DOI: https://doi.org/10.61957/joerai-20240205

Title: Research on AI-assisted Education Based on the "use and Satisfaction" Theory in Communication Studies

Author: Jiaxin Qin, Qiang Shi

Abstract

With the rapid progress of artificial intelligence technology, especially in the fields of natural language processing, machine learning, deep learning and other significant breakthroughs, AI technology has shown a wide range of application prospects in the field of education. It is of great academic and practical value to conduct in-depth research on AI-assisted education based on the theory of "use and satisfaction". Under this framework, students are no longer limited to passively receiving knowledge, but can actively choose and use AI tools to meet their individual learning needs. This paper focuses on how AI-assisted education can effectively map the "use and satisfaction" theory, and aims to comprehensively explore its potential advantages and possible challenges. At the same time, this paper also deeply analyzes the current problems in AI-assisted education, and puts forward targeted circumvention or solutions, in order to provide strong support for promoting innovation and development in the education field. With the rapid progress of artificial intelligence technology, especially in the fields of natural language processing, machine learning, deep learning and other significant breakthroughs, AI technology has shown a wide range of application prospects in the field of education. It is of great academic and practical value to conduct in-depth research on AI-assisted education based on the theory of "use and satisfaction". Under this framework, students are no longer limited to passively receiving knowledge, but can actively choose and use AI tools to meet their individual learning needs. This paper focuses on how AI-assisted education can effectively map the "use and satisfaction" theory, and aims to comprehensively explore its potential advantages and possible challenges. At the same time, this paper also deeply analyzes the current problems in AI-assisted education, and puts forward targeted circumvention or solutions, in order to provide strong support for promoting innovation and development in the education field.