Design and Application of Decision Support System for Educational Management Based on Big Data

被引:0
作者
Bai, Haining [1 ]
机构
[1] North China Elect Power Univ Baoding, Dept Econ Management, Baoding 071003, Hebei, Peoples R China
关键词
Recommendation System; Big Data; Decision Support System (DSS); Educational Management; Education Management;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Decision support system (DSS) for educational management based on big data leverage advanced analytics and machine learning techniques to enhance decision -making processes within educational institutions. By collecting and analyzing large volumes of data from various sources such as student performance, administrative records, and institutional resources, the DSS provides valuable insights and predictive models to administrators and educators. These insights can inform strategic planning, resource allocation, student interventions, and curriculum development, ultimately improving student outcomes and organizational efficiency. With the ability to process vast amounts of data in real-time, the DSS enables timely and data -driven decision -making, empowering educational leaders to address challenges and capitalize on opportunities in today's complex educational landscape.The integration of big data analytics with the Recommender Ranking Decision Support System (RRDS) presents a transformative approach to enhancing educational management. This paper explores the application of big data analytics within the educational setting, focusing on the development and implementation of the RRDS. By leveraging large and diverse datasets, the RRDS enables personalized learning experiences, optimizes resource allocation, and enhances student outcomes. Through predictive modeling, the RRDS predicts student performance and identifies at -risk students, facilitating targeted interventions to support student success and retention. Additionally, the system offers personalized learning recommendations tailored to individual student needs, fostering engagement and motivation. The findings underscore the significance of data -driven decision -making in improving educational practices and institutional performance. As educational institutions increasingly embrace technology -driven solutions, the integration of big data analytics and RRDS stands poised to revolutionize educational management, ultimately leading to more effective teaching and learning methodologies and better outcomes for students.
引用
收藏
页码:1645 / 1655
页数:11
相关论文
共 16 条
[1]  
Al-Alwan M., 2022, International Journal of Data and Network Science, V6, P693
[2]   A novel decision support system for managing predictive maintenance strategies based on machine learning approaches [J].
Arena, S. ;
Florian, E. ;
Zennaro, I ;
Orru, P. F. ;
Sgarbossa, F. .
SAFETY SCIENCE, 2022, 146
[3]   A decision support system for configuring spare parts supply chains considering different manufacturing technologies [J].
Cantini, Alessandra ;
Peron, Mirco ;
De Carlo, Filippo ;
Sgarbossa, Fabio .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2024, 62 (08) :3023-3043
[4]   Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system [J].
Cinelli, Marco ;
Kadzinski, Milosz ;
Miebs, Grzegorz ;
Gonzalez, Michael ;
Slowinski, Roman .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022, 302 (02) :633-651
[5]   A survey on big data-enabled innovative online education systems during the COVID-19 pandemic [J].
Cui, Yuhuan ;
Ma, Zezhong ;
Wang, Liya ;
Yang, Aimin ;
Liu, Qiumei ;
Kong, Shanshan ;
Wang, Huifang .
JOURNAL OF INNOVATION & KNOWLEDGE, 2023, 8 (01)
[6]   Artificial intelligence for decision support systems in the field of operations research: review and future scope of research [J].
Gupta, Shivam ;
Modgil, Sachin ;
Bhattacharyya, Samadrita ;
Bose, Indranil .
ANNALS OF OPERATIONS RESEARCH, 2022, 308 (1-2) :215-274
[7]   Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives [J].
Karatas, Mumtaz ;
Eriskin, Levent ;
Deveci, Muhammet ;
Pamucar, Dragan ;
Garg, Harish .
EXPERT SYSTEMS WITH APPLICATIONS, 2022, 200
[8]   Deep Learning-Assisted Smart Process Planning, Robotic Wireless Sensor Networks, and Geospatial Big Data Management Algorithms in the Internet of Manufacturing Things [J].
Lazaroiu, George ;
Andronie, Mihai ;
Iatagan, Mariana ;
Geamanu, Marinela ;
Stefanescu, Roxana ;
Dijmarescu, Irina .
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2022, 11 (05)
[9]   Prospective Evaluation of a Clinical Decision Support System in Psychological Therapy [J].
Lutz, Wolfgang ;
Deisenhofer, Anne-Katharina ;
Rubel, Julian ;
Bennemann, Bjoern ;
Giesemann, Julia ;
Poster, Kaitlyn ;
Schwartz, Brian .
JOURNAL OF CONSULTING AND CLINICAL PSYCHOLOGY, 2022, 90 (01) :90-106
[10]   Smart City Construction and Management by Digital Twins and BIM Big Data in COVID-19 Scenario [J].
Lv, Zhihan ;
Chen, Dongliang ;
Lv, Haibin .
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2022, 18 (02)