TY - GEN
T1 - DMP_AI: An AI-Aided K-12 System for Teaching and Learning in Diverse Schools
AU - Yang, Zhenqun
AU - Cao, Jiannong
AU - Li, Xiaoyin
AU - Wang, Kaile
AU - Zheng, Xinzhe
AU - Poon, Kai Cheung Franky
AU - Lai, Daniel
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - 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 AIaided 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 prediction, early warning system, analytics of Individualized Education Plan, talented students’ prediction and identification, and cross-school personalized electives recommendation. The development of this system has been meticulously carried out while prioritizing user privacy and addressing the challenges posed by data heterogeneity. We successfully implemented the DMP_AI system in real-world primary and secondary schools, allowing us to gain valuable insights into the potential and challenges of integrating AI into K-12 education in the real world. This system will serve as a valuable resource for supporting educators in providing effective and inclusive K-12 education.
AB - 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 AIaided 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 prediction, early warning system, analytics of Individualized Education Plan, talented students’ prediction and identification, and cross-school personalized electives recommendation. The development of this system has been meticulously carried out while prioritizing user privacy and addressing the challenges posed by data heterogeneity. We successfully implemented the DMP_AI system in real-world primary and secondary schools, allowing us to gain valuable insights into the potential and challenges of integrating AI into K-12 education in the real world. This system will serve as a valuable resource for supporting educators in providing effective and inclusive K-12 education.
U2 - 10.48550/arXiv.2412.03292
DO - 10.48550/arXiv.2412.03292
M3 - Conference article published in proceeding or book
SN - 0302-9743
VL - 14797
T3 - Lecture Notes in Computer Science (LNCS)
SP - 117
EP - 130
BT - Blended Learning. Intelligent Computing in Education - 17th International Conference on Blended Learning, ICBL 2024, Proceedings
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th International Conference on Blended Learning, ICBL 2024
Y2 - 29 July 2024 through 1 August 2024
ER -