Predicting And Classifying User’s Behaviour for Improving Student’s Information Literacy Using Kernel Techniques

Abstract

The rapid development of information technology has led to widespread use of computers and the Internet in various aspects of society. Key skills in the 21st century include creativity, critical thinking, and information literacy. College students need to develop information literacy to adapt to the information society and meet societal expectations. This research develops a prediction model for learning impact based on literacy in information learning behaviour characteristics, exploring the projected learning effect and examining college students' educational behaviour. The study demonstrates the effectiveness of the direct kernel method in improving college students' information literacy, enhancing prediction and classification models, and making it a promising option for intelligent learning settings.