Introduction to Jiang Qing

Jiang Qing, the director of Big Data Research Laboratory of China Statistics Information Service Center (CSISC), is an EMBA alumna and an enterprise supervisor of MBA School, ZUEL. She is also a specialistin public relations and a practitioner and researcher of big data.

In recent years, big data has become a hot topic and a word that can draw the public’s attention and increase the authority of your statement. The influence of big data on production and life are obvious. But in the field of education, big data is just beginning.

Education is a complicated issue, an issue that is related to the national welfare and the people’s livelihood. Big data has great potential in reshaping education. So, how could big data drive education reform? What challenges and difficulties will big data face in the field of education? In order to figure out the answers to these questions, the reporter from China Education Daily had an exclusive interview with Jiang Qing, a specialist in big data.

Educational big data is at its preliminary stage of development

Reporter: Big data has become a hot top. However, many people are not familiar with it. So, what is big data? And what are the differences and connections between big data and small data in the field of education?

Jiang Qing: Big data or small data are not describing the size of the data. They are different was of information processing and decision making. In educational big data, different groups of data are connected properly, thus making them more valuable to us. However, in educational small data, different groups are isolated, making their analysis less objective and their values smaller.

Reporter: What are the influences of big data on education reform and development?

Jiang Qing:Although educational big data is at its preliminary stage of development, it will bring great changes to traditional education. Besides improving education efficiency and research effectiveness, big data may even bring lifelong individualized education. Besides online education, it can be used in the field enrollment, budget planning, students service to ensure the transparency. And it will have great influences on students’ study, faculty’s teaching and research, campus governance, interaction between school and parents, education decision, employment management, enrollment management, and so on.

Reporter: Can big data overcome the weakness of traditional data and focus on students’ personal development?

Jiang Qing: Big data has been applied to public education in the U.S. And they have planned to use $ 25 million from the financial budget to understand the influences of personality on students’ study.

Reporter: What can big data do in individualized teaching?

Jiang Qing: Researchers have developed five methods to establish a study analysis system to support study. These techniques will held education workers carry out individualized teaching.

Data distortion has to be dealt with

Reporter: We often say that we shall talk in accordance with truth and data. But does data equal truth? What is the relationship between educational big data and educational truth?

Jiang Qing: Educational big data is the logical summary of the facts of education. It is the collection, processing, research and application of raw data. If big data is appropriately employed, it can reflect the facts of education and thus provide references for us when making decisions.

Reporter: But how can we make sure that the data collected are objective and un-distorted?

Jiang Qing: It is not easy to get data. For college students, data collection is not a big problem. But for students of primary schools and high schools, it is very challengeable, because the collection of certain data is not only a legal issue, but also a moral issue.

Another problem is the number and techniques of data collector. The collection of data needs special channels and certain techniques. And for the educational authorities, the collection and confirmation of data depend on network of lots of educational districts and researchers in China.

The core challenge lies in the analysis of data and its visual presentation

Reporter: How to protect privacy during the collection of data?

Jiang Qing: First of all, we shall respect the privacy. In order to achieve this aim, we advocate that the data shall be processed before releasing it to the public. The data presented to the public shall be data products, instead of specific data. Meanwhile, the organizations which collect and possess the data shall increase their legal awareness and enhance the protection of data.

Reporter: How should we reasonably analyze and employ the collected data?

Jiang Qing: Using external and internal data, education authorities can optimize the allocation of education resources, improve the development of education, guide the growth of students and share study materials. With the help of educational big data, we can establish “digital education map” to optimize the allocation of education resources, “smart education platform” to improve the management of education results, and “performance appraisal system” to promote the innovation of scientific research.

Uncontrolled use of educational big data will lead to risks

Reporter: There is a tendency which regards big data as almighty. But educational big data also has its limitation, because the growth of a people is far more completed than what we can imagine. In the field of education, is there anything that big data cannot explain or predict.

Jiang Qing: Education big data can fix the education process to make it more appropriate. But it is indeed not almighty. For example, big data may predict that a student will become a scientist in the future. However, it may turn out that he becomes an actor. As an individual, we are changing from time to time. But the educational data that have been collected will remain the same.

Reporter:Schoenberg said: “Our prediction over possibilities may increase the inequality of education. The first threat of education data is not the inappropriate release of information, but the fact that it will be limited by our past and therefore denies our ability of making progress, developing and changing.” What do you think?

Jiang Qing: Parents and experts have been showing great concern over the protection of students’ privacy and the tracking of students’ academic performances, because they are potential threats to students’ opportunities. Big data will not only enlarge these problems, but also change their nature. As time passes, we will change our view and reshape our values. Big data shall be used together with experience, otherwise its value will be limited and it may lead to risks in decision making.

Educational of big data has to overcome difficulties

Reporter: What are the prospects of educational big data in China? What are the difficulties?

Jiang Qing: The government has alreadydesignated the development of big data industry as a national strategy. Therefore, various guidance and supports will be offered. Big data in educational field will face similar difficulties as it does in other fields: the development of big-data thinking, the cultivation of big-data talents, the establishment of related standards and the formulation of related laws and regulations.

Reporter: How to overcome these difficulties?

Jiang Qing: In order to overcome difficulties, different measures shall be taken accordingly. For the purpose of developing big-data thinking, educational authorities could organize training programs, formulate policies and hold academic conferences to introduce the application of big data in education field. For the purpose of cultivating big-data talents, some universities and institutes have already initiated their talents cultivation programs. Besides these on-campus programs, some training programs shall be offered to personnel who have already worked in the area of statistics and information. Standards of big-data industry shall be established with the cooperation of big-data practitioners and the objects of big data. Laws and regulations shall be formulated to solve the problems of big-data industry, such as the protection of privacy.