The Effects of an AI-Supported Illustration Design Learning System on University Students’ Achievement and Motivation

Abstract

This study investigated the effects of an AI-Supported Illustration Learning System (AILS) on university students’ learning achievement and motivation in illustration design. The study was motivated by the limited support for immediate and personalised feedback in conventional learning systems (CLS), which may limit students’ learning achievement in illustration design. A quasi-experimental design was adopted, with learning mode (AILS versus CLS) serving as the independent variable and learning achievement and motivation as the dependent variables. A total of 60 undergraduate students from a university in China participated in the study. ANCOVA was conducted to examine differences in learning achievement, while an independent-samples t-test was used to compare motivation between the two groups. The findings revealed that students who learned through AILS achieved significantly higher learning achievement and reported higher motivation than those who learned through CLS. Overall, the findings suggest that AILS can enhance students’ learning achievement and motivation in illustration design education.