Raw Data_Factors Influencing E-learning Continuance Intention Among EFL Students

The dataset, "Raw Data_Factors Influencing E-learning Continuance Intention Among EFL Students," was collected from 567 university students at Guizhou University of Finance and Economics, China, using the Wenjuanxing platform (www.wjx.cn) between August and October 2024.   The survey focused on examining the relationship between five key factors—perceived usefulness (PU), perceived ease of use (PEOU), confirmation (CON), perceived enjoyment (PE), and satisfaction (SAT)—and their influence on students' continuance intention (CI) to engage with e-learning.   After cleaning the data for invalid responses, the dataset includes valid responses from 435 participants.   The study applied structural equation modeling (SEM) to assess how these factors, along with the mediating role of SAT, contribute to e-learning CI among English as a Foreign Language (EFL) students.   This dataset offers valuable insights into the dynamics of e-learning in the context of foreign language education, and can be used for further research into improving student engagement and satisfaction in online learning environments.