Education big data portrait-based learning condition evaluation method and device

Abstract

The invention provides an education big data portrait-based learning condition evaluation method and device. The method comprises the following steps: S1, collecting education basic data; s2, determining the type to which the collected education basic data belongs from preset types; s3, inputting the education basic data of the determined type into the analysis model obtained by training, and obtaining an analysis result output by the analysis model, the analysis model comprising a personal analysis model, a volume analysis model, a class analysis model, a subject analysis model, a school analysis model and a comprehensive report analysis model; s4, based on the analysis result, evaluating the learning condition of the student. According to the invention, deep analysis and mining of the education basic data are realized, integration of the education basic data is realized, and the information data sharing barrier existing in provincial and municipal education bureaus, school commanders, grade dominators and the like is broken; thus, students, teachers, parents and education bureau personnel can conveniently know respective required conditions, and benign collaborative development of learning, education and management is achieved.

Description

【Technical field】 [0001] The present invention relates to academic education technology, in particular to a learning evaluation method and device based on educational big data portraits. 【Background technique】 [0002] Big data portrait is a model based on a large amount of data. Educational big data portrait refers to an educational model based on a large amount of basic data in the field of education. Educational big data portraits have guiding significance for students, teachers, parents and educational institutions. [0003] However, at present, there are barriers to data sharing of information among provincial and municipal education bureaus, school principals, grade directors, etc., and a large amount of basic educational data cannot be integrated, let alone the analysis and mining of basic educational data. Moreover, the traditional educational evaluation model is relatively simple. School teachers are busy with teaching and can only learn about students' test resul...

AI Technical Summary

Problems solved by technology

[0003] However, at present, there are barriers to data sharing of information among provincial and municipal education bureaus, school principals, grade directors, etc., and a large amount of basic educational data cannot be integrated, let alone the analysis and mining of basic educational data

Moreover, the traditional educational evaluation model is relatively single. School teachers are busy with teaching and can only understand the students' test results, but cannot fully understand the reasons for the students' results, so they cannot really prescribe the right medicine to help students improve their grades.

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