<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In order to provide a way to develop the teaching effectiveness of physics experiments, this paper optimizes the platform search engine by combining heterogeneous data features and representing document information as feature vectors based on visual learning analysis methods. The algorithm is dynamically adjusted according to the authority to build a network database. And the virtual physics experiments have interacted with virtual experimental equipment to build a physics virtual simulation experiment platform. The results show that the overall level of visual student portrait analysis is above 40%, and the average completion efficiency of visual evaluation tasks 1-9 is 87.9%, which helps the digital transformation and upgrading of experimental physics teaching and promotes the construction of high-quality virtual simulation experimental teaching system.</p>
</abstract>

In order to provide a way to develop the teaching effectiveness of physics experiments, this paper optimizes the platform search engine by combining heterogeneous data features and representing document information as feature vectors based on visual learning analysis methods. The algorithm is dynamically adjusted according to the authority to build a network database. And the virtual physics experiments have interacted with virtual experimental equipment to build a physics virtual simulation experiment platform. The results show that the overall level of visual student portrait analysis is above 40%, and the average completion efficiency of visual evaluation tasks 1-9 is 87.9%, which helps the digital transformation and upgrading of experimental physics teaching and promotes the construction of high-quality virtual simulation experimental teaching system.

Visual learning analysis of physical virtual simulation experiments based on heterogeneous data features

Applied Mathematics and Nonlinear Sciences

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

In order to provide a way to develop the teaching effectiveness of physics experiments, this paper optimizes the platform search engine by combining...

Visual learning analysis of physical virtual simulation experiments based on heterogeneous data features

Online veröffentlicht: 09. Okt. 2023

Seitenbereich: -

Eingereicht: 03. Dez. 2022

Akzeptiert: 19. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00560

Schlüsselwörter
Visual learning, Heterogeneous data, dynamically adjusted, Search engine, Virtual experiment

© 2023 Guanqi Tao et al., published by Sciendo

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

Visual learning analysis of physical virtual simulation experiments based on heterogeneous data features

Online veröffentlicht: 09. Okt. 2023

Seitenbereich: -

Eingereicht: 03. Dez. 2022

Akzeptiert: 19. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00560

SchlüsselwörterVisual learning, Heterogeneous data, dynamically adjusted, Search engine, Virtual experiment

© 2023 Guanqi Tao et al., published by Sciendo

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

Schlüsselwörter
Visual learning, Heterogeneous data, dynamically adjusted, Search engine, Virtual experiment