情背景下网络线上教学探究——以“HTML5网站设计”为例

文章从线上教学课程特点、线上教学活动的具体举措以及教学效果和反思等方面,探索如何在新冠肺炎疫情下进行"HTML5网站设计"课程的线上教学,提出一些线上教学活动的具体实施方法,例如:如何调动学生线上学习的积极性,如何让学生运用各种平台解决学习过程中遇到的问题等。     

疫情时期数字电子技术线上混合式教学实践

针对疫情期间的特殊情况,选择腾讯课堂和超星泛雅课程平台和学习通软件等工具,实施了数字电子技术课程的SPOC混合式线上教学工作,并取得良好的教学效果。文中对近两个月的教学实践过程进行了梳理和分析,探讨了疫情过后继续运用网络和软件工具开展线上、线下SPOC混合式教学的前景。     

新冠肺炎疫情对数字经济消费的影响及对策

2020年春节假期与新型冠状病毒肺炎疫情防控期叠加,线下消费锐减,居民对于数字经济消费的依赖倍增。短期来看,线上文娱产业迎来爆发式增长,出行相关OTA(在线旅游预订商)消费平台面临短暂的消费空窗期,电商平台为化解疫情期间对消费的冲击提供了缓冲空间,线上协同办公、远程诊疗、网络教育等对传统线下模式进行大规模替代。长期来看,经历疫情磨砺的数字经济消费各环节协同和响应能力将得到提升,线上协同模式将更成熟,资源将不断累积,消费者数字经济消费习惯将进一步巩固,利好数字经济消费未来发展。     

疫情期间"数字电子技术"线上混合式教学实践

针对疫情期间的特殊情况,我们课程教研组选择腾讯课堂、超星泛雅课程平台和学习通软件等工具,实施了"数字电子技术"课程的SPOC混合式线上教学工作,并取得良好的教学效果.本文对近一学期的教学实践过程进行了梳理和分析,探讨了疫情过后继续开展线上、线下SPOC混合式教学的前景.     

基于"互联网+"的"宽带与数据传输"O2O教学模式创新改革与研究

针对线下教育在疫情面前无能为力,线上教育要求网络环境好、学生自觉性高等问题,文章首先描述了"宽带与数据传输"课程开展现状,就目前存在问题展开了分析讨论,然后以"链路聚合技术原理与配置"为例,详细阐述了将二者相融合的新型教学模式——线上线下(O2O)混合教学模式课程实施方案,最后总结了采用新型教学模式的优势,为后期高职院...     

基于效果导向的电商类课程线上教学方式研究

线上教学方式作为应对新冠疫情的新举措迅速走进高校,疫情常态后更是成了一种常用的辅助教学方式.电商类课程大多是实践性较强含有实操环节的课程,在适用线上教学方式的过程中难免出现一些问题,影响教学效果.文章分析了电商类课程的构成、特点以及目前电商类课程线上教学面临的问题,以效果为导向,提出了电商类课程线上教学方式的优化建议.     

"讲一练二考三"在"电子技术"线上教学中的探索

新冠肺炎疫情背景下无法开展线下课程,因此"电子技术"课程采用线上教学的方式,教师与学生均面临诸多问题与挑战.本文基于"讲一练二考三"的教学理念,针对"电子技术"线上教学的特点,提出了重难点线上教学立体化的"讲一"、学生被动学习方式转变下的"练二"、线上考核形式丰富灵活化的"考三"的改革方法.所提方法对未来疫情防控常态化下的高校工科线上课程有积极参考意义.     

What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis

The COVID-19 pandemic has caused major global changes both in the areas of healthcare and economics. This pandemic has led, mainly due to conditions related to confinement, to major changes in consumer habits and behaviors. Although there have been several studies on the analysis of customers’ satisfaction through survey-based and online customers’ reviews, the impact of COVID-19 on customers' satisfaction has not been investigated so far. It is important to investigate dimensions of satisfaction from the online customers’ reviews to reveal their preferences on the hotels' services during the COVID-19 outbreak. This study aims to reveal the travelers’ satisfaction in Malaysian hotels during the COVID-19 outbreak through online customers’ reviews. In addition, this study investigates whether service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. Accordingly, we develop a new method through machine learning approaches. The method is developed using text mining, clustering, and prediction learning techniques. We use Latent Dirichlet Allocation (LDA) for big data analysis to identify the voice-of-the-customer, Expectation-Maximization (EM) for clustering, and ANFIS for satisfaction level prediction. In addition, we use Higher-Order Singular Value Decomposition (HOSVD) for missing value imputation. The data was collected from TripAdvisor regarding the travelers’ concerns in the form of online reviews on the COVID-19 outbreak and numerical ratings on hotel services from different perspectives. The results from the analysis of online customers’ reviews revealed that service quality during COVID-19 has an impact on hotel performance criteria and consequently customers' satisfaction. In addition, the results showed that although the customers are always seeking hotels with better performance, they are also concerned with the quality of related services in the COVID-19 outbreak.     

Recommendation agents and information sharing through social media for coronavirus outbreak

The novel outbreak of coronavirus disease (COVID-19) was an unexpected event for tourism in the world as well as tourism in the Netherlands. In this situation, the travelers’ decision-making for tourism destinations was heavily affected by this global event. Social media usage has played an essential role in travelers’ decision-making and increased the awareness of travel-related risks from the COVID-19 outbreak. Online consumer media for the outbreak of COVID-19 has been a crucial source of information for travelers. In the current situation, tourists are using electronic word of mouth (eWOM) more and more for travel planning. Opinions provided by peer travelers for the outbreak of COVID-19 tend to reduce the possibility of poor decisions. Nevertheless, the increasing number of reviews per experience makes reading all feedback hard to make an informed decision. Accordingly, recommendation agents developed by machine learning techniques can be effective in the analysis of such social big data for the identification of useful patterns from the data, knowledge discovery, and real-time service recommendations. The current research aims to adopt a framework for the recommendation agents through topic modeling to uncover the most important dimensions of COVID-19 reviews in the Netherland forums in TripAdvisor. This study demonstrates how social networking websites and online reviews can be effective in unexpected events for travelers’ decision making. We conclude with the implications of our study for future research and practice.     

The role of online news and social media in preventive action in times of infodemic from a social capital perspective: The case of the COVID-19 pandemic in South Korea

Infodemic, the spread of false information during the COVID-19 pandemic, has been raised as one of the major concerns aggravating the confusion in the global society. In this regard, the role of media as an information channel in delivering the reliable information and motivating the active participation of citizens in complying with government’s preventive actions becomes much more important. In this study, the role of online news and social media on people’s preventive actions considering the role of trust in citizens and government from the perspective of social capital is investigated. For the empirical study, a structural equation modeling is employed by using survey material gathered from South Korea in the early days of the COVID-19 outbreak. South Korea was selected as its COVID-19 prevention strategy focused not only on the provision of medical support, but also on the enhancement of social trust through active engagement with people through media channels. Our results reveal that the perceived characteristics of online news and social media influence preventive actions through the trust in citizens or in government. In addition, while online news media enhances trust in both the citizens and the government, social media only influences trust in citizens. Based on our findings, the role of media in preventing the spread of COVID-19 is dicussed.     

Understanding individual psychological and behavioral responses during COVID-19: Application of stimulus-organism-response model

To comprehend the nature, implications, risks and consequences of the events of the COVID-19 crisis, individuals largely relied on various online information sources. The features of online information exchange (e.g., conducted on a massive scale, with an abundance of information and unverified sources) led to various behavioral and psychological responses that are not fully understood. This study therefore investigated the relationship between exposure to online information sources and how individuals sought, forwarded, and provided COVID-19 related information. Anchored in the stimulus-organism-response model, cognitive load theory, and the theory of fear appeal, this study examined the link between the online consumption of COVID-19-related information and psychological and behavioral responses. In the theory development process, we hypothesized the moderating role of levels of fear. The research model included six hypotheses and was empirically verified on self-reported data (N = 425), which was collected in early 2021. The results indicate that continuous exposure to online information sources led to perceived information overload, which further heightened the psychological state of cyberchondria. Moreover, the act of seeking and providing COVID-19 information was significantly predicted by perceived cyberchondria. The results also suggest that higher levels of fear led to increased levels of seeking and providing COVID-19-related information. The theoretical and practical implications of these findings are presented, along with promising areas for future research.     

线上教学的启发与实践

2020年新冠肺炎疫情的特殊时期要求开展线上教学,线上教学初期面临网络不稳定、实时管控不利、在线组织教学难发力等多种问题,为了保障教学工作顺利进行,延安大学西安创新学院提供了多平台支撑,教学工作结合传统的教学理念,利用网络平台优势提供在线视频教学、签到监督、课程视频回放、学习辅助资料上传、线上作业批改、线上答疑,其中“校企合作”案例教学实施增加了线上教学的趣味性和实践能力,同时为线上教学课堂理念带来了新的思考与创新。     

数字贸易对稳外贸与促复工的影响

随着世界卫生组织将新型冠状病毒肺炎疫情认定为"国际公共卫生紧急事件",多个国家宣布对中国采取出入境管制、暂停往返航班和进出口商品限制等措施,中国外贸面临来自内外部的巨大压力。与2003年非典疫情爆发时不同,如今中国数字贸易已经进一步发展成熟,在稳外贸和促复工中正发挥重要作用。我国应进一步推动贸易开展方式的数字化转型,鼓励支持数字产品和服务出口,并加快完善数字服务贸易治理体系。     

