evaluation of simulation-based training for aircraft carrier marshalling with learning cubic and kirkpatrick’s models

Clicks: 54
ID: 252546
2015
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #86 of 90 articles by views in Cancer epidemiology

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Simulation-based training is a promising way to train a carrier flight deck crew because of the complex and dangerous working environment. Quantitative evaluation of simulation-based training quality is vital to make simulation-based training practical for aircraft carrier marshalling. This paper develops a personal computer-based aircraft carrier marshalling simulation system and a cave automatic virtual environment (CAVE)-based immersive environment. In order to compare the training effectiveness of simulation-based training and paper-based training, a learning cubic model is proposed and a contrast experiment is carried out as well. The experimental data is analyzed based on a simplified Kirkpatrick’s model. The results show that simulation-based training is better than paper-based training by 26.80% after three rounds of testing, which prove the effectiveness of simulation-based aircraft carrier marshalling training.
Reference Key
tian2015chineseevaluation Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Yongliang Tian;Hu Liu;Jiao Yin;Mingqiang Luo;Guanghui Wu
Journal Cancer epidemiology
Year 2015
DOI
10.1016/j.cja.2014.12.002
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.