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

<p>In the context of the information age, Civics education in colleges and universities faces new challenges. Cognitive mapping, an emerging technology, and its application in the design of Civics teaching in college courses is expected to enhance the teaching effect and quality. The purpose of this paper is to explore the use of cognitive mapping in the teaching of Civics in colleges and universities. The study uses the methods of data collection, preprocessing, knowledge extraction, fusion, and map construction to create a cognitive mapping-based model for teaching Civics in colleges and universities. The results show that the model can significantly improve the teaching effectiveness. In the named entity recognition experiments, the precision, recall, and F1 value of the BiLSTM-CRF-GNN model reached 93.47%, 93.58%, and 93.88%, respectively. In addition, the analysis of the hotspots of Civics research shows that the most frequent keywords include “Civics curriculum”, “Civics education” and “teaching practice”. This study not only advances the application of cognitive mapping theoretically, but also provides practical guidance for teaching Civics in colleges and universities, which is of great significance for improving the quality and efficiency of Civics teaching.</p>
</abstract>

In the context of the information age, Civics education in colleges and universities faces new challenges. Cognitive mapping, an emerging technology, and its application in the design of Civics teaching in college courses is expected to enhance the teaching effect and quality. The purpose of this paper is to explore the use of cognitive mapping in the teaching of Civics in colleges and universities. The study uses the methods of data collection, preprocessing, knowledge extraction, fusion, and map construction to create a cognitive mapping-based model for teaching Civics in colleges and universities. The results show that the model can significantly improve the teaching effectiveness. In the named entity recognition experiments, the precision, recall, and F1 value of the BiLSTM-CRF-GNN model reached 93.47%, 93.58%, and 93.88%, respectively. In addition, the analysis of the hotspots of Civics research shows that the most frequent keywords include “Civics curriculum”, “Civics education” and “teaching practice”. This study not only advances the application of cognitive mapping theoretically, but also provides practical guidance for teaching Civics in colleges and universities, which is of great significance for improving the quality and efficiency of Civics teaching.

A case for cognitive mapping constructive approach to teaching civics in higher education programs design

Applied Mathematics and Nonlinear Sciences

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

In the context of the information age, Civics education in colleges and universities faces new challenges. Cognitive mapping, an emerging technology, and its...

A case for cognitive mapping constructive approach to teaching civics in higher education programs design

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 04 abr 2024

Aceptado: 18 abr 2024

DOI: https://doi.org/10.2478/amns-2024-1049

Palabras clave
Cognitive Mapping, Civics Teaching, Named Entity Recognition, Teaching Effectiveness

© 2024 Lingling Shi et al., published by Sciendo

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

A case for cognitive mapping constructive approach to teaching civics in higher education programs design

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 04 abr 2024

Aceptado: 18 abr 2024

DOI: https://doi.org/10.2478/amns-2024-1049

Palabras claveCognitive Mapping, Civics Teaching, Named Entity Recognition, Teaching Effectiveness

© 2024 Lingling Shi et al., published by Sciendo

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

Palabras clave
Cognitive Mapping, Civics Teaching, Named Entity Recognition, Teaching Effectiveness