An intelligent recommendation method of learning resources based on learner model

Abstract

The invention discloses an intelligent recommendation method of learning resources based on a learner model, which comprises the following steps: (1) managing information of the learner and the learning resources, establishing a database, and storing electronic teaching material data, homework and examination data, digital resource data, interactive exchange data and electronic archive data in classification; 2, establishing a learner model base on database data, wherein that learner model comprises personal information, academic information, relationship information, preference information, performance information and work set information; 3, establishing a recommendation model, integrating different recommendation method, and setting different recommendation methods according to different learning situation; Step 4: judging the learning situation of the learner according to the information in the learner model and make recommendation. The invention is based on learner information recommendation, has high recommendation matching precision and realizes automatic matching. At the same time, different recommendation methods are used in different learning contexts to achieve high recommendation efficiency and intelligent recommendation.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a learning resource intelligent recommendation method based on a learner model. Background technique [0002] With the development of the Internet, online learning has become the normal state of learning. Many teaching resources for online learning are constantly increasing. Students often face a large number of teaching resources when they are studying. Because each student's personal situation is different, the teaching resources needed Different, in many cases, it is impossible to correctly select the teaching resources that suit them. Users need to be able to choose a method that suits their own teaching resources. [0003] In the existing teaching resource recommendation methods, the search is performed based on the keywords input by the user, but the user does not have a correct understanding of all his own situations, and there is always a lot of noise in the matching proces...

AI Technical Summary

Problems solved by technology

[0002] With the development of the Internet, online learning has become the normal state of learning. Many teaching resources for online learning are constantly increasing. Students often face a large number of teaching resources when they are studying. Because each student's personal situation is different, the teaching resources needed Different, many times it is impossible to choose the teaching resources that suit them correctly, and users need to be able to choose the teaching resources that suit them.

[0003] In the existing teaching resource recommendation methods, the search is based on the keywords input by the user, but the user himself does not understand all his own situations correctly, and there is always a lot of noise in the matching process or only part of the teaching resources are found. As a result, the efficiency of user matching is low, and users' satisfaction with recommended teaching resources is not high, and accurate matching of users cannot be achieved.

[0004] Moreover, the learning process is divided into stages. Different learning stages and different learning situations have different needs of learners. A single recommendation method is not suitable for all learning situations.

Images