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A textcnn-based student online learning behavior detection method and system

A detection method, student's technology, applied in digital data information retrieval, biological neural network model, unstructured text data retrieval, etc., can solve problems such as complex structure

Active Publication Date: 2022-07-08
FUZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In order to solve the problem of traditional models ignoring word order and context and complex structure, lai proposed a model of recurrent convolutional neural network (RCNN)

Method used

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  • A textcnn-based student online learning behavior detection method and system
  • A textcnn-based student online learning behavior detection method and system
  • A textcnn-based student online learning behavior detection method and system

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Experimental program
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Embodiment Construction

[0059] As shown in the figure, a TextCNN-based online learning behavior detection method for students is characterized in that: the detection method includes the following steps;

[0060] Step S1, log in to the online classroom, and crawl the speech information of the students as learning behavior data;

[0061] Step S2, preprocessing the data obtained by crawling to form preprocessing data;

[0062] Step S3, using the preprocessing data to pre-train the Skip-gram model;

[0063] Step S4, training to obtain the TextCNN classification model;

[0064] Step S5, using the TextCNN classification model to identify the online learning behavior of the students to be tested;

[0065] Step S6: Calculate the course comment activity index and the final score of each student according to the identification result.

[0066] The step S1 adopts the method of combining Selenium and browser driving to crawl the student's learning behavior data, specifically: first, enter the account number a...

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Abstract

The present invention provides a method and system for detecting students' online learning behavior based on TextCNN, the detection method and system include the following steps: Step S1, log in to the online classroom, and crawl the student's speech information as learning behavior data; Step S2, correct Crawling the obtained data preprocessing to form preprocessing data; Step S3, using the preprocessing data to pre-train the Skip-gram model; Step S4, training to obtain a TextCNN classification model; Step S5, using the TextCNN classification model to test the students' online Identify the learning behavior; step S6, calculate the course comment activity index and the final score of each student according to the identification result; the present invention designs a new course discussion score evaluation method by identifying the valid and invalid comments in the online classroom comment area, which is an online class discussion score evaluation method. The learning platform provides auxiliary evaluation tools to correct students' learning behavior and cultivate students' ability to think independently.

Description

technical field [0001] The invention relates to the technical field of behavior detection, and aims to provide an auxiliary evaluation tool for an online learning platform, in particular to a TextCNN-based online learning behavior detection method and system for students. Background technique [0002] At the beginning of 2020, online courses have become the main form for students to continue their education, and many high-quality courses have been published on MOOCs of Chinese universities. The course assessment content includes unit tests, final tests, video study duration, and course discussions. Course discussions are included in the assessment. The original intention is to cultivate students’ ability to think independently, encourage students to ask questions actively, communicate and interact with course teachers, and help course teams advance course construction. However, taking the number of participating comments as the only criterion for evaluating the grades of co...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/33G06F16/9535G06F40/289G06K9/62G06N3/04G06Q10/06G06Q50/20
CPCG06F16/9535G06F40/289G06F16/3344G06Q50/205G06Q10/06395G06N3/045G06F18/214
Inventor 董晨洪祺瑜王泽鸿陈羽中张浩熊乾程
Owner FUZHOU UNIV