Modelling users’ perception of the online real estate platforms in a digitally disruptive environment: An integrated KANO-SISQual approach

Global disruption and innovation are revolutionising many industries and creating a digitally disruptive environment (DDE); real estate is no exception. Real estate online platforms (REOPs) are getting more attention in the era of COVID-19, where the real estate businesses must run online, and the service users are pushed to a forced digital experience adoption. The users or consumers are not satisfied or happy with the current state of REOPs and often regret their decisions due to the poor quality of the web-based information provided on these REOPs. Based on a mixed approach of integrated KANO-SISQual, the current study develops a comprehensive smart real estate technology adoption model (SRETAM) to model the users’ perception of the REOPs in DDE. Data is collected through a questionnaire survey from 407 Sydney based REOP users. A total of 31 key factors are identified by reviewing 256 articles vetted by 12 local real estate agents. The results highlight 19 factors to be very important to REOPs users: reliability, the accuracy of the information, and credibility of the online platforms are the top three important factors. The hypotheses’ results show that all the SRETAM categories contribute equally to the users’ behavioural intention to use the REOPs and the KANO categories are statistically different. For KANO categories, eight attractive features are identified: graphical statistics, familiar web technology, content structure, web design, immersive content, self-efficacy, information novelty, and presence of 3D interactive models. Displaying the users’ location, learning tutorials, and hyperlinks to external sources on the web portals dissatisfy REOP users. The factors and their classifications can help the users get more features, verified, and transparent information for making better decisions in the DDE, whereas the REOP can enjoy more business due to increased service consumers. This can lay the foundation for transforming the traditional real estate sector into smart real estate in lines with industry 4.0 requirements in the DDE.     

Can COVID-19 pandemic influence experience response in mobile learning?

The mass spreading of COVID-19 has changed the paradigm of the education industry. In China and many other nations, universities have introduced compulsory remote education programs such as mobile learning (m-learning) to prevent public health hazards caused by the pandemic. However, so far, there is still a lack of understanding of student’s learning experience responses in compulsory m-learning programs. As such, there is a necessity to explore the factors and mechanisms which drives students’ experience. This paper evaluates the influence of both pedagogy and technology on learner’s compulsory m-learning experience response (ER) by extending the mobile technology acceptance model (MTAM) during the COVID-19 pandemic. An online self-administered questionnaire was used to collect the data, which was then analysed through SmartPLS 3.2.9. Importance-performance matrix analysis was applied as a post-hoc procedure to gauge the importance and performance of the exogenous constructs. The results revealed that perceptions of m-learning’s learning content quality, user interface, and system’s connectivity affect the perceived mobile usefulness and easiness which in turn affects ER. This paper validates MTAM in the field of education by integrating MTAM with pedagogy and technology attributes under a social emergency setting such as the COVID-19 pandemic. In addition, the current research explains users' ER rather than behaviour intention which is commonly adopted in past studies.     

Why DO citizens engage in government social media accounts during COVID-19 pandemic? A comparative study

The worldwide COVID-19 outbreak that crushed the global economy and healthcare increased the public willingness to acquire more information and enthusiasm to engage online among billions of users through social networks. As more towns, cities, and regions turn to lockdown, government social media accounts (GSMAs) develop as a trustworthy source to obtain information about the COVID-19 pandemic. Thus, investigating the determinants and consequences of citizens' participation behavior on GSMAs is essential. Drawing on the self-determination theory (SDT) and civic volunteer model (CVM), we examine the influence of motivational factors (i.e., intrinsic extrinsic) on citizens' participation behavior on GSMAs, which leads to online civic behavior. Comparative research between China and Pakistan is carried out using data collected through an online survey. This study shows that information-seeking, political benefits, self-development, altruism, and perceived reciprocity are the critical antecedents of citizens' participatory behavior on GSMAs in both countries, resulting in online civic behavior. Furthermore, moderating results reveal that perceived connectivity moderates the relationship between certain motivational factors (intrinsic and extrinsic) and citizens' participatory behavior on GSMAs, whereas trust in government moderates the relationship between participatory behavior on GSMAs and online civic behavior during COVID-19. Theoretical and managerial implications are discussed in detail.     

COVID-19 pandemic and the cyberthreat landscape: Research challenges and opportunities

Although cyber technologies benefit our society, there are also some related cybersecurity risks. For example, cybercriminals may exploit vulnerabilities in people, processes, and technologies during trying times, such as the ongoing COVID-19 pandemic, to identify opportunities that target vulnerable individuals, organizations (e.g., medical facilities), and systems. In this paper, we examine the various cyberthreats associated with the COVID-19 pandemic. We also determine the attack vectors and surfaces of cyberthreats. Finally, we will discuss and analyze the insights and suggestions generated by different cyberattacks against individuals, organizations, and systems.