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<p>In order to optimize the drawbacks of current personalized learning systems on the market, a big data algorithm is used to optimize the personalized learning system. This paper first analyzes the system model, constructs the basic framework of the system, and optimizes the algorithm based on a collaborative filtering algorithm that converts user behavior into ratings and recommends personalized learning content for learners. Since learning resources and learners are interconnected, this connection is analyzed by an ant colony algorithm to provide the optimal path for students to learn and create a personalized learning path. After comparing the student models, we understand that the clearer the description of students’ interests, the clearer the accuracy returned, where User A and User C have the highest similarity of 99% and accuracy of 85% and 88% respectively, proving the feasibility of the system. The personalized learning system supported by big data in education can optimize the drawbacks of the current personalized learning system in the market, meet the concept of teaching according to student’s abilities, and outperform the learning system in the market.</p>
</abstract>

In order to optimize the drawbacks of current personalized learning systems on the market, a big data algorithm is used to optimize the personalized learning system. This paper first analyzes the system model, constructs the basic framework of the system, and optimizes the algorithm based on a collaborative filtering algorithm that converts user behavior into ratings and recommends personalized learning content for learners. Since learning resources and learners are interconnected, this connection is analyzed by an ant colony algorithm to provide the optimal path for students to learn and create a personalized learning path. After comparing the student models, we understand that the clearer the description of students’ interests, the clearer the accuracy returned, where User A and User C have the highest similarity of 99% and accuracy of 85% and 88% respectively, proving the feasibility of the system. The personalized learning system supported by big data in education can optimize the drawbacks of the current personalized learning system in the market, meet the concept of teaching according to student’s abilities, and outperform the learning system in the market.

Research on the construction of personalized learning system supported by big data in education

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In order to optimize the drawbacks of current personalized learning systems on the market, a big data algorithm is used to optimize the personalized learning...

Research on the construction of personalized learning system supported by big data in education

Online veröffentlicht: 02. Okt. 2023

Seitenbereich: -

Eingereicht: 18. Dez. 2022

Akzeptiert: 12. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00438

Schlüsselwörter
Personalized recommendation algorithm, Filtering recommendation algorithm, Ant colony algorithm, Personalized learning system

© 2023 Xuekong Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the construction of personalized learning system supported by big data in education

Online veröffentlicht: 02. Okt. 2023

Seitenbereich: -

Eingereicht: 18. Dez. 2022

Akzeptiert: 12. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00438

SchlüsselwörterPersonalized recommendation algorithm, Filtering recommendation algorithm, Ant colony algorithm, Personalized learning system

© 2023 Xuekong Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Personalized recommendation algorithm, Filtering recommendation algorithm, Ant colony algorithm, Personalized learning system