scholarly journals Application of Big Data in Online Education in China

Author(s):  
Lingling Dong ◽  
Jiachen Han ◽  
Xiaohui Zhang
2017 ◽  
Vol SED2017 (01) ◽  
pp. 5-7
Author(s):  
Ruchi Jain ◽  
Neelesh Kumar Jain

The concept of big data has been incorporated in majority of areas. The educational sector has plethora of data especially in online education which plays a vital in modern education. Moreover digital learning which comprises of data and analytics contributes significantly to enhance teaching and learning. The key challenge for handling such data can be a costly affair. IBM has introduced the technology "Cognitive Storage" which ensures that the most relevant information is always on hand. This technology governs the incoming data, stores the data in definite media, application of levels of data protection, policies for the lifecycle and retention of different classes of data. This technology can be very beneficial for online learning in Indian scenario. This technology will be very beneficial in Indian society so as to store more information for the upliftment of the students’ knowledge.


2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wen Li ◽  
Robyn Gillies ◽  
Mingyu He ◽  
Changhao Wu ◽  
Shenjun Liu ◽  
...  

Abstract Background The COVID-19 pandemic posed a huge challenge to the education systems worldwide, forcing many countries to provisionally close educational institutions and deliver courses fully online. The aim of this study was to explore the quality of the online education in China for international medical and nursing students from low- and middle-income countries (LMICs) as well as the factors that influenced their satisfaction with online education during the COVID-19 pandemic. Methods Questionnaires were developed and administered to 316 international medical and nursing students and 120 teachers at a university in China. The Chi-square test was used to detect the influence of participants’ personal characteristics on their satisfaction with online education. The Kruskal–Wallis rank-sum test was employed to identify the negative and positive factors influencing the online education satisfaction. A binary logistic regression model was performed for multiple-factor analysis to determine the association of the different categories of influential factors—crisis-, learner-, instructor-, and course-related categories, with the online education satisfaction. Results Overall, 230 students (response rate 72.8%) and 95 teachers (response rate 79.2%) completed the survey. It was found that 36.5% of students and 61.1% of teachers were satisfied with the online education. Teachers’ professional title, students’ year of study, continent of origin and location of current residence significantly influenced the online education satisfaction. The most influential barrier for students was the severity of the COVID-19 situation and for teachers it was the sense of distance. The most influential facilitating factor for students was a well-accomplished course assignment and for teachers it was the successful administration of the online courses. Conclusions Several key factors have been identified that affected the attitudes of international health science students from LMICs and their teachers towards online education in China during the COVID-19 pandemic. To improve the online education outcome, medical schools are advised to promote the facilitating factors and cope with the barriers, by providing support for students and teaching faculties to deal with the anxiety caused by the pandemic, caring for the state of mind of in-China students away from home, maintaining the engagement of out-China students studying from afar and enhancing collaborations with overseas institutions to create practice opportunities at students’ local places.


Author(s):  
Jyotsna Talreja Wassan

Big data is revolutionizing the world in the internet age. The wide variety of areas like online businesses, electronic health management, social networking, demographics, geographic information systems, online education, etc. are gaining insight from big data principles. Big data is comprised of heterogeneous datasets which are too large to be handled by traditional relational database systems. An important reason for explosion of interest in big data is that it has become cheap to store volumes of data and there is a major rise in computation capacity. This chapter gives an overview of big data ecosystems comprising various big data platforms useful in today's competitive world.


2020 ◽  
Vol 25 (5) ◽  
pp. 595-600
Author(s):  
Jia Wen ◽  
Xiaochong Wei ◽  
Tao He ◽  
Shangshang Zhang

With the proliferation of the fifth generation (5G) communication technology, another boom of online education will come, and reshape our traditional learning model. Inspired by the literature on online education platform, this paper establishes a model for the factors affecting the acceptance of online education platform among college students based on the theory of planned behavior (TPB), and put forward several hypotheses on the influence of multiple factors over the acceptance. Then, a scientific questionnaire was designed and distributed online to college students. The survey data were subject to descriptive analysis and correlation analysis. The results show that college students have considered online education platforms an important learning tool; the acceptance of online education platform among college students is positively affected by such factors as personal value, course satisfaction, teacher quality, social influence, and self-efficacy. The research results provide a good reference for the development of online education in China.


Author(s):  
Xi Chen ◽  
Erya Xia ◽  
Wen Jia

In the information age, the proliferation of online education platforms is accompanied by various problems. This paper aims to solve the problems of online education platforms, making them more useful and adaptable. Targeting at a key online education platform (SmartStudy) in China, the authors conducted a questionnaire survey among users on their utilization and perception of online education platforms. Based on the survey data, the current state of the platform was summarized, followed by an analysis on the degree of impact from each factor on the selection between platforms. Next, the platform development and user satisfaction were discussed in the light of platform security, credit rating and user experience. Finally, several suggestions were put forward to improve the online education platform. The research results are of great importance to the development of online education in China.


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