DMP_AI: An AI-Aided K-12 System for Teaching and Learning in Diverse Schools
Zhen-Qun Yang, Jiannong Cao, Xiaoyin Li, Kaile Wang, Xinzhe Zheng, Kai, Cheung Franky Poon, Daniel Lai

TL;DR
The paper presents DMP_AI, an AI-driven K-12 educational platform that leverages data mining, NLP, and machine learning to support personalized teaching, early warning, and talent identification in diverse school settings.
Contribution
It introduces a comprehensive AI-aided system tailored for K-12 education, addressing data heterogeneity and privacy, and demonstrates its deployment in real-world schools.
Findings
Effective prediction of student performance and behavior.
Successful implementation in real-world primary and secondary schools.
Enhanced support for personalized and inclusive education.
Abstract
The use of Artificial Intelligence (AI) has gained momentum in education. However, the use of AI in K-12 education is still in its nascent stages, and further research and development is needed to realize its potential. Moreover, the creation of a comprehensive and cohesive system that effectively harnesses AI to support teaching and learning across a diverse range of primary and secondary schools presents substantial challenges that need to be addressed. To fill these gaps, especially in countries like China, we designed and implemented the DMP_AI (Data Management Platform_Artificial Intelligence) system, an innovative AI-aided educational system specifically designed for K-12 education. The system utilizes data mining, natural language processing, and machine learning, along with learning analytics, to offer a wide range of features, including student academic performance and behavior…
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Taxonomy
TopicsOnline Learning and Analytics
