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Journal of Intelligent Computing

Analysis of Talent Cultivation and Development Under the Development of Immersion Data Mining Platform

Xu Meng
School of Systems Science and Engineering Sun Yat-sen University, Guangzhou, 510000 Guangdong, China.

Abstract: With the rapid development of information technology and big data, the methods of talent cultivation are also gradually changing. To improve the quality and efficiency of talent cultivation, we propose an immersive talent cultivation experimental platform based on data mining algorithms. The platform first collects various data on students, including learning behaviour, grades, personality traits, etc. Then, we used data mining algorithms to conduct indepth analysis and mining these data. Specifically, we used clustering algorithms to classify studentsÃ¢â‚¬â„¢ learning behaviors, association rule mining algorithms to discover the relationship between studentsÃ¢â‚¬â„¢ grades and personality traits, and decision tree algorithms to predict studentsÃ¢â‚¬â„¢ academic performance. By applying these algorithms, we can better understand studentsÃ¢â‚¬â„¢ learning status and needs and provide them with more personalized and accurate teaching services. At the same time, the platform also has immersive educational features, providing students with a more realistic and vivid learning experience through technologies such as virtual reality (VR) and augmented reality (AR). Students can conduct various experimental operations through the platform, deepening their understanding of knowledge points and enhancing their practical ability and innovative thinking.

Keywords: Talent Cultivation, Immersion, Data Mining, Platform Development Analysis of Talent Cultivation and Development Under the Development of Immersion Data Mining Platform

DOI:https://doi.org/10.6025/jic/2024/15/1/1-9

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References:

[1] Yuan, Di-ping, Jin, Xue-sheng, Zhang, Xiao-li, Wang, Chang-jiang, Jiang, Lian-rui, Wang, Xingbo, & Shen, Jian-yi. (2012). Design and implementation of immersive environment for firefighting tactical training. Fire Science and Technology, 2012(2), 162-165.
[2] Li, Tingting, Liu, Shi, Chen, Falu. (2017). Research on the development and key technologies of immersive virtual campus simulation systems. Microcomputer & Its Applications, 36(1), 79-82.
[3] Wu, Xiaozhu, Chen, Chongcheng, Liu, Xianfeng, Li, Jieguang, & Fang, Lina. (2016). Virtual Cultural Tour Guidance System Integrated with IBeacon-based Indoor Positioning. Computer Engineering, 42(10), 6-11.
[4] Wang, Jian-tao, Zhao, Ji-hai. (2017). Construction of Popular Books Discovery System Based on Data Mining. Library Theory and Practice, 2017(4), 94-97.
[5] Shen, Yi-Ting, Zhou, Ying, Chen, Xia, et al. (2017). Prescription characteristics of Chinese medicine for improving learning and memory ability based on data mining. Chinese Journal of Gerontology, 37(18).
[6] Zhang, Hao, Lei, Hong, Gong, Chengbin, Peng, Jingdong. (2017). Quantitative Analysis of Virtually Experimental Teaching Using Data Mining. Laboratory Research and Exploration, 36(9).
[7] Zhang, Yannxu, Hu, Chunchao, Huang, Shu, Feng, Shanqiang, Lin, Goanqiangz. (2017). Apriori Algorithm Based Data Mining and Analysis Method for Secondary Device Defects. Automation of Electric Power Systems, 41(19).
[8] Chen, Zijian, Zhu, Xiaoliang1. (2017). Research on Prediction Model of Online Learners’ Academic Achievement Based on Educational Data Mining. CET China Educational Technology, 2017(12).
[9] Chen, Hong-fu. (2013). Immersive Teaching Based on relevant-content Education Model of Undergraduate Business English Majors. Journal of Sichuan International Studies University, 29(4), 158-160.
[10] Lin, Yua. (2017). Research on Data Mining of Valuable Information in Unstructured Network. Computer Simulation, 34(2), 414-417.
[11] Ding, Guoyong, Cheng, Jinkuan. (2017). Experience and Implications of Educational Data Mining in US Universities. Comparative Education Review, 39(5), 73-78.
[12] Peng, Tao, Ding, Ling-yun. (2015). Performance Prediction Model Based on Data Mining Based Education Students. Heilongjiang Researches on Higher Education, 2015(11), 55-58.
[13] Shu, Zhong-mei, Qu, Qiong-fei. (2014). An Analysis of University Students’ Learning Outcome Based on Educational Data Mining. Journal of Northeastern University (Social Science), 16(3), 309-314.
[14] Cui, Xiao, Cui, JianTAO. (2017). Research on Project-driven Immersion Teaching Model Based on Extreme Programming Theory. Computer & Telecommunication, 2017 (10), 78-80.
[15] Jiang, Ao-shuang. (2017). Thoughts on Chinese Immersion Program in the United States. Journal of Research on Education for Ethnic Minorities, 2017(3), 95-100.

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