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<p>Integrating information technology with the curriculum has been closely watched by the educational community, and how well the two are integrated determines the effectiveness of mathematics education. This paper proposes an implementation scheme for mapping mathematical knowledge. Firstly, the Word2vec word vector model is used to acquire data from the original mathematical text, and then the Conditional Random Field model is used to extract the knowledge entities, and the Markov Logic Nets are used to extract the relationships between the knowledge entities. Then, the Path Ranking algorithm is utilized on the basis of entity alignment to realize the knowledge inference of the subject knowledge graph and mine the learning paths in the knowledge graph. Through the experimental and questionnaire methods, it was found that the math scores of the experimental class before the comparison experiment increased by 9.4337 points, which was significantly ahead of the control class. The average number of students who thought knowledge mapping teaching greatly improved their interest in math learning was 46.81%, while 31.29% believed that the new method had a relatively positive impact on their motivation to learn. It shows that knowledge mapping can be an effective method of teaching information technology.</p>
</abstract>

Integrating information technology with the curriculum has been closely watched by the educational community, and how well the two are integrated determines the effectiveness of mathematics education. This paper proposes an implementation scheme for mapping mathematical knowledge. Firstly, the Word2vec word vector model is used to acquire data from the original mathematical text, and then the Conditional Random Field model is used to extract the knowledge entities, and the Markov Logic Nets are used to extract the relationships between the knowledge entities. Then, the Path Ranking algorithm is utilized on the basis of entity alignment to realize the knowledge inference of the subject knowledge graph and mine the learning paths in the knowledge graph. Through the experimental and questionnaire methods, it was found that the math scores of the experimental class before the comparison experiment increased by 9.4337 points, which was significantly ahead of the control class. The average number of students who thought knowledge mapping teaching greatly improved their interest in math learning was 46.81%, while 31.29% believed that the new method had a relatively positive impact on their motivation to learn. It shows that knowledge mapping can be an effective method of teaching information technology.

Integration Strategies of Information Technology in Mathematics Education and Student Motivation Enhancement

Linzhou College of Architectural Technology

Applied Mathematics and Nonlinear Sciences

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

Integrating information technology with the curriculum has been closely watched by the educational community, and how well the two are integrated determines...

Integration Strategies of Information Technology in Mathematics Education and Student Motivation Enhancement

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 25. März 2024

Akzeptiert: 18. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-1874

Schlüsselwörter
Knowledge mapping, Path Ranking algorithm, Word2vec word vector model, Informalized teaching

© 2024 Yunna Yan., published by Sciendo

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

Integration Strategies of Information Technology in Mathematics Education and Student Motivation Enhancement

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 25. März 2024

Akzeptiert: 18. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-1874

SchlüsselwörterKnowledge mapping, Path Ranking algorithm, Word2vec word vector model, Informalized teaching

© 2024 Yunna Yan., published by Sciendo

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

Schlüsselwörter
Knowledge mapping, Path Ranking algorithm, Word2vec word vector model, Informalized teaching