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

<p>The current traditional means of teaching adopt the indoctrination teaching mode. Students passively accept information, learning enthusiasm is not high, and the traditional teaching mode needs to be reconstructed urgently. This paper constructs a blended teaching mode for civil litigation based on the WeChat public platform and provides the implementation process for the blended teaching mode. In order to enable students to obtain civil litigation-related resources more in line with the learning characteristics of the WeChat platform, a multi-objective learning path optimization algorithm is proposed, and the discrete binary particle swarm algorithm is used to optimize and solve the multi-objective learning path. The teaching experiment method is utilized to select the research object and method to study the teaching effect of the blended teaching mode and then obtain the students’ satisfaction with the blended teaching mode. The results show that through the BPSO algorithm, after the number of iterations reaches 150 times, its fitness value is around 10-5, the average running time of the 20 test functions is around 500ms, and the mean value of students’ satisfaction with the blended teaching mode is 9.31 points. The blended teaching mode of civil litigation in the context of the rule of law can help students better establish the thinking of the rule of law and promote the improvement of students’ learning ability, and multi-objective optimization can help students better obtain the optimal learning path.</p>
</abstract>

The current traditional means of teaching adopt the indoctrination teaching mode. Students passively accept information, learning enthusiasm is not high, and the traditional teaching mode needs to be reconstructed urgently. This paper constructs a blended teaching mode for civil litigation based on the WeChat public platform and provides the implementation process for the blended teaching mode. In order to enable students to obtain civil litigation-related resources more in line with the learning characteristics of the WeChat platform, a multi-objective learning path optimization algorithm is proposed, and the discrete binary particle swarm algorithm is used to optimize and solve the multi-objective learning path. The teaching experiment method is utilized to select the research object and method to study the teaching effect of the blended teaching mode and then obtain the students’ satisfaction with the blended teaching mode. The results show that through the BPSO algorithm, after the number of iterations reaches 150 times, its fitness value is around 10-5, the average running time of the 20 test functions is around 500ms, and the mean value of students’ satisfaction with the blended teaching mode is 9.31 points. The blended teaching mode of civil litigation in the context of the rule of law can help students better establish the thinking of the rule of law and promote the improvement of students’ learning ability, and multi-objective optimization can help students better obtain the optimal learning path.

A Blended Instructional Design for Civil Litigation Combining Multi-Objective Optimization Algorithms in a Rule of Law Context

Applied Mathematics and Nonlinear Sciences

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

The current traditional means of teaching adopt the indoctrination teaching mode. Students passively accept information, learning enthusiasm is not high, and...

A Blended Instructional Design for Civil Litigation Combining Multi-Objective Optimization Algorithms in a Rule of Law Context

Data publikacji: 06 gru 2023

Zakres stron: -

Otrzymano: 20 sty 2023

Przyjęty: 16 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01399

Słowa kluczowe
Multi-objective optimization, Civil litigation, Discrete binary, Particle swarm algorithm, Blended learning

© 2023 Tingting Su, published by Sciendo

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

A Blended Instructional Design for Civil Litigation Combining Multi-Objective Optimization Algorithms in a Rule of Law Context

Data publikacji: 06 gru 2023

Zakres stron: -

Otrzymano: 20 sty 2023

Przyjęty: 16 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01399

Słowa kluczoweMulti-objective optimization, Civil litigation, Discrete binary, Particle swarm algorithm, Blended learning

© 2023 Tingting Su, published by Sciendo

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

Słowa kluczowe
Multi-objective optimization, Civil litigation, Discrete binary, Particle swarm algorithm, Blended learning