Associations between the classroom learning environment and student engagement in learning 2: A structural equation modeling approach

Year: 2012

Author: Harbaugh, Allen G., Cavanagh, Robert F.

Type of paper: Refereed paper



This report is about the second of two phases in an investigation into associations between student engagement in classroom learning and the classroom-learning environment. The same instrument was used in both phases, and the sample of the current study was a subset of the larger sample used in the first phase. The difference between the phases was in the measurement approach applied. This report is about the application of latent variable modeling to explore the data; the previous report (Associations between the Classroom Learning Environment and Student Engagement in Learning 1: A Rasch Model Approach) utilized Rasch Modeling to analyze the data  

Student engagement in learning is an important consideration for research into learning environments and instructional design. The investigations in both phases of this study employed a novel model of engagement in classroom learning based on flow theory and bio-ecological frameworks. The objectives of the phase reported here were (1) to assess the psychometric properties of the instrument measuring the latent constructs of student engagement in classroom learning and the characteristics of the classroom-learning environment, and (2) to use structural equation modeling (SEM) to explore potential relationships between student engagement and classroom environment. The hypothesis of the SEM approach was that specific classroom-learning environment elements would be predictive of student engagement in learning.


Using the 85-item rating scale instrument created for the first phase of this study, 26 of 27 items were retained as a measure student engagement, and 35 of 58 items were retained to measure 7 characteristics of the classroom-learning environment. The self-report instrument was administered to 1760 secondary school students in metropolitan country regions of Western Australia. The computer program R was used for data analysis. After confirming the psychometric properties of the measurement model, factor scores were extracted and used in the SEM analysis.


Classroom-learning environment characteristics had direct effects on students' self-esteem and had direct and indirect effects on students' expectations of the classroom environment.  Classroom characteristics directly influencing students' self-esteem included the educational values, learning outcomes, classroom learning and parental support.  Classroom characteristics directly influencing students' expectations included the educational values, learning outcomes, classroom learning, support from fellow students and expectations of the teacher.


The investigation is an important contribution to knowledge and theorizing about student engagement and classroom learning environments. The two reports enable comparison of contemporary analytic approaches – Rasch and Structural Equation Modeling.