Abstract:

Because of advancements in information technology, online learning has been extensively used. Primary school kids, on the other hand, have less relevant assessments and applications. All learning innovation activities are aimed at enhancing educational quality by establishing an active learning environment for students. Students' engagement in the teachinglearning process may be increased by choosing learning resources that are suited for the student's learning style. The study's goal is to create and assess the effect of an AI-based learning style prediction model in an online learning portal for primary school children. The topics were drawn from Indonesian elementary school pupils in grades four through six. The AI model in the online learning portal was created to propose learning resources that fit students' learning styles, in order to meet the notion of individualised learning. We developed a novel AI technique that allows collaborative filteringbased AI models to be powered by learning style prediction. Using this AI system, the online learning portal may deliver content suggestions suited particularly to each student's learning style. The AI model performance test yielded acceptable results, with an average RMSE (Root Mean Squared Error) of 0.9035 on a scale of 1 to 5. Furthermore, the findings of a t-test study on 269 individuals between pre-test and post-test scores increased students' learning performance

Description:

Online learning, learning style prediction, artificial intelligence, personalized learning, primary school.