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A Digital Class Adviser System for Education and Training Based on Artificial Intelligence and Robotic Process Automation

Author(s)

Guangpeng Liu, Han Zhang*, Zhuoyue Li, Yanheng Zhao, Kaili Guo, Zhan Shi, Chen Qi

Affiliation(s)

State Grid of China Technology College, Jinan, Shandong, China *Corresponding Author

Abstract

This paper presents the functional design of a Digital Class Adviser for education and training, drawing on the integration of a teaching and training big data system into the State Grid E-learning Platform. The design addresses routine administrative work, fragmented information, and the need for timely communication between class advisers and trainees. It combines a digital business platform enabled by artificial intelligence (AI) with robotic process automation (RPA). The platform integrates training resources and data, while RPA executes predefined workflows for trainee dispatch, attendance, evaluation, and examination. Supporting modules include optical character recognition, class group notifications, knowledge-based question answering, voice interaction, and report generation. The paper describes the information displayed in each scenario, the tasks assigned to software robots, and the review activities retained by class advisers. These functions are intended to reduce repetitive administrative work and improve the coordination of training activities. The contribution is a scenario-based system design; improvements in cost, efficiency, and learning outcomes remain to be established through empirical evaluation.

Keywords

Artificial Intelligence; Robotic Process Automation; Education; Training; Digital Transformation

References

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