Impact of cognitive load reduction in artificial intelligence enhanced in smart education and smart research

This study investigates how to reduce cognitive load through AI in smart education and research, emphasizing the roles of user technological confidence and ethical transparency by cognitive load theory. The reduction in cognitive load is proposed to enhance user engagement and performance, with user technological confidence acting as a mediator. The research uses quantitative analysis with 360 respondents, including staff, students, policymakers, and administrators. SPSS and SEM using Smart PLS 4.0 software are employed for data analysis. The results bring out the design of AI to improve efficiency and build user confidence. Ethical integrity, thereby maximizing their impact on smart education and research. These findings suggest that organizations and developments must prioritize user-centered and ethically transparent designs to fully understand AI’s potential in transforming education research landscapes. The implications of the improving capacity of AI smart education research emphasize the importance of reducing cognitive load and promoting ethical transparency and confidence in technologies. Furthermore, ethical transparency plays an important role in strengthening user trust and approving AI systems. Transparent AI systems that are clear about data usage, fairness, and decision-making processes can mitigate concerns about misuse and bias, fostering a more trusting and productive relationship between users and technology.