With the rapid development of society, the spread of information has accelerated. Today, data has penetrated every industry and every field of business and has become a major production factor. Big data has been in use for some time in the industries of finance, communication, and logistics. However, their application in education is relatively lacking. Against the background of using big data to develop new businesses and innovating operational modes in all industries, how should the education industry drive the development of education in China in order to enter the new big data era?
On 13th June 2018, the Seminar on Big Data Research and Practice in Distance Education was held at the Open University of China (OUC). The seminar was sponsored by the Engineering Research Centre for Technology Integration and the Application of E-Learning and Distance Education in China and co-sponsored by Huawei Technologies Co., Ltd., under the supervision of the OUC’s Information Technology Department. The theme of the seminar was discovering “big data potential · incubating big data projects · creating big data value.” About 200 people from relevant fields attended the seminar.
“According to UNESCO statistics from December 2017, 159 national qualification frameworks have been established, accounting for three-fourths of the 193 sovereign states. Fifty-seven countries within the “Belt and Road” agreement have established qualification frameworks,” Professor Zhang Weiyuan from Beijing Normal University said, indicating that qualification frameworks internationalise education and represents a trend in global education integration. The establishment of qualification framework levels and standards for vocational education by combining international standards and local characteristics to develop a professional development scheme, which are based on big data analyses and in conformity with job requirements, are conducive to changing the current disconnection between the development of vocational education professionals and the needs of society. It is beneficial to train vocational education professionals that meet the requirements of industries and enterprises, establish general quality standards for vocational education, and realise credit transfer among local, national and international vocational education institutions. The realisation of the integrated settlement plan will solve the disconnection between majors, course contents, and occupations by establishing a big data platform that matches talent development and vocational requirements.
Jiang Guozhen, executive head of the OUC’s Information Technology Department, gave a report entitled Education Big Data: Expectations and Challenges. He put forward four expectations: to obtain real big data, to record the entire learning process with the learning management system, to conduct more scientific education research based on the complete record of the education teaching process, and to drive education changes with big data. According to the introduction given by Jiang Guozhen, the features of big data are huge data volume, diversified data varieties, low value density, and rapid processing velocity. He cautioned that big data today is both developing fast and faced with development problems. Where is massive education data? How can high-quality big data be extracted? How can we construct a data analysis model? In addition, it is also necessary to develop good tools for data analysis.
“We have entered the big data era. According to Moore’s law of big data, global data totals will now double every 24 months or so,” Chen Liang, a big data expert from Huawei cloud EI underlined. “Enterprises have to improve their big data competency, mastering and analysing more data. Big data can help enterprises to more accurately anticipation their customers’ needs, to gain an insight into the market, and to innovate their products.” He indicates that big data can support the teaching of information technology as far as education is concerned. The teachers can improve their teaching competence through teaching applications, quality resource construction, and big data analysis. Teaching efficiency can be upgraded and the burden of teaching lightened through teaching applications, quality resources building, big data analysis, and family education. A new model of quality education resource supply will be gradually explored through the joint construction and sharing of famous teacher resources.
“Big data is increasingly penetrating traditional industries and driving changes to modes of production and management.” According to the introduction given by Jin Xin, advisory director of Taiji Government Administration Application and Support Department, China is paying greater attention to the development of big data and the number of government websites in China has risen to 84,000. Pilot smart city schemes have been carried out in nearly 300 cities. The number of internet users has surpassed 700 million. China has become one of the largest producers and collectors of data. Taiji Government Administration has launched Guangdong Smooth Project of E-Government Affairs, Hainan Provincial Government Affairs Big Data Public Service Platform, the Court Big Data Application Platform, Beijing Big Data Management Platform, and other big data service projects.
Professor Li Jianping from the Department of Mathematics of the School of Arts and Sciences of the National University of Defence Technology emphasises that every technological change promotes changes to the form of teaching and that MOOCs represent a new development direction for distance education. MOOCs have broken through restrictions of time and space by making use of the advantages of the internet. They are regarded as an effective means of solving educational contradictions. Many university teachers are enthusiastic about the development of MOOCs and thousands of learners can learn the same MOOC course together. Big data about learning behaviours has been accumulated thanks to the MOOC course platform. “MOOC big data research has covered a number of disciplines, including pedagogy, mathematics, statistics, data science, information theory, web science, anthropology, and learning theories. MOOC big data is of huge research value from the perspectives of application, science, and commerce.”
As a leading Chinese MOOC platform, Tsinghua University’s Xuetang online (xuetangx.com) has 12 million registered users. According to CTO Guang Jian, big data is something that they rely on. Due to the low value density, correlation analysis has to be conducted for various kinds of data in order to extract useful information. “We provide different data support for different roles using the data gathered. With this support, teachers can teach better and students can learn better. The teaching managers can make better management desicions and coordinate between the schools and courses. Our data can now cover every second of learning for each learner,” Guang Jian said.
