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Online learning behavior analysis-based individualized learning recommending method

A recommendation method and behavior analysis technology, applied in the field of data analysis, can solve problems such as regression prediction of test scores of students who cannot learn, the influence of learning effect is not considered, and data mining is insufficient, so as to achieve easy understanding and clear meaning of learning characteristics. , the effect of improving the prediction accuracy

Active Publication Date: 2018-06-19
深圳市优课再学教育科技有限公司
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Problems solved by technology

[0004] In order to overcome the existing situation that the online behavior data mining of learners is not sufficient, the influence of the regularity of login learning time on the learning effect is not considered, and the regression prediction of the test scores of the learners cannot be accurately performed, the present invention provides a prediction accuracy Higher and more comprehensive analysis of learners' online learning time regularity BP neural network prediction method

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  • Online learning behavior analysis-based individualized learning recommending method
  • Online learning behavior analysis-based individualized learning recommending method
  • Online learning behavior analysis-based individualized learning recommending method

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Embodiment Construction

[0044] The implementation process of the present invention will be described below in conjunction with the drawings and embodiments.

[0045] refer to Figure 1 to Figure 7 , a personalized learning recommendation method based on online learning behavior analysis. This method collects students' online learning behavior operation data from the open data interface provided by Wankewang platform. According to the system design requirements, the student's operation behavior data mainly includes 6 types: a. Login time. The system login time of each login (the screened time of more than 30 minutes is the effective time); b. Browsing teaching resources. Behavior data is the length of online time, which must be operated with the mouse and keyboard, and the number of operations that cannot be fast-forwarded is valid data; c. Forum data. It mainly refers to the quantity and quality of posts and replies, and takes the number of words, browsing response rate, etc. as valid data; d. Onli...

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Abstract

An online learning behavior analysis-based individualized learning recommending method comprises the following steps of 1 collecting the data, and obtaining the learner log data, the student score data and the student character data of an online learning platform; 2 extracting and mining the features; 3 preparing a dataset to train a BP neural network and testing the accuracy of a model; 4 utilizing the trained model to predict the scores of the new learners; 5 issuing the questionnaires to the learners, and collecting the questionnaire data; 6 carrying out the k-means clustering analysis on the questionnaire data; 7 combining the character features of the different learners to recommend the individualized learning methods. The present invention provides a BP neural network prediction method that is higher in prediction precision and can analyze the online learning time regularity of the learners more comprehensively. According to the present invention, the characters of the learners can be analyzed, and the individualized learning methods can be recommended to the learners.

Description

technical field [0001] The invention relates to the field of data analysis, in particular to a method for evaluating online learning behaviors based on big data, analyzing learners' personalities, and recommending personalized learning. Background technique [0002] With the widespread use of online courses and the popularity of online learning, the proportion of online learning in the study life of contemporary students is increasing day by day. Online learning systems such as MOOC (Massive Open Online Course) and SPOC (Small Open Online Course) PrivateOnline Course, small-scale restricted online course) enables learners not to be limited by time and space, and can conduct online learning, online discussion, and online assessment anytime and anywhere through the Internet. Furthermore, the time regularity performance of learners' login and online learning reflects learners' self-discipline from the side, and objectively evaluating the learning time regularity characteristics...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/20
CPCG06Q10/04G06Q10/0639G06Q50/205
Inventor 陈晋音方航
Owner 深圳市优课再学教育科技有限公司
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