Intraindividual Structural Equation Models for learning experiences

Journal article

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.

Authors: Malmberg, LE

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Taylor and Francis
• Journal: International Journal of Research methods in Education
• Volume: 43
• Issue: 4
• Pages: 413-430
• Publication date: 2020-08-24
• Acceptance date: 2020-06-29
• DOI: 10.1080/1743727X.2020.1793939
• EISSN: 1743-7288
• ISSN: 1743-727X
• Language: English
• Keywords: FFR; ecological momentary assessment; intraindividual; intensive longitudinal data; motivation; multilevel structural equation models