This study aims to examine design students' intention towards using Artificial Intelligence-aided Design Tools (AIDTs). An extended model is developed by combining the affective-cognitive consistency theory with the Unified Theory of Acceptance and Use of Technology (UTAUT). Data are collected through online comments from Chinese streaming media platforms and responses from a survey involving 313 Chinese students, with subsequent analysis using Partial Least Squares and Structure Equation Modeling (PLS-SEM) statistical techniques and Natural Language Processing (NLP). The results reveal that technophobia, perceived enjoyment, performance expectancy, and effort expectancy directly affect the intention of design students to use AIDTs. Additionally, social influence, facilitating conditions, and subjective knowledge indirectly influence this intention. Technophobia, perceived enjoyment, and subjective knowledge emerge as critical determinants. The proposed framework offers insights for AIDTs developers to enhance user experience, while educators are encouraged to provide requisite training and incentives to motivate design student's engagement with AIDTs.