Practical effect evaluation and learning path recommendation system and method based on cognitive diagnosis

A learning path and recommendation method technology, applied in the fields of cognitive diagnosis, smart education and personalized learning, can solve problems such as lack of subject learning, teachers' inability to provide personalized guidance, and reduced learning completion

Active Publication Date: 2020-03-27
SUN YAT SEN UNIV
View PDF5 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional education ensures a relatively complete knowledge acquisition process for advanced learners through teachers' teaching, supervision and evaluation processes. However, it is difficult to capture learners' accurate cognition of various knowledge by relying on test scores in general, and

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Practical effect evaluation and learning path recommendation system and method based on cognitive diagnosis
  • Practical effect evaluation and learning path recommendation system and method based on cognitive diagnosis
  • Practical effect evaluation and learning path recommendation system and method based on cognitive diagnosis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0098] The first aspect of the present invention discloses a practical effect evaluation and learning path recommendation system based on cognitive diagnosis, such as figure 1 As shown, including extended feature preprocessing model, deep learning tracking model, knowledge network construction model and path recommendation model;

[0099] The extended feature preprocessing model uses a tree model to predict learners' answers to exercises under the condition of heterogeneous features based on the learner's historical interaction records, and obtains a preliminary prediction of the learner's cognitive ability, and compares the prediction results with the original The sequence of exercise answers is used as the input of the deep learning tracking model;

[0100] The deep learning tracking model is input to the neural loop network to learn the knowledge state of the learner according to the information output by the extended feature preprocessing model, and the hidden unit h is co...

Embodiment 2

[0104] The second aspect of the present invention provides a cognitive diagnosis-based practice effect evaluation and learning path recommendation method, including the following steps:

[0105] S1. The extended feature preprocessing model predicts the learner’s answer to the exercises under the condition of heterogeneous features according to the learner’s historical interaction records, obtains the preliminary prediction of the learner’s cognitive ability, and uses the prediction result and the original exercise answer sequence as The input of the deep learning tracking model;

[0106] S2. The deep learning tracking model inputs the information output by the extended feature preprocessing model to the neural loop network to learn the knowledge state of the learner, and the hidden unit h is activated through the sigmoid activation function t Pass to the fully connected layer to get the output y t , which shows the cognitive ability of the learner to the knowledge concept, an...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a practical effect evaluation and learning path recommendation method based on cognitive diagnosis. The practical effect evaluation and learning path recommendation method comprises an expansion feature preprocessing model, a deep knowledge tracking model, a knowledge network construction model and a path recommendation algorithm based on cognitive ability. The expansion feature preprocessing model performs primary evaluation of cognitive competence according to skill attributes in a learner test process, and introduces personalized difference information into the diagnosis model. And the deep knowledge tracking model predicts the knowledge mastery ability of the learner according to the test sequence and the heterogeneous features of the implicit coding, and the knowledge mastery ability serves as a basis of learning guidance. The exercises and knowledge network construction model provides a global map of scientific thinking, and the cognitive diagnosis is combined to recommend a learning path to a learner, so that the cognitive ability difference in the learning process is considered, and the logic of a knowledge structure is followed.

Description

technical field [0001] The present invention relates to the fields of cognitive diagnosis, smart education and personalized learning, and more specifically, to a method for evaluating practical effects and recommending learning paths based on cognitive diagnosis. Background technique [0002] The Internet education model has broadened and improved the form and content of traditional education, and lowered the threshold for education, but at the same time, it has shown disadvantages in the follow-up improvement, evaluation and supervision of teaching. Traditional education ensures a relatively complete knowledge acquisition process for more advanced learners through teachers' teaching, supervision and evaluation processes. However, it is difficult to capture learners' accurate cognition of various knowledge by relying on general test scores, and teachers cannot target specific knowledge for each individual. The basic differences of students provide completely personalized gui...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06Q50/20G06F16/9535G06F16/901G06N3/04G06N3/08
CPCG06Q50/205G06F16/9535G06F16/9027G06N3/08G06N3/045Y02D10/00
Inventor 吴迪方静如
Owner SUN YAT SEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap