ML techniques used to a web-based intelligent learning diagnostic system

Abstract

By providing learners with the opportunity to select learning topics in which they are interested and gain knowledge on the specific topics through Internet research for related learning courseware and discussion of what they have learned with their colleagues, this work proposes an intelligent learning diagnosis system that supports a Web-based learning model based on a thematic approach. An intelligent diagnostic system uses log files that record students' prior online learning behavior to provide suitable learning assistance to help students improve their study habits and get better grades for online class participation. According to our findings from the experiments, the suggested learning diagnosis system may effectively assist learners in broadening their knowledge while using a "theme-based learning" paradigm in cyberspace.