## 7 Conclusions and Limitations  
In this study, the design factors and intrinsic motivation factors of AI tools were included in the analysis to explore the factors that affect college students' continuance intentions. In addition, the complex relationships between these multiple factors were rigorously examined using fsQCA, providing detailed insights into their interactions. The research model was validated, and we obtained the following conclusions. First, perceived usefulness is identified as the core factor affecting university students' continuance intentions towards AI tools. Factors such as the system quality, the information quality, and socialized interaction play significant roles in shaping the perceived usefulness, with the information quality playing the most important role. Intrinsic motivation factors have a substantial positive impact on users' intentions to continue using AI tools. The formation of intrinsic motivation is mainly influenced by users' perceived autonomy and perceived abilities, of which perceived autonomy plays the most key role. Satisfaction significantly enhances users' intentions to continue using AI tools. Perceived competence, perceived autonomy, perceived usefulness, and socialization interaction all contribute to the formation of satisfaction, with perceived competence exerting a more pronounced influence. In addition, the fsQCA analysis highlights the importance of high-quality system platforms, rich and accurate information resources, and students' positive perceptions of their own learning abilities in motivating them to continue using AI tools for SDL. These conclusions provide theoretical support for the dissemination and innovative application of AI tools. In order to maximize the potential of AI tools, it is critical to consider both their functionality and utility, as well as students' motivation for SDL. In addition, a mechanism should be considered to improve AI tools and take advantage of their ability to streamline the learning process. Moreover, it is essential to transfer the advantages of AI tools to users and enhance their abilities. This study has certain limitations: Firstly, it mainly focused on the university student demographic, with relatively little exploration of other groups that use AI tools, such as corporate employees, primary and secondary school students, etc. Furthermore, the study focused only on students from China. This could limit the generalizability of the study's conclusions. Future research should include a broader range of user groups to more comprehensively understand the needs and usage patterns of different AI tool users. Secondly, this study mainly focused on factors that have a positive impact on the willingness to continue using and may have overlooked the obstacles, negative experiences, cultural backgrounds, and technology acceptance that might hinder continued use. Cultural differences in educational practices and attitudes towards technology can affect the applicability of the results to other contexts. Therefore, future research could provide a more balanced perspective and offer insights into how to overcome barriers to continued use. Furthermore, a longitudinal approach would allow for a better understanding of how these factors influence students' behaviors and how their importance changes with longer exposure to AI tools. J.Z. : writing--review and editing, writing--original draft, software, methodology, investigation, formal analysis, data curation. H.Z. : writing--review and editing, project administration, methodology, funding acquisition, formal analysis, conceptualization. All authors have read and agreed to the published version of the manuscript. This research was supported by Macao Polytechnic University (RP/FCHS-02/2022) and Macao Polytechnic University (RP/FCHS-01/2023). This research project received ethical approval from the Scientific Research Committee of the Macao Polytechnic University under the approval number RP/FCHS-01/2023/E01. The informed consent was obtained in the survey.