A Personal Growth System Supporting the Sustainable Development of Students Based on Intelligent Graph Element Technology
Fengying Li; Ge Yu; Congjing Mu; Qingshui Xue; Shih-Pang Tseng; Tongchao Wang
In recent years, the sustainable development of education has become an increasing concern, and new technology characterized by intelligence has played an important role in promoting it. However, facing the endless stream of teaching platforms, learning platforms, student management platforms and learning APPs, teachers and students are tired of coping. Meanwhile, there has been a serious lack of real information about student growth, especially in the fields of electronic graphics, and audio and video materials. At present, there is no continuous student growth system that can be used over the course of their life, which is very unfavorable to their individual development. Graphic code is a technology with the potential to solve these problems: however, the existing graphic code technology suffers from clear deficiencies in the realization of a personalized student growth system that incorporates intelligence, security and sustainability. In response to this, this paper proposes a new generation of graphic code technology, namely intelligent graph element technology (IGET). Further, a new sustainable personalized student growth system model is designed based on artificial intelligence, big data analysis and intelligent graph element technologies, and the architecture and implementation of this system platform are completed. Finally, a student growth system based on intelligent code is verified through by an analysis of the results of a questionnaire survey. The research results show that, compared with the traditional student management system, the student growth system based on an intelligent graph element code has obvious advantages in convenience, intelligence, precision, security, and sustainability.
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