Learner learning track quantification method based on three-dimensional knowledge network

Abstract

The present invention provides a learner learning track quantification method based on a three-dimensional knowledge network. The method comprises the following implementation steps: 1, constructing a complete knowledge network based on knowledge points; 2, constructing a teaching program based on the knowledge network according to teaching requirements; 3, constructing a learning path according to the teaching program; 4, recording an individual learner' s learning track according to the learning path in detail and feeding the learning track back to the system; 5, forming all the learners' historical learning track through recording of each learner's learning track through the system, performing multidimensional data analysis of all the learners' learning track through the system, deducing the learner group's total learning capability, assessing the difficulty of knowledge points included in the teaching program, the extent and the depth of the content and the reasonability matching with the learning group, and performing quantitative evaluation of difficulty reasonability of the teaching program; and 6, according to the individual learning track and the group learning track and analysis results of the individual learning track and the group learning track, and performing quantitative evaluation of a certain learner's learning investment time, investment effect and learning capacity so as to optimize the planning or regulate the extent and the depth of knowledge points required being covered in the learner's individual learning path.

Description

technical field [0001] The invention relates to the field of online or network teaching, and more specifically, to a method for quantifying learners' learning tracks based on a three-dimensional knowledge network. Background technique [0002] Although most of the existing MOOC and SPOC education platforms overcome some of the problems of traditional education, there are still many problems that cannot be overcome, such as: ① Failure to build a targeted platform for users Complete knowledge network, but only stay in teaching and providing services in simple units of courses; ②Failure to fully tap the relevance of knowledge points and build learning paths around knowledge points and their relevance, and record learning trajectories; ③Failure to provide Effective tools implement the educational philosophy that varies from person to person or teach students in accordance with their aptitude; the difficulty value of knowledge points is not quantified, but simply divided into sim...

AI Technical Summary

Problems solved by technology

Learners also cannot quickly obtain their own learning progress, learning effect comparison and feedback

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