Application of Human-Computer Interaction Technology in Remote Language Learning Platform

Abstract

In order to realize the deep integration of Internet and education, and realize the efficient allocation and comprehensive coverage of educational resources, the remote language learning platform based on human-computer interaction technology is proposed. The overall architecture of the system is designed with the help of PaaS and IaaS, and the hardware and software of the system are designed according to the overall architecture. In the hardware design, Hibernate framework and SpringJDBC are used to realize the interaction between business logic layer and data layer, and the interaction of language learning function and practice function. In addition, the remote wireless communication module is designed to complete the rapid communication of the system. The learning analysis model is constructed in the software design to determine the actual online learning needs of college students, and the collaborative filtering algorithm is used to recommend online interactive learning information data, so as to realize the function of long-distance language online interactive learning system in colleges and universities. The experimental results show that with the increase of the number of users, the page jump time of the three functions such as sending information, submitting homework and asking for leave are all below 0.04 s, especially the page jump time of the function of sending information always keeps the lowest. The login or registration function takes a long time to go back to the page. The maximum value is about 0.07 s. The results show that the system can still show excellent operation ability for large-scale users, and the sending information rate is fast, and the remote online interaction effect has obvious advantages.

Keywords:

• Cloud platform
• distance learning
• online learning
• online education
• learning system
• the human-computer interaction

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

Yuanyuan Yang is responsible for the writing and communication of the manuscript, Wei Bao is responsible for the data analysis, data preparation and modification of the manuscript.

Data availability statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author/s.

Additional information

Notes on contributors

Yuanyuan Yang

Yuanyuan Yang received the B.S. degree from LiaoNing Normal University in 2012, and the Ph.D. degree from Minzu University of China. She is currently an associate professor with Bohai University. Her current research interests include computational linguistic, mapping knowledge domain, minority language information processing.

Wei Bao

Wei Bao received the B.S. degree from Jiangsu Normal University in 2015 and the Ph.D. degree in computational linguistics from Minzu University of China in 2019. She is currently an engineer in China Electronics Standardization Institute. Her research interests include natural language processing, speech recognition and artificial intelligence standardization.