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<p>Physics experiment is one of the key points and difficulties of physics teaching, and it has become a recognized bottleneck that restricts the quality of physics teaching. This paper firstly explores the integration of high school physics experimental teaching with information technology based on physics experimental teaching practice and physics curriculum standards through various ways and means. Secondly, it proposes constructing a collaborative physics experimental teaching design scheme based on information fusion technology, using three non-hierarchical multi-model fusion methods with Gaussian stochastic processes for modeling to achieve effective fusion of multiple non-hierarchical models of physics response information and physics teaching. Finally, a practical study in the form of a physics experimental teaching case is analyzed, and the teaching effect is measured to verify the effectiveness and feasibility of the design scheme. The results show that the physics teaching design based on information fusion technology effectively improves students’ experimental performance by 21.2%, learning interest by 36.4%, and learning participation by 19.8%. This study takes physics experimental teaching and information fusion technology as the entry point and improves the overall teaching quality of physics as the goal, which provides reference or reference teaching reform and practice in the context of information technology.</p>
</abstract>

Physics experiment is one of the key points and difficulties of physics teaching, and it has become a recognized bottleneck that restricts the quality of physics teaching. This paper firstly explores the integration of high school physics experimental teaching with information technology based on physics experimental teaching practice and physics curriculum standards through various ways and means. Secondly, it proposes constructing a collaborative physics experimental teaching design scheme based on information fusion technology, using three non-hierarchical multi-model fusion methods with Gaussian stochastic processes for modeling to achieve effective fusion of multiple non-hierarchical models of physics response information and physics teaching. Finally, a practical study in the form of a physics experimental teaching case is analyzed, and the teaching effect is measured to verify the effectiveness and feasibility of the design scheme. The results show that the physics teaching design based on information fusion technology effectively improves students’ experimental performance by 21.2%, learning interest by 36.4%, and learning participation by 19.8%. This study takes physics experimental teaching and information fusion technology as the entry point and improves the overall teaching quality of physics as the goal, which provides reference or reference teaching reform and practice in the context of information technology.

Research on optimization design of physics teaching objectives based on information fusion technology

Applied Mathematics and Nonlinear Sciences

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

Physics experiment is one of the key points and difficulties of physics teaching, and it has become a recognized bottleneck that restricts the quality of...

Research on optimization design of physics teaching objectives based on information fusion technology

Online veröffentlicht: 23. Sept. 2023

Seitenbereich: -

Eingereicht: 27. Okt. 2022

Akzeptiert: 03. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00358

Schlüsselwörter
Non-hierarchical multi-model, Information fusion techniques, Non-hierarchical, Gaussian stochastic processes, Physical response

© 2023 Yongqing Yang, published by Sciendo

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

Research on optimization design of physics teaching objectives based on information fusion technology

Online veröffentlicht: 23. Sept. 2023

Seitenbereich: -

Eingereicht: 27. Okt. 2022

Akzeptiert: 03. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00358

SchlüsselwörterNon-hierarchical multi-model, Information fusion techniques, Non-hierarchical, Gaussian stochastic processes, Physical response

© 2023 Yongqing Yang, published by Sciendo

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

Schlüsselwörter
Non-hierarchical multi-model, Information fusion techniques, Non-hierarchical, Gaussian stochastic processes, Physical response