This study offers methodological synergy in the examination of factorial structure in second language (L2) research. It illustrates the effectiveness and flexibility of the recently developed exploratory structural equation modeling (ESEM) method, which integrates the advantages of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) into one complete measurement model. Two sets of data were collected using the L2 Passion Scale, which measures a dualistic model of passion. Study 1 participants were 220 L2 students. A comparison was made between the CFA and the ESEM models. The results demonstrated the superiority of the ESEM method relative to CFA in terms of better goodness-of-fit indices and realistic correlated factors. These results were replicated in another sample of 272 L2 students, providing support for the predictive validity using a structural ESEM model. Guidelines are provided and Mplus syntax files (codes) are included to help analysts apply the methods. We also make the data available publicly. Overall, this research demonstrated the usefulness of ESEM for examining the construct, discriminant, and convergent validity of L2 scales over CFA.

本研究为检验第二语言 (L2) 研究中的因子结构提供了方法学协同作用。它说明了最近开发的探索性结构方程模型 (ESEM) 方法的有效性和灵活性，该方法将探索性因素分析 (EFA) 和验证性因素分析 (CFA) 的优点集成到一个完整的测量模型中。使用 L2 激情量表收集了两组数据，该量表测量激情的二元模型。研究 1 的参与者是 220 名 L2 学生。对 CFA 和 ESEM 模型进行了比较。结果证明了 ESEM 方法在更好的拟合优度指标和现实相关因素方面相对于 CFA 的优越性。这些结果在另一个包含 272 名 L2 学生的样本中得到复制，使用结构 ESEM 模型为预测有效性提供支持。提供指南并包含 Mplus 语法文件（代码）以帮助分析人员应用这些方法。我们还公开提供数据。总的来说，这项研究证明了 ESEM 在检查 L2 量表相对于 CFA 的结构、判别和收敛有效性方面的有用性。