The effects on the personalized learning platform with machine learning recommendation modules: Focused on learning time, self-directed learning ability, attitudes toward mathematics, and mathematics achievement

The purpose of this study is to verify the effects of personalized learning platforms applied with machine learning recommendation modules that upgrade recommended algorithms by themselves through learning big data analysis on students' learning time, self-directed learning ability, mathematics achievement, and attitudes toward mathematics, and the correlation between them.According to the study, customized learning affected learning time, self-directed learning ability and mathematics attitude, while learning time affected self-directed learning ability.Self-directed learning ability has had a significant impact on the attitude of mathematics and mathematical achievements.As a result of the mediated effectiveness test, the indirect impact of customized learning on mathematics attitude and mathematics performance was significant through the medium of learning time and self-directed learning ability.