This study investigates integrating Virtual Reality (VR) technology with the Goal-Based Scenario (GBS) learning theory in tree risk assessment education. The aim was to enhance students’ learning performance and understanding of Visual Tree Assessment (VTA) methods through a GBS-based SVVR Tree Risk Assessment Assisted Learning System (hereafter referred to as the SVVR-GBS system) that simulates real-world risk assessment scenarios. The research was conducted with forestry students at the University of Science and Technology, employing a quantitative approach to assess the SVVR-GBS system’s impact on students’ learning outcomes, cognitive load, and acceptance. Results showed that the SVVR-GBS system significantly improved students’ learning performance while managing cognitive load effectively. Moreover, students demonstrated high acceptance of the SVVR-GBS system. The findings indicate that integrating VR and GBS in tree risk assessment education offers a promising approach to enhancing learning outcomes and engagement.