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Assessment of User Acceptance of an AI-Driven Career Guidance Model: A UTAUT-Based Quantitative Study

Domaine:

education

Type de record:

papermodel
Créateur:
BisFav
Éditeur:
AMO Publisher
Hôte:avatar

This study investigates the factors influencing the adoption of an AI-driven career guidance platform among computing students in Uganda. Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, extended with the construct of Digital Confidence (DC), we conducted a user-based quantitative evaluation. Data were collected from 957 participants across 13 public and private universities. Structural Equation Modeling (SEM) was employed to test theoretical relationships. The results reveal that Performance Expectancy and Effort Expectancy are the strongest predictors of Behavioral Intention. Furthermore, while users expressed strong intentions to adopt the system, Facilitating Conditions emerged as a critical determinant of actual usage behavior. This study provides empirical evidence on user readiness and highlights the psychological and infrastructural factors necessary for the successful integration of AI in low-resource higher education settings.

Visit

doi.org

Tags

AI adoptionUTAUTStructural Equation ModelingCareer GuidanceDigital Confidence

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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