Doctor Xu Pengfei from the National Engineering Laboratory for Cyberlearning and Intelligent Technology at Beijing Normal University proposed several reflections on big data. He believes that data shouldn’t be “big” for the sake of being “big” and that analysis can also be conducted on small data. Moreover, with the faster speed of computing and research and development, the overall cost of storing the data is becoming even lower. In addition, we should make big data small as early as possible. Sometimes we need big data technology, especially that of extensible storage and distributed computing, but we may not need it all the time. Some information may get lost during the course of ‘becoming small at the earliest possible time’ but the benefits outweigh the risks. In addition, we must guard against getting into the “big but deviated” trap. If we go deviated, it is valueless no matter how great the value is. It is no easy job to conduct a complete analysis and evaluation.
Deputy director Yuan Yaxing of the OUC Department of Information Technology elaborated on the concept and application of “panoramic perception.” According to his introduction, “perception” is the base of smart campuses. Only after further study of big data built on perception is it possible to upgrade to the level of “cognition” and thus make a “smart” campus. The OUC’s offline education system covering urban and rural areas conducts all kinds of management activities by making use of the cloud platform. “Panoramic perception” is needed to fully present all the management and the teaching progress from different perspectives. It is of top priority to build the perception model.
According to President Xiang Chunzhi from the School of Information Technology of Henan Radio and TV University (RTVU), the government has high requirements for the construction of a lifelong education system for all and the promotion of the well-rounded development of the Chinese people since the 18th CPC National Congress. The 19th CPC National Congress specifically laid out the need to improve continuing education and to step up efforts to build a learning society, providing an opportunity to match the big data and education industries. Over the past 30 years, Henan RTVU has followed the principle of open school education supported by modern information technology to serve the communities. Its education network covering urban and rural areas throughout the province is devoted to improving its support for lifelong education. In this way, it has laid a solid foundation for the creation of a lifelong education big data database for entrepreneurship and innovation in schools and to serve the construction of a national overall experimental area for big data. Last year, the “Big Data Base for Entrepreneurship and Innovation in Henan Province” was unveiled for construction at Henan RTVU.
Director Li Chunying of the OUC Business Department of Beijing OU shared an exploratory study of a school oriented to future education development trends. Where is the levelled education system for open universities? How can we supervise and control the teaching quality of open universities? How can we upgrade support for open universities? How can we demonstrate the integration of technology and education at open universities? How can we take a leading role? Based on the consideration of these questions, Beijing OU’s Innovation Centre for Open Education has been founded. 3.23 million yuan has been invested in the centre, which has an area of 155 square metres. The centre provides functions such as VR-based integrated administrative management, dynamic synchronous process monitoring of teaching quality based on big data analysis, and AI-based exploration of future online education mode. In the future, they hope to add quality evaluation analysis and introduce AI technology-aided teaching.
“Only by starting from evaluation data can continuous improvements made on course and teaching,” Huang Dafang, director of the Learner Support Center of Chengdu RTVU said while sharing the explorations into big data teaching and management that have been made by central city RTVUs. Huang Dafang introduced the path Chengdu RTVU was taking toward normalising online teaching behaviours and requirements, digitalising online teaching process and results, and making online teaching process and support hierarchical. He proposed applying big data thought processes to the management of online learning processes and making data the key to sorting out the structural management process, transitioning toward intelligent and smart management in a hope of raising the happiness index of students, teachers, and management personnel in online teaching and learning.
During the seminar, Professor Zhang Weiyuan from Beijing Normal University, executive head Jiang Guozhen from the OUC, general managers Zhang Yi and Chen Liang from Huawei EBG China Education System Department, and Jin Xin from Taiji Government Administration Support Department expressed their own views on topics such as “how can enterprises, universities, research institutes, and users coordinate to make their own contributions to the development of big data in education” and “how to carry out the genuine big data programmes.” Zhang Yi elaborated on Huawei Technologies Co., Ltd’s “platform + ecology” and its commitment to creating a “client-connection-cloud” platform and developing a big data ecosystem to help enterprises, universities, research institutes, and users of education big data to realise their own value in their own fields.
The launch ceremony for the Report on Big Data Development in China (2018) was held at the same time. The report project was jointly launched by the Engineering Research Centre for Technology Integration and the Application of E-Learning in Distance Education in China, the Professional Committee on University Distance Education of the China Association for Educational Technology, and Digital Fujian Big Data Research Institute for Lifelong Education. It aims to demonstrate the status quo, experiences, problems, trends, and future directions of big data policy, scientific research, practical application, industrial development, and talent cultivation in distance education in China. A big data research and application commonwealth in the field of distance education is being planned with the report as the platform to follow up further relevant activities, such as the publication of discussions, trainings, and results.
By Cheng Xueyun, OUC