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

<p>The teaching of law courses in Legal Experimental Teaching System (LETS) enables students to have a clearer understanding of the litigation process, master the format and production of various criminal litigation legal documents and train their communication and collaboration skills in litigation by cooperating to complete the experimental process. However, there are some shortcomings in experimental teaching using the LETS system, such as teachers being unable give real-time guidance and unable to reflect the principle of direct speech in litigation. Given these problems, this paper proposes a framework for the deep integration of LETS software and criminal litigation under the background of artificial intelligence (AI). First, it introduces the current situation and development of criminal litigation under the background of AI. Then, a set of AI parameters is designed based on the background of LETS software and criminal proceedings deep integration framework, and at the same time, the framework is used for intelligent learning criminal proceedings. The experimental results show that LETS software can better match the algorithm of the AI environment to push personalised criminal procedure learning courses. The experiment also shows that this framework can provide new ideas and development for the future study of criminal procedure.</p>
</abstract>

The teaching of law courses in Legal Experimental Teaching System (LETS) enables students to have a clearer understanding of the litigation process, master the format and production of various criminal litigation legal documents and train their communication and collaboration skills in litigation by cooperating to complete the experimental process. However, there are some shortcomings in experimental teaching using the LETS system, such as teachers being unable give real-time guidance and unable to reflect the principle of direct speech in litigation. Given these problems, this paper proposes a framework for the deep integration of LETS software and criminal litigation under the background of artificial intelligence (AI). First, it introduces the current situation and development of criminal litigation under the background of AI. Then, a set of AI parameters is designed based on the background of LETS software and criminal proceedings deep integration framework, and at the same time, the framework is used for intelligent learning criminal proceedings. The experimental results show that LETS software can better match the algorithm of the AI environment to push personalised criminal procedure learning courses. The experiment also shows that this framework can provide new ideas and development for the future study of criminal procedure.

Research on the experimental principle of deep integration of LETS software and criminal procedure under the background of artificial intelligence

Applied Mathematics and Nonlinear Sciences

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

The teaching of law courses in Legal Experimental Teaching System (LETS) enables students to have a clearer understanding of the litigation process, master the...

Research on the experimental principle of deep integration of LETS software and criminal procedure under the background of artificial intelligence

Publicado en línea: 30 nov 2022

Páginas: 2695 - 2704

Recibido: 30 jun 2022

Aceptado: 16 sept 2022

DOI: https://doi.org/10.2478/amns.2021.2.00279

Palabras clave
Experimental teaching system of law, Artificial intelligence, Criminal proceedings, Deep learning

© 2023 Yao Liu, published by Sciendo

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

Research on the experimental principle of deep integration of LETS software and criminal procedure under the background of artificial intelligence

Publicado en línea: 30 nov 2022

Páginas: 2695 - 2704

Recibido: 30 jun 2022

Aceptado: 16 sept 2022

DOI: https://doi.org/10.2478/amns.2021.2.00279

Palabras claveExperimental teaching system of law, Artificial intelligence, Criminal proceedings, Deep learning

© 2023 Yao Liu, published by Sciendo

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

Palabras clave
Experimental teaching system of law, Artificial intelligence, Criminal proceedings, Deep learning