Extended TAM Model Analysis of Continuous Use Factors and Psychological Well-Being on University Learning Platforms

Abstract

This study investigates the elements inspiring the continuous usage of intelligent learning systems in advanced educational environments emphasizing technological and psychological aspects. The present work investigates how perceived trust, perceived enjoyment, and ideological alignment affect user involvement and retention using an updated Technology Acceptance Model (TAM). Moreover, taken under more importance as a better understanding of user behavior are psychological elements such as user contentment, perceived fear, and expectation confirmation. Structural equation modeling (SEM) was used to evaluate data taken from a structured questionnaire. The study underscores the relevance of user experience and shows that, with a path coefficient = 0.52, p < 0.001, subjective satisfaction is the most important factor of continuous usage intention. Path coefficient = -0.13, p = 0.05 indicates that perceived trust negatively affects contentment mostly because of unmet expectations generating discontent. Though expected confirmation increases perceived usefulness (path coefficient = 0.31, p < 0.01) system quality does not affect on satisfaction (path coefficient = 0.05, p > 0.05). The outcomes highlight the requirement of platform developers to give realistic management of customer expectations top priority, matching platform features with user requests, and creating interesting and engaging user experiences a top priority. These pragmatic findings provide fast fixes to boost user participation and improve the utilization of intelligent learning technology in learning settings.