Primary science curriculum student acceptance of blended learning: structural equation modeling and visual analytics

This paper focuses on the analysis of perceived usefulness (PU), perceived ease-of-use (PE), perceived playfulness (PP), community support (CS), and other factors that affect the acceptance of Chinese students (SA) in Blended learning of primary science curriculum. Based on technology acceptance model and Unified Theory of Acceptance and Use of Technology, an initial structural equation model is proposed. The initial structural model is for blended learning student acceptance (SA) in primary science curriculum. It contains five latent variables, and 4 latent variables can affect SA. Questionnaire responses are collected through blended learning SA questionnaire survey and analyzed using statistical methods. The questionnaire has 25 questions and collects 357 answers from all over China. Based on the reliability analysis, exploratory factor analysis, and confirmatory factor analysis of the data, the initial structural equation model is improved. According to the final structural equation model, the influence order of influencing factors on primary science curriculum blended learning SA is CS > PP > PU > PE. Based on the final model, an interactive visualization application is designed and implemented using SAP Analytics Cloud to allow users to understand the model easily and explore interactions among these factors visually. Teachers can directly see the changes of various factors through visualization, and do not need to pay attention to complex model details. This approach provides new practice for the application of theoretical models in Pedagogy.