College student learning behavior analysis system based on big data

By designing a university student learning behavior analysis system based on big data and building a student portrait label system, the shortcomings of the existing online learning platform for students' learning behavior and effect tracking and evaluation are solved, and high-accurate student portraits and personalized learning support are achieved to help students' academic development.

CN119648045APending Publication Date: 2025-03-18LIAOCHENG UNIV
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Patent Information

Application Number
CN202411713478.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-27
Publication Date
2025-03-18

AI Technical Summary

Technical Problem

The existing online learning platforms lack effective tracking and evaluation of students' learning behavior and effects, making it difficult for students to accurately select suitable learning resources, poor learning results, and insufficient student portrait accuracy and personalized recommendation system implementation.

Method used

Design a learning behavior analysis system for college students based on big data. By building an objective, real and accurate student portrait label system, combining data collection, processing, label generation and storage modules, a high-accurate student portrait is generated, providing personalized learning support and recommendation system.

Benefits of technology

It reduces the cognitive load of a large amount of data on teachers and students, realizes in-depth portrayal of the student group, and has high accuracy in the generated student portraits, provides decision-making support for education managers, helps students' academic development, and reduces the repetitive and cumbersome work of manual labeling.

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Abstract

The invention belongs to application of a big data analysis technology in the field of education, discloses a college student learning behavior analysis system based on big data, and aims to provide personalized learning suggestions and education decision support by analyzing online learning data of students. The system specifically comprises a data acquisition module, a data processing module, a label module, a data storage module and a portrait generation module. According to the college student learning behavior analysis system based on the big data, an objective, real and accurate student portrait label system is constructed, so that the cognitive load brought to teachers and students by a large amount of data is reduced; the student group is deeply depicted, the generated portrait is high in accuracy, and corresponding decision support is provided for student education managers, so that student academic development is assisted, repeated and tedious work caused by manual labeling is reduced, a label system is periodically updated, and automatic updating of the portrait is realized.
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