计算机科学
商业智能
适应性学习
商业模拟
人工智能
多媒体
人机交互
模拟
知识管理
作者
G. Bharathi,Indra Chandra,Durga Prasada Rao Sanagana,Chaitanya Kanth Tummalachervu,Vuda Sreenivasa Rao,S. Neelima
标识
DOI:10.1016/j.entcom.2024.100699
摘要
This study investigates how automated adaptable learning (BSG) may improve business simulating games (BSG) and its transformation possibilities. The rapid increase of information, combined with the intricate nature of today's company contexts, means that classic BSG education techniques frequently fail to adequately prepare students for the difficulties they will face in everyday life. This study provides a revolutionary architecture that continually evolves learning paths, responses, and testing situations based on specific student progress and desires. It does this by utilizing modern artificial intelligence methods, including machine learning. This technique seeks to maximize users' preservation of expertise, ability to make decisions, and capacity for creative thinking through tailoring their education. In summary, our study raises possibilities for better and more interesting educational opportunities throughout the modern age by adding to the continuing conversation about the relationship between AI, training, and corporate strategies.
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