Smartbi Graduate Teaching Big Data Service Platform

National policy：

In 2014, the Academic Degrees Committee of the State Council and the Ministry of Education issued the "Opinions on Strengthening the Quality Assurance and Supervision System of Degree and Postgraduate Education", requiring random inspections of doctoral and master’s degree theses, strengthening the quality awareness of degree-granting units, tutors and graduate students, and strengthening Degree-granting management to ensure the quality of degree-granting.

In December 2016, General Secretary Xi Jinping put forward at the National Conference on Ideological and Political Work in Colleges and Universities: "The ideological and political work of colleges and universities is related to the fundamental issue of what kind of people are cultivated in universities, how to train them, and for whom. The central link is to run ideological and political work through the entire process of education and teaching, to realize the whole process of educating people and all-round education and strive to create a new situation in the development of China's higher education. Building morality is the fundamental task of China's education, and it is also the theoretical and practical guide for ideological and political education in the new era. "

In 2018, the Ministry of Education clearly stated in the "Education Informatization 2.0 Action Plan": "In order to thoroughly implement the spirit of the 19th National Congress of the Communist Party of China, accelerate the modernization of education and the establishment of a strong education country, promote the development of educational informatization in the new era, promote innovation-driven development, and combine the national "Internet +", big data, new generation of artificial intelligence and other major strategic task arrangements and the requirements of "National Medium and Long-term Education Reform and The development plan outline (2010-2020)", "the 10-year development plan of education informatization (2011-2020)" and other documents, formulated this plan. "

Project Background:

Postgraduate education is a high-level and high-level existence in the educational structure and has an important mission of cultivating high-level innovative talents for the country. In the context of the construction of "double first-class", colleges and universities are paying more and more attention to the cultivation of graduate students and the improvement of the quality of graduate students. Strengthening the construction of disciplines, building a first-class faculty, optimizing talent training, improving the level of scientific research, and continuously improving the quality of postgraduate education have gradually become the goals of postgraduate training in various universities. Therefore, it is necessary to build a platform that can reflect the quality of graduate education to reflect the problems in graduate education, so as to effectively improve the quality of graduate education.

Customer pain points：

● Irregular or missing postgraduate data

Many data in colleges and universities are non-standard EXCEL versions or paper versions, and there is no unified planning and management, which leads to excessive redundant data or lack of necessary data in the monitoring of postgraduate teaching. Therefore, it is also necessary to form a systematic management database that includes collection, reporting, and monitoring. In addition, in the process of postgraduate training, due to the untimely data collection, many postgraduate research data statistics are missed, which requires the use of crawler technology to crawl graduate research data.

● Limited evaluation index for postgraduate teaching quality

At present, in the evaluation system of postgraduate teaching, the evaluation indexes of each university are too limited. For example, the quality of teaching is only reflected by grades, enrollment rate or employment rate. This can cause colleges and universities to be unable to truly recognize their problems in various aspects of graduate training.

● Unreasonable Curriculum Design

Many colleges and universities offer unreasonable courses for postgraduates with professional degrees. The main reason is that they don’t set courses according to the training objectives and characteristics of postgraduates with professional degrees. In teaching, the courses are based on theoretical lectures, lacking practical courses and lack of interaction. As for teaching approach, the curriculum design is not distinguished from that of academic graduate students, and the courses are still conducted in accordance with the traditional teaching method.

● The instructors are powerless and incapable

In the process of graduate training, tutors play a pivotal role. The quality of graduate education largely depends on the level of graduate tutors and their dedication. With the expansion of postgraduate enrollment, the selection threshold for postgraduate tutors is lowered. Therefore, the problem of teacher-student ratio in some majors is very prominent, and some tutors are even laissez-faire to graduate students, which leads to poor graduate education quality.

Solution：

The postgraduate teaching big data service platform builds a platform to achieve three unifications.

Three unifications: unify data sources, data definitions, and postgraduate teaching display models during the entire platform establishment process.

A platform: The analysis platform enables analysts to complete the analysis and decision-making of the whole process of postgraduate teaching on this platform, and complete various subjective business analysis and presentations.

Figure: Architecture of A Big Data Service Platform for Postgraduate Teaching

Through the construction of a postgraduate teaching big data service platform, a postgraduate teaching database with integration of collection, reporting and management is built. This changes the current situation where data is scattered in various offices, projects, and management personnel, avoids data damage, missing, and leaks, and ensures the security, integrity and continuity of data related to postgraduate students in universities.

This platform provides seven major functions: leadership cockpit, quality monitoring, postgraduate portrait, tutor portrait, theme analysis, prediction and early warning, and quality report for graduate teaching quality analysis. 

Among them, the leadership cockpit displays real-time core indicators that leaders care about and that reflect the teaching status of graduate students, and it provides data basis for decision-making (the application is shown in the figure below). The quality monitoring function monitors and analyzes the key indicators of the input, process and output of the graduate student training process. The portraits of graduate students and tutors comprehensively display the characteristics of each student and tutor, helping managers to understand the situation of teachers and students comprehensively and quickly. Topic analysis uses association mining analysis to form a topic analysis report. Prediction and early warning are carried out on the management of students and mentors from graduate school and tutor training. In addition, this platform regularly provides postgraduate quality reports to the leaders and managers of the school. Through the vertical and horizontal analysis and comparison of these major functions, it is possible to give full play to the aggregation of data and discover deeper problems in the process of graduate training.

Figure: Functions of the Graduate Teaching Big Data Service Platform

Figure: Leadership Cockpit

Improve the platform role permission assignment function. Different postgraduate teaching analysis results can be shown to corresponding personnel, according to different roles and different analysis content, to ensure data security and confidentiality.

Platform features:

● Postgraduate teaching model analysis store

The postgraduate teaching model analysis store developed with Smartbi products converts the required postgraduate teaching analysis model into a visual model, which is a model innovation in the industry.

● Perfect indicator system

In the graduate teaching big data service platform, the quality monitoring indicators and observation points are based on the indicator system of the National Graduate Teaching Quality Big Data Analysis Platform of the Ministry of Education's Degree Center, combined with the university’s own characteristics and needs, discussed with experts, and finally established the school-level indicator system.

Figure: The Quality Index System of Graduate Education

● Cross-business system associated query

The big data service for postgraduate teaching analyzes data mainly for reporting by various business departments of colleges and universities, which requires extracting tables of different data for associated queries in data analysis. In the past, data in different databases were converted to the same database, which was time-consuming and labor-intensive, and personnel who were not familiar with the data could not operate it. So now Smartbi implements cross-database query to solve this problem very well. Through Smartbi, different types of databases can be directly linked by dragging and dropping tables without conversion.

Figure: Cross-business system associated query

● High-performance mining components

A variety of algorithm components and mining components are built in the system. After the data is imported into the platform, the model process can be flexibly established to solve the industry's own business scenarios by dragging and dropping with the help of components.

Figure: Mining Components

Value：

● Corresponding national postgraduate education policy guidelines

1.Reform the evaluation mechanism of graduate education and establish a quality assurance system with training units as the main body. Apply big data analysis technology to the evaluation of the quality of higher education personnel training and promote the in-depth development of higher education reform.

2.The analysis of big data for graduate education covers the whole process of graduate education quality management, which helps to make accurate attacks after discovering education quality problems.

● Establish a quantitative evaluation of the teaching quality of graduate students

1.The quality monitoring of the input, process and output of graduate students is carried out to avoid subjective judgments and make the problems in the graduate training process more objective.

2.Quantitative quality monitoring and evaluation are aimed at the whole process of graduate training, not at a certain stage.