This article reports on a study that investigated user acceptance of a high-immersion virtual reality learning environment to learn English paragraph writing structure. 134 undergraduate university students participated in the study by using a high-immersion virtual reality system combined with an in-house developed virtual reality learning environment program for the purpose of learning paragraph structure. A post-session questionnaire was used to collect data. A partial least squares structural equation modelling (PLS-SEM) analysis was then conducted to test an extended technology acceptance model conceptualized from a priori theoretical deduction and previous empirical findings. The extended model featured the constructs of Imagination, Immersion, and Interaction as exogenous variables with Perceived Ease of Use and Perceived Usefulness in mediating roles leading to the endogenous construct of Behavioral Intention to Use. Results of the confirmatory PLS-SEM analysis revealed inherent problems with the model's application to the high-immersion virtual reality system and program used. Considering these findings, a PLS-SEM exploratory model optimization analysis was conducted which saw the variable of Immersion best relocated to be a predicator for both the Interaction and Imagination constructs. This exploratory model showed superior predictive relevance and improved significance of the relevant construct paths. Based on these results, this paper provides new theoretical reasoning that is in line with these statistical findings, namely that the construct of Immersion is best positioned as a singular external exogenous variable impacting Interaction and Imagination for the high-immersion virtual reality technology acceptance model used in this study.

本文报告了一项研究，该研究调查了用户对高沉浸式虚拟现实学习环境以学习英语段落写作结构的接受程度。134名大学生使用高浸入式虚拟现实系统和内部开发的虚拟现实学习环境程序相结合的方式参与了本研究，以学习段落结构。会后调查表用于收集数据。然后进行了局部最小二乘结构方程模型（PLS-SEM）分析，以测试从先验理论推论和先前经验发现概念化的扩展技术接受模型。扩展模型具有“想象力”，“沉浸感”，“ 和交互作用作为具有感知易用性和感知有用性的外生变量，在中介作用中导致内在构造行为意图使用。验证性PLS-SEM分析的结果揭示了该模型在高浸入式虚拟现实系统和所用程序中的应用所固有的问题。考虑到这些发现，进行了PLS-SEM探索性模型优化分析，发现浸入变量最佳地重新定位为交互和想象构造的谓词。该探索性模型显示出较高的预测相关性，并改善了相关构建路径的重要性。基于这些结果，本文提供了与这些统计结果相符的新的理论推理，