Unlocking AI-Powered Tools Adoption among University Students: A Fuzzy-Set Approach

This study examines, from a post-pandemic theoretical perspective, university students' continuous intention (CI) to utilise AI-powered tools for educational purposes. AI-powered tools are new and underutilised in higher education. The fact that students and teachers need knowledge to use these apps in the classroom compounds the issue. Despite this technology's recent academic introduction, nothing is known about its impacts. In order to investigate the variables that influence the continual intention to employ artificial intelligence, this study discusses the possibility of integrating the self-determination theory (SDT) and technology acceptance model (TAM) with the post-acceptance model (PAM). Three hundred forty university students were solicited to complete a questionnaire to collect data for the proposed model. A dual-stage approach uses both symmetrical assumptions from structural equation modelling with partial least squares (PLS-SEM) and asymmetrical configurations from fuzzy-set qualitative comparative analysis (fsQCA). In order to better comprehend the intricate interplay between the model's inputs and its desired output, this approach is devised. Consideration is given to the fact that various configurations of external constructs exert distinct influences on internal constructs. In Thailand, perceived usefulness (PU) and autonomy predict continued AI-powered tool use. Perceived ease of use (PEOU) did not affect continuing intention. Conclusions drawn from the configurational analysis show that no single factor adequately explains a high CI level. Rather, three distinct configurations were identified as improving CI using AI-powered tools. Overall, theoretical and practical ramifications are addressed.