Abstrait

Analysis of the virtual learning community user adoption behavior based on perceived risk

Aiping Xie

Purpose: The virtual learning community plays an important role in the distance education. In the modern distance education, student’s learning process is a student’s interacting process with other network teaching components, including human-computer interaction, interaction of contents and interpersonal interaction.

Design/Methodology/approach: This paper is to explain the adoption behavior of virtual learning community users, through the questionnaire data collection, and usage the structural equation model to verify the perceived risk of virtual learning community user adoption behavior effect, thus put forward the strategy to reduce the user perceived risk.

Findings: In this paper, it uses Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to measure the scale reliability and validity of the model. In order to test whether scale is suitable for exploratory factor analysis, it needs to calculate KMO and Bartlett sphere test in advance. The results show KMO value is 0.804, and the test results show that it is suitable for factor analysis. Based on TAM theory, the article analyses user adoption behavior of virtual learning community for real-time interaction and completes the learning task in the distance education from the user perceived risk perspective.

Originality/Value: This paper puts forward the relationship between perceived risk model of user in virtual learning community utilizing structural equation modelling and regression testing of hypotheses.