Targeted work generation method and system based on big data

Abstract

The invention relates to a targeted work generation method and system based on big data. On the basis of a big data method, big data analysis is carried out on knowledge structures and learning processes and states of a great number of students, learning rules of different kinds of students are grasped; targeted precise works are arranged for the students according to the rules on the basis of learning history and thought characteristics of the students; and the students are assisted in learning. Through continuously accumulated samples, comprising continuously collected learning state data and generated targeted works, a work generation model is trained and updated, so the work generation model can be updated along with the real-time levels of the students, thereby obtaining the precise targeted works all the time. According to the method and the system, the learning state data of the students is collected, and teaching information, such as teaching audios / videos and blackboard-writings of teachers, is collected synchronously, so the correspondence between the learning states of the students and the explaining content, explaining modes, content and details of the teachers is learned, thereby helping the teachers to adjust teaching methods and content.

Description

technical field [0001] The present invention relates to data screening technology, and more specifically, to a method for generating targeted jobs based on big data, and a system for generating targeted jobs based on big data. Background technique [0002] In an environment that pays more attention to teaching students according to their aptitude, the general teaching in the school classroom cannot meet the different teaching priorities of different students. Within a limited time, teachers cannot complete targeted teaching for students of different levels, especially in terms of homework. Common means of testing learning outcomes and training students for self-study, common homework cannot accurately reflect the real learning situation of each student, and the learning effect is discounted. [0003] Students usually use small-class after-school tutoring to make up for it, which not only increases the burden on students and financial pressure, but also in the context of non-...

AI Technical Summary

Problems solved by technology

[0002] In an environment that pays more attention to teaching students according to their aptitude, the general teaching in the school classroom cannot meet the different teaching priorities of different students. Within a limited time, teachers cannot complete targeted teaching for students of different levels, especially in terms of homework. It is a common means of testing learning outcomes and training students to learn by themselves. Common homework cannot accurately reflect the real learning situation of each student, and the learning effect is discounted.

[0003] Students usually use small-class after-school tutoring to make up for it, which not only increases the burden on students and financial pressure, but also in the context of non-compliant extracurricular tutoring by teachers and in the tutoring industry that lacks the participation of regular teachers, uneven non-regular teachers It is also difficult to guarantee the quality of teaching

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