In recent years, many typical big data applications have emerged in the field of education, such as learning analysis in the field of teaching information, behavior files, ability assessment, personalized services in the field of education management information, teaching and research support, decision support, etc. The development of educational big data is showing a vibrant scene.
Educational big data typical application
From the perspective of development, the practice of colleges and universities is a touchstone for promoting the application of big data in the field of education, and has important reference value for other education stages. At present, the big data application cases of colleges and universities are mainly concentrated in the following three aspects.
First, it is an educational big data application for student management. Such applications are often referred to as smart grids and grid management applications. They focus on all aspects of college student management, and compose the behavioral trajectories and development processes of life, school, and thought in the whole life cycle of students. Counseling, forming a new model of collaborative and sustainable smart management and guiding development. At present, some colleges and universities have established functional applications such as student portraits, student behavior warnings, student family economic status analysis, student comprehensive data retrieval, student group analysis, etc., from mixed-oriented groups to feature-oriented group management, to better distinguish students in the profession. The potential for learning or employment, providing students with a personalized management and training program.
Second, it is an educational big data application for campus services. Such applications mainly through real-time crawling and analysis of various types of data on campus, monitoring campus public opinion, optimizing campus resource allocation, providing construction management decisions for the school, and demonstrating the school's humanistic care. Some colleges and universities have already carried out relevant functional pilots. Among them, the integrated school performance display function can enable managers to monitor the school students' situation, course conditions, scientific research results, awards, and teaching staff through integration of basic data analysis and behavioral data analysis. Intuitive understanding and comparison, help students to understand themselves and their differences from rigorous data analysis, and feel the humanistic care and change brought by informationization.
Second, it is an educational big data application for teaching and research. Some colleges and universities began to try to carry out data analysis based on teaching resources according to various professional enrollment plans, this year's start-up plan, and teaching arrangements in previous years, and give predictions and warnings for various resources in teaching activities. There are also universities that are exploring the introduction and aggregation of various types of scientific research data, establishing multi-dimensional data analysis services for university scientific research indicators, and accurately finding external talents that are more in line with school needs.
Thoughts on the development of educational big data
From the above development status and typical applications, it is not difficult to see that there is a certain contrast between the ideal and the actual state of the current educational big data. To better play the role of educational big data in promoting the development of education, on the one hand, it is necessary to further emphasize the educational information. The supporting role of infrastructure, on the other hand, needs to re-examine and reflect on the essential needs of big data in education.
Education big data infrastructure support
If education big data is to educate the high-rise buildings in this “parkâ€, then the information infrastructure is “water, electricity, coal†and three links, there is no perfect infrastructure structure, and education big data may be “little buildings†in the future. Information island.
The infrastructure of education informatization includes basic services such as cross-domain identity authentication, authorization, time, interface, security, and soft assets such as application system data, machine-generated data, user behavior data, and Internet data. A variety of business systems in the field of education ensure the robust operation and development of each system and promote the interconnection of these systems. Infrastructure construction helps to fundamentally address the critical issues facing education big data applications, which can help clean up the common stumbling blocks in big data construction.
The essential needs of educational big data
Educational big data is not a theoretical level, and it must bring about revolutionary changes in the field of education. It must be specifically targeted to specific educational issues in the current education field. We believe that from micro to macro, education big data should mainly solve four levels of problems.
First, how to better promote the personal development of learners. This is the core and most essential appeal of education, and it is also the most difficult thing to overcome in the current education big data application. The approach is to in-depth study and focus on learner behavior data, including the learning information of learners in the learning process, learning activities, learning process and the learning environment with which they interact, to achieve learner-centered learning The whole process of data acquisition, coding, storage, analysis and feedback, so as to go deep into the behavior mechanism layer to face the learners have an important impact.
Second, how to better explore the rules of education and teaching, and improve the quality of education and teaching. Learner behavior data only focuses on the “learning†part, while school education includes both teaching and learning activities and other content related to these activities. This level of data can be called educational behavior data. With the application of relevant educational behavior data, it is possible to collect, record and analyze teaching and learning and related educational behaviors, better outline the true form of education and teaching, effectively promote teaching informationization, and deeply promote the transformation of teaching and learning methods.
Third, how to better improve the level of education management services and education governance. Based on the data on educational behaviors, this paper further integrates various educational management and educational service data, and uses data to improve the quality of education and education and the level of educational management services, so as to better promote the modernization of educational governance systems and educational governance capabilities.
Fourth, how to better formulate educational decisions, promote education reform and development, and support the national development strategy. This is the most macroscopic category of educational big data applications, and it is open to all education-related data.
For different educational issues, the goals, subjects, and data types of educational big data applications at different levels are different. At a finer granularity, educational big data applications at all levels need to be more flexible and targeted based on actual conditions.
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