Relationship between Cognitive Load and AI Dependence among University Teachers: Moderating role of Decision Making Styles

Abstract

As the highly robust environment of higher education keeps progressing, university instructors face increasing cognitive imposition due to their multi-role task nature and growing integration of technology in learning. This study investigates the relationship between cognitive load, decision making styles (rational, intuitive) and dependence on artificial intelligence (Al) among university teachers. Data were collected from 240 faculty members of both public and private sector universities in Islamabad and Rawalpindi. A cross-sectional survey design was employed and the Cognitive Load Theory was implemented. Cognitive load (NASA-TLX), Al dependence, and decision-making styles (rational and intuitive) were assessed using standardized instruments. Results established a significant positive correlation between cognitive load, decision making styles and AI dependence. The findings highlight the need for proficient cognitive strategies and measured integration of Al in educational settings to prevent over-reliance and preserve critical thinking. This research contributes to the literature on educational psychology and technology integration and offers practical implications for policy makers and educators in curating focused interventions and training programs to enhance decision-making competence and manage cognitive demands in academic environments.