ABSTRACT With a growing interest in research on educational processes, there is a need to overview suitable latent variable models for students' learning experiences in real-time. This tutorial provides an introduction to intraindividual (multilevel) structural equation models (ISEM) for the analysis of process data (e.g. intensive longitudinal, intraindividual, diary, or person-period data) collected in educational settings. Using example data on 202 students' ecological momentary assessment of 10 to 24 reports (M = 14.9, SD = 3.2), of controlled (extrinsic) and autonomous (intrinsic) motivation the following models are presented: (1) measurement models and covariate effects models; (2) models for fixed, random, and moderator effects; and (3) models for reciprocal effects of chronologically ordered data. Step-by-step instructions for modelling, and substantive interpretations are given. Overall, ISEM establishes an important window into research on real-time educational processes.

中文翻译：

---

用于学习经验的个体内结构方程模型

摘要随着对教育过程研究的兴趣日益浓厚，有必要概述适合学生实时学习经验的潜变量模型。本教程介绍了个人（多级）结构方程模型（ISEM），用于分析在教育环境中收集的过程数据（例如，密集的纵向，个人，日记或人为时期的数据）。使用关于202名学生的生态瞬时评估的示例数据，这些评估有10到24个报告（M = 14.9，SD = 3.2），受控制的（外部）动机和自主的（内部）动机，以下模型被提出：（1）测量模型和协变量效应楷模; （2）固定，随机和主持人效应模型；（3）按时间顺序排列的数据相互影响的模型。给出了建模的分步说明和实质性解释。总体而言，ISEM为实时教学过程的研究提供了重要的窗口。