Exploring the characteristics of the cadets´ learning network under military education

Autores

  • Keng-Yu Lin R.O.C. Military Academy
  • Long-Hui Chen National Kaohsiung Normal University
  • Ching-Wen Chen National Kaohsiung University of Science and Technology
  • Kuei-Hu Chang R.O.C. Military Academy https://orcid.org/0000-0002-9630-7386

DOI:

https://doi.org/10.4025/actascitechnol.v46i1.63819

Palavras-chave:

social network analysis; social norms; learning network.

Resumo

Military academy education is a part of university education. This study aims to explore the characteristics and achievements of the learning network for military academies students in Taiwan order to understand the main reasons for the differences and to identify special students. Moreover, this study analyzed the social network to explain the patterns of the students´ learning network. The findings are as follows. (1) An extensively connected learning network exists among the students of different classes. Students who comply with social norms have close relationships and interact frequently with each other. (2) Different cognition of social norms is the main reason leading to differences among students in their learning network and performance. Compliance with social norms is effectively conducive to the access and sharing of knowledge and improvement of learning performance. (3) The academic performances of those who have aloof relationships with their peers are polarized with either extreme good or extreme poor, and most of them comply with no notice or reflect the behavior of rejecting social norms. The academic contribution can support administrator as an important reference for planning education strategy.

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Publicado

2024-09-04

Como Citar

Lin, K.-Y., Chen, L.-H., Chen, C.-W., & Chang, K.-H. (2024). Exploring the characteristics of the cadets´ learning network under military education. Acta Scientiarum. Technology, 46(1), e63819. https://doi.org/10.4025/actascitechnol.v46i1.63819

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Estatí­stica

 

0.8
2019CiteScore
 
 
36th percentile
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0.8
2019CiteScore
 
 
36th percentile
Powered by  Scopus