Purpose
This report is about one phase in an investigation into associations between student engagement in classroom learning and the classroom learning environment. Both phases applied the same instrumentation to a similar sample. The difference was in the measurement approach applied. This report is about application of the Rasch Model to analyse the data; the second report (Associations between the Classroom Learning Environment and Student Engagement in Learning 2: A Structural Equation Modeling Approach), is about Structural Equation Modeling application.
Student engagement has become an important consideration for research into learning environments and instructional design. A novel model of engagement in classroom learning based on flow theory and bio-ecological frameworks underpinned the investigation. The objectives of the phase reported here were to construct a composite measure of student engagement in classroom learning and the classroom learning environment; then to use the Rasch Rating Scale Model to examine properties of data when the measure was administered. The hypothesis of the Rasch approach was that engagement in learning variables and classroom learning environment variable could be measured on the same linear scale.
Method
An 85-item rating scale instrument was created by combining 27 items from a previously developed Rasch Model measure of student engagement with 58 items from a previously developed Rasch Model measure 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 (RUMM2030, Rasch Unidimensional Measurement Models), was used for data analysis. The fit of data from individual items were iteratively tested for fit to the measurement model until a set of items were identified with good data-to-model fit.
Results
Data on engagement in classroom learning and the classroom learning environment were able to be plotted on one 60-item linear scale. Calibrations of student affirmativeness of their engagement and the learning environment and of the difficulty the items presented to students were estimated on the scale. This suggests presence of an underlying common construct - a latent trait.
Statistically significant differences in overall student scores between country and city students, boys and girls, year cohorts, curriculum areas, and favourite and non-favourite subjects
Conclusion
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.