Editor's Note: General Secretary Xi Jinping emphasised at the National Conference on Education that the national education digitalisation initiative should be fully implemented, with efforts to expand the coverage of high-quality education resources and improve public services for lifelong learning.
The Open University of China (OUC) has thoroughly implemented the educational digitalisation strategy, actively promoted the deep integration of digital technology and education, and been committed to building a ubiquitous and accessible lifelong education system. It has carried out numerous beneficial explorations in digital empowerment for lifelong learning, achieving tangible results.
The rapid development of generative artificial intelligence (AI) technology is profoundly transforming traditional teaching service models and gradually becoming a key force in driving educational service innovation. Its powerful semantic understanding and content generation capabilities provide strong technical support for creating efficient and convenient intelligent customer service. Currently, intelligent customer service systems based on generative AI technology have been fully launched in fields such as AI majors, education for the elderly, and open education. These systems have been integrated with existing teaching platforms to provide 24/7 instant consultation services for different learner groups and academic fields, initially forming an intelligent customer service system that covers various educational services of the Open University of China (OUC).
AI Assistant for AI Majors
The first AI service assistant exclusively for AI major students has been developed, offering policy interpretation and student affairs consultation services. This AI service assistant relies on large language models and integrates various knowledge bases such as teaching schedules, academic management, and professional policies. It deeply understands students' inquiries and engages in smooth and coherent multi-turn dialogues, providing detailed procedural guidance and personalised advice on process guidance, information queries, common issues, and problem-solving, thereby enhancing service efficiency and consultation experience.
"Little Leaf" Intelligent Customer Service for Seniors University
An intelligent customer service system named "Little Leaf" has been built for elderly learners, offering comprehensive, personalised business consultation services. "Little Leaf" deeply integrates large language models with knowledge bases related to elderly education, answering questions regarding registration, functionality guidance, course consultation, and event participation. The system emphasises age-friendly design, providing convenient voice interaction services for more natural and smooth communication, thus facilitating intelligent assistance for the elderly, making learning barrier-free and enjoyable.
One Network One Platform Intelligent Customer Service
The One Network One Platform intelligent customer service system has been iteratively upgraded to bring a more flexible and convenient user experience to teachers and students. The system establishes a dynamic knowledge base update mechanism based on user feedback, continuously optimising and supplementing knowledge base content to enhance the accuracy and comprehensiveness of generated content. Additionally, the system has developed a collaborative service model that combines intelligent and human customer service. When users encounter complex issues, they can get professional and timely human assistance, which improves problem solving efficiency.
In the future, the OUC will continue to improve the intelligent customer service system based on AI infrastructure, with a focus on deep customisation to meet the needs of different learner groups and learning fields, ensuring comprehensive and personalised services. The OUC will also continuously optimise the knowledge base and improve interaction capabilities to provide a more intelligent, efficient, and thoughtful service experience to all teachers and students.
Department of Digitalisation