The Impact of AI-Assisted Learning Experience Based on the ARCS Model on Management Students’ Learning Outcomes

<jats:p>The use of AI-assisted teaching in management education is becoming more common; nonetheless, the underlying structure of the learning experience and the mechanisms by which it affects learning outcomes warrant additional investigation. Based on the ARCS model, this study categorizes the learning experience of AI-assisted education into four dimensions—attention, relevance, confidence, and satisfaction—and develops a model of its impact on management students’ learning outcomes. This study analyzed data from 396 undergraduate students majoring in management using PLS-SEM. SPSS 26.0 was utilized for reliability and validity testing, as well as descriptive statistical analysis, and SmartPLS 4.0 was employed to assess the measurement and structural models. The results indicate that all four dimensions of the learning experience have a significant positive impact on learning outcomes, with confidence-building having the strongest effect (β= 0.319), followed by perceived relevance (β= 0.273), satisfaction (β= 0.233), and attention stimulation (β= 0.163). The model’s explanatory power was R2= 0.515, with a good model fit (SRMR = 0.052, NFI = 0.878). This study proved the applicability of the ARCS model in AI-assisted teaching contexts and provides theoretical guidance for the design and evaluation of AI tools in educational administration.</jats:p>