Construction of Personalized Learning Mode for Higher Mathematics in Vocational Education Based on Artificial Intelligence

Abstract

With the inclusion of artificial intelligence (AI)in vocational education, there comes new chances to improve on how higher mathematics gets taught and learned. Traditional methods used for instruction in vocational college cannot cater to the varying mathematical base, speed of learning and mode of thinking among students thus leading to big differences in achievement as well as loss of interest. This paper proposes and examines a comprehensive AI-based personalized learning mode specifically designed for higher mathematics instruction in vocational education contexts. Based on the theories of adaptive learning, cognitive load theory and mastery learning theory, it is expected that a personalized learning path could be realized by combining ML algorithms, KGs and ITS. From the empirical data that I have obtained after doing a 16 weeks intervention with 240 vocational college students, we can look into how effective this model is. Student's math performance has improved a lot, they are more engaged and confident too. Four data table give out the comparison on a way of performance metric, learning styles distribution, adaptation strategy matching and satisfied result. It will contribute to academic researches about AI-enhanced Education and also have practical significance for curriculum developer, instructors, administrator in vocational education.