Excessive AI Use: Effect on Perceived Self Efficacy and Self-Concepts Clarity

Abstract

This investigation focuses on the psychological effects and motivational trends that result from using AI tools within educational and occupational frameworks. With 151 participants, this study explored relationships between variables like frequency of AI use, dependency, AI use motivation (both intrinsic and cognitive engagement), and self-concept clarity. AI has begun to be integrated into learning and working environments, and there is a need to look more closely at how it may affect one's sense of self and user motivation. A structured questionnaire was used to collect data from 151 participants, measuring the frequency of AI use, dependence, intrinsic motivation, cognitive involvement, and self-concept clarity. Ratings were recorded on a five-point Likert scale (1-5). Data was analysed using SPSS, including descriptive statistics, reliability testing (using Cronbach's Alpha), exploratory factor analysis (EFA), and multiple regression analysis. The results showed strong positive associations between intrinsic motivation, AI confidence (R² = 0.930), and cognitive engagement (R² = 0.626). Intrinsic motivation, however, was a negative predictor of self-concept clarity (R² = 0.444), meaning that the more motivated and confident users are in using AI, the less clear their self-perception could be. This paradox underscores the dual capacity of AI to enhance productivity whilst immensely complicating the process of self-identification and self-development. People interact with AI with dynamism, self-assuredness, and a sense of agency.  However, overreliance on AI could hinder one's ability to distinguish oneself. These results underscore the psychological burden that AI usage could carry and support the need for students and professionals to design and apply thoughtful and intelligent approaches in balancing different aspects of AI.