Configuring Factors Influencing Science Teachers' Intention to Use Virtual Experiments in China: An fsQCA-Based Study

The multiple benefits of virtual experiments applied to science education depend heavily on science teachers' intentions to use them. The inducing mechanism is a process that combines different conditions of multiple factors. From the perspective of overall configuration, this study used the fuzzy-set qualitative comparative analysis (fsQCA) method, based on the unified theory of acceptance and use of technology 2 (UTAUT2), to construct a causal explanation model of Chinese K-12 science teachers' intentions to use virtual experiments. Additionally, the snowball method was used to conduct a questionnaire survey of 342 Chinese K-12 science teachers. The results show that different conditions of the seven factors, performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV), and habit (H), do not have the necessary explanatory power for the results. Three paths for science teachers' high intentions to use virtual experiments were obtained by configuration analysis: Configuration 1 (PE*EE*SI*HM*PV*H), Configuration 2 (EE*SI*FC*PV*H), and Configuration 3 (PE*EE*FC*HM*H). These findings effectively broaden the scope of knowledge and interpretation of the original inductive mechanism of intentions to adopt technology. They provide theoretical and practical support for education departments to design more targeted programs to improve the ability of science teachers to apply virtual experiments in K-12 education. Finally, future research directions are explored.