Visual learning analysis of physical virtual simulation experiments based on heterogeneous data features-Reference-Cited by-同舟云学术

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

Published:2023-10-09 Issue:1 Volume:9 Page:
ISSN:2444-8656
Container-title:Applied Mathematics and Nonlinear Sciences
language:en
Short-container-title:

Author:

Tao Guanqi¹,Wang Yinshu²,Fan Yina¹

Affiliation:

1. 1 Experimental and Practical Education Innovation Center , Beijing Normal University at Zhuhai , Zhuhai , Guangdong , , China .

2. 2 Faculty of Arts and Sciences , Beijing Normal University at Zhuhai , Zhuhai , Guangdong , , China .

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science

Link

https://www.sciendo.com/pdf/10.2478/amns.2023.2.00560

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