Personalized teaching-guiding system based on non-zero jumping-off point in network teaching

Abstract

A course guiding system based on non-zero start point and knowledge point in network education belongs to the field of computer technologies. The invention includes an initial knowledge domain construction module, an individualized knowledge domain generation module, an individualized learning route generation module, a history learning record module, a knowledge structure level evaluation module, and an individualized learning resource recommendation module. With knowledge point as the core, the invention constructs courses into the corresponding knowledge point tree and graph among knowledge points; learners are examined on knowledge points at each stage; by the analysis of learners' learning data and test of learning effect, the system obtains the learning status of learners at each knowledge point, their learning prediction result and knowledge point structure, recommends the corresponding learning resources and students to learners, and helps learners form the self-organized learning community to enhance the learning quality.

Description

technical field [0001] The invention relates to a system in the field of computer application technology, in particular to a personalized teaching guidance system based on a non-zero starting point in network education. Background technique [0002] Modern distance education has become an increasingly popular way of lifelong learning. However, due to the wide range of network users, teachers cannot predict the original knowledge structure and level of online learners, and the original knowledge level of network learners is uneven. Many learners have a certain foundation for learning content, that is, a non-zero starting point. At the same time, in the distance teaching under the network environment, learners are faced with a large number of network learning resources. If there is no perfect guidance process, it is difficult for learners to systematically grasp the knowledge structure of the course. Therefore, it is very important to design a personalized guidance system bas...

AI Technical Summary

Problems solved by technology

Its shortcomings are: (1) There is no uneven level of knowledge structure for online learners, which is not conducive to personalized guidance; (2) The teaching content is not combined according to knowledge points, so that learners lack the overall knowledge structure. Clear understanding is not conducive to learners' learning; (3) There is no online evaluation of learners' learning situation, and no historical learning records are kept, so as to analyze learners' mastery of knowledge points, so that learners can understand their own learning process. (3) There is no recommendation function for relevant learning resources for learners and no mechanism for learners to communicate with each other

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