Enhancing Student Engagement in New Business Discipline Experimental Teaching through Smart Resource Allocation Systems

doi:10.1109/CSRSWTC64338.2024.10811649

	Enhancing Student Engagement in New Business Discipline Experimental Teaching through Smart Resource Allocation Systems
	Luo, Fu 1; Zhu, Yingying2 ; Guo, Xuan 1; Deng, Chunhong 1; Zhang, Zheng1
	2024
会议名称	2024 Cross Strait Radio Science and Wireless Technology Conference
会议录名称	2024 CROSS STRAIT RADIO SCIENCE AND WIRELESS TECHNOLOGY CONFERENCE, CSRSWTC 2024
页码	531-534
会议日期	NOV 04-07, 2024
会议地点	PEOPLES R CHINA
出版地	NEW YORK
出版者	IEEE
摘要	This paper designs and validates an intelligent resource allocation system aimed at optimizing resource distribution in business experimentation teaching through the use of machine learning algorithms (Random Forest). The system dynamically adjusts teaching resources based on the analysis of student behavior data, including task completion time, test scores, and engagement, to provide personalized learning support. The experiment involved 52 students divided into high-performance, moderate-performance, and low -performance groups, with student behavior data collected through the Superstar Learning platform. The results demonstrate that the intelligent resource allocation system significantly improved student engagement and learning outcomes, particularly for low -performance students, who showed substantial improvement in both engagement and test scores. Additionally, the system's performance evaluation revealed high resource allocation efficiency and rapid feedback response times across different scenarios. The paper also discusses the advantages and limitations of the system, confirming its potential application in real-world teaching.
关键词	Intelligent Resource Allocation System Machine Learning Random Forest Personalized Teaching Engagement Learning Outcomes Superstar Learning Platform
DOI	10.1109/CSRSWTC64338.2024.10811649
收录类别	CPCI-S
语种	英语
WOS研究方向	Engineering ; Telecommunications
WOS类目	Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001414377800176
原始文献类型	Proceedings Paper
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/38817
专题	工商管理学院经济学院
通讯作者	Zhu, Yingying
作者单位	1.Guangdong Univ Sci & Technol, Sch Management, Dongguan 523083, Peoples R China; 2.LanZhou Univ Finance & Econ, Lanzhou 730020, Peoples R China
通讯作者单位	兰州财经大学
推荐引用方式 GB/T 7714	Luo, Fu,Zhu, Yingying,Guo, Xuan,et al. Enhancing Student Engagement in New Business Discipline Experimental Teaching through Smart Resource Allocation Systems[C]. NEW YORK:IEEE,2024:531-534.