AI-driven adaptive learning for enhancing business intelligence simulation games

被引:1
|
作者
Bharathi, G. P. [1 ]
Chandra, I. [2 ]
Prasada, Durga [3 ]
Sanagana, Rao
Tummalachervu, Chaitanya Kanth [4 ]
Rao, Vuda Sreenivasa [5 ]
Neelima, S. [6 ]
机构
[1] Saveetha Univ, Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Elect & Commun Engn, Chennai, India
[2] Rajalakshmi Inst Technol, Dept Elect & Commun Engn, Chennai 600124, India
[3] Provident Credit Union, Redwood City, CA USA
[4] RingCental Inc, Denver, CO USA
[5] Koneru Lakshmaiah Educ Fdn, Dept Comp Sci & Engn, Green Fields, Vaddeswaram 522302, Andhra Pradesh, India
[6] Aditya Univ, Dept Informat Technol, Surampalem, India
关键词
AI -driven adaptive learning; Business simulation games (BSG); Machine learning; Personalized learning; Data -driven learning; SYSTEMS;
D O I
10.1016/j.entcom.2024.100699
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
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.
引用
收藏
页数:7
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