Impact of AI-Integrated Cognitive and Physical Training Programs on Decision-Making and Skill Acquisition among College Students

Abstract

The integration of Artificial Intelligence (AI) in education and training environments has transformed traditional learning paradigms. This study investigates the impact of Artificial Intelligence (AI)-integrated cognitive and physical training programs on decision-making, skill acquisition, motivation, and engagement among college students. Using an experimental pre-test–post-test control group design, 120 undergraduate participants were divided into an experimental group (AI-integrated training) and a control group (traditional training). Standardized instruments, including the Decision-Making Accuracy Scale (DMAS), Reaction Time Test (RTT), Skill Acquisition Index (SAI), and Motivation and Engagement Scale (MES), were employed to measure key outcomes. Statistical analyses using t-tests and ANOVA revealed significant improvements in the experimental group across all parameters—decision-making accuracy (p < 0.01), reaction time (p < 0.05), skill acquisition (p < 0.01), and motivation and engagement (p < 0.01). The findings demonstrate that AI-driven training enhances learners’ cognitive processing speed, problem-solving accuracy, and intrinsic motivation by providing adaptive, data-informed, and personalized feedback. Moreover, the AI environment fostered higher consistency in performance and deeper learner engagement, confirming the holistic benefits of integrating cognitive and physical learning domains. The study concludes that AI-based personalized programs can effectively enhance both intellectual and affective dimensions of learning, preparing students for complex, technology-driven academic and professional contexts. It further emphasizes the need for ethical implementation and long-term evaluation to maximize AI’s transformative potential in higher education.