Optimization of Elderly Education Community Learning System Based on Kano Model and Deep Learning

The rapid development of artificial intelligence (AI) technology and deep learning (DL) algorithms is profoundly changing the service model in the field of education. Especially in the context of the accelerated aging process in Chinese society, how to use computer technology to improve the quality of elderly education has become an important issue that urgently needs to be addressed. The current online learning platforms targeting the elderly generally suffer from uneven quality and poor user experience, making it difficult to meet the growing learning needs of the elderly. In response to this situation, this article innovatively proposes an elderly education learning system based on the Kano model, and constructs a personalized learning recommendation model that integrates DL technology. The system has undergone comprehensive aging friendly modifications to the user interface based on the physiological characteristics and usage habits of the elderly; At the same time, the system deeply mines the learning behavior data of elderly people through DL algorithm, and combines their learning records and interest preferences to achieve accurate recommendation of personalized learning resources. The results indicate that our designed system can meet the educational needs of the elderly, providing useful references for the construction and optimization of information-based community learning systems for elderly education.