A study on how to improve students' continuance intention in landscape architecture conservation course within a virtual learning environment based on SVVR

Abstract

With the rapid pace of global urbanization, preserving natural landscapes has become increasingly critical. However, urbanization presents significant environmental risks worsened by decreased ecological consciousness. This has led to a pressing demand for education in landscape conservation. While university curricula begin to focus on this area, the shortcomings of conventional teaching methods are apparent, especially in technology-supported learning. Therefore, it is crucial to incorporate cutting-edge technologies to devise novel educational strategies that improve students' learning experiences and achievements. Based on the relevant variables from the UTAUT model, coolness theory, and flow theory, this study constructs a structural equation model to assess students' intention to continue using SVVR teaching materials. The model includes external factors like performance expectancy, effort expectancy, perceived sustainability, self-efficacy, flow, and perceived coolness. A survey of 382 students was conducted, and the data were analyzed using structural equation modeling (SEM). Results indicated that: 1) students' intention to use SVVR educational resources is significantly affected by their attitude and flow; 2) performance expectancy, effort expectancy, perceived coolness, perceived sustainability, and self-efficacy have a positive impact on attitude, whereas flow does not directly affect attitude, and 3) there is a positive relationship between self-efficacy and flow. These insights are instrumental in developing and implementing SVVR educational materials for landscape conservation classes. They confirm the utility of the expanded UTAUT model, providing a methodological framework for its use in similar settings.