Strategic Digital Learning Platform Utilization: the Roles of User Experience, Trust, and Task–Technology Fit

Abstract

The rapid development of digital technologies has transformed how individuals utilize digital learning platforms for knowledge sharing, collaboration, and professional development. Previous studies have primarily examined technology adoption factors separately, while limited research has integrated user experience, trust, and task–technology fit within a single framework to explain behavioral intention and actual use behavior. Therefore, this study aims to analyze the effects of user experience, trust, task characteristics, and technology characteristics on task–technology fit, behavioral intention, and use behavior in digital learning platforms. A quantitative approach was employed using survey data collected from 200 active users of digital learning platforms involved in educational and professional learning activities. Data were analyzed using descriptive statistics and multiple regression analysis. The results indicate that task characteristics (β = 0.31, p < 0.001) and technology characteristics (β = 0.37, p < 0.001) significantly influence task–technology fit (R² = 0.44). User experience (β = 0.34, p < 0.001), trust (β = 0.29, p < 0.001), and task–technology fit (β = 0.28, p < 0.001) significantly affect behavioral intention, explaining 48% of the variance (R² = 0.48). Behavioral intention also significantly influences use behavior (β = 0.41, p < 0.001), with R² = 0.36. These findings demonstrate that positive user experience, trust, and alignment between platform capabilities and user tasks contribute to stronger behavioral intention and actual platform usage. This study contributes to the literature by proposing an integrated user-level model that combines user experience, trust, and task–technology fit to explain digital learning platform utilization.