Digital Wellness among Students and Faculty in AI-Enabled Learning Environments: Impact on Academic Productivity and Psychological Well-being

Abstract

The challenge of digital wellness has emerged as one of the most important in the field of AI-enabled learning where the increasing popularity of artificial intelligence tools has changed teaching and learning practices and brought a range of concerns like cognitive overload, screen burnout and diminished interpersonal communication. The overall goal is to investigate the connection between digital wellness, academic productivity, and psychological well-being between the students and faculty involved in AI-facilitated education. The research design chosen is a mixed-method study that applies both the survey method, which employed 200 participants of various academic backgrounds and cross-sectional survey. Descriptive statistics, correlation analysis and paired sample t-tests were used to analyze data examining relationships and differences among key variables. The results show that there is a strong positive relationship between digital wellness and academic productivity, which means that mindful use of digital devices results in increased learning effectiveness and efficiency. Further, psychological well-being increases moderately and positively in response to exposure to AI-enabled tools indicating that it brings increased confidence and less academic stress. But the findings also point to heightened screen fatigue as an important barrier to the longer digital interaction. This discussion focuses on the two-sided character of AI integration, which provides some opportunities to improve learning and factors detrimental to mental and physical health. The conclusion lays emphasis on the concept of a balance between digital and sustainable academic success. Implications underscore institutional policies of healthy technology usage, with shortcoming being in terms of smaller sample and cross-sectional design. Long-term implications and the effective intervention should be studied using longitudinal and experimental study methods in the future.