Evaluating Individual Students' Perceptions of Instructional Quality: An Investigation of their Factor Structure, Measurement Invariance, and Relations to Educational Outcomes

Abstract

Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed.

Final Remarks

“…There is long-standing controversy over whether teacher or student ratings should be used to assess instructional quality (Desimone et al 2009;Marsh et al 2012;Scherer et al 2016;Schlesinger and Jentsch 2016;Wagner et al 2015). Our results do not resolve the controversy given that they indicate that there are problems with both approaches.…”

Measurement invariance of the ICT engagement construct and its association with students’ performance in China and Germany: Evidence from PISA 2015 data

“…The invariance issue has been studied with the use of certain statistical techniques (eg, structural equation modeling) to test and compare factor loadings, item intercepts and error variances. In the literature, four types of measurement invariance, that is, configural, metric, scalar and strict, have been discussed at length (Scherer, Nilsen, & Jansen, ). The configural invariance model is the starting point for conducting measurement invariance analyses.…”

“…In the literature, four types of measurement invariance, that is, configural, metric, scalar and strict, have been discussed at length (Scherer, Nilsen, & Jansen, 2016). The configural invariance model is the starting point for conducting measurement invariance analyses.…”

Students’ Perceptions of Their Teachers’ Performance in Teaching Engineering Drawing in Nigerian Tertiary Institutions

“…Students' perceptions of teacher performance have continued to be among the most important measures for evaluating teaching effectiveness [48]. Studies examining students' perceptions are new, particularly in the field of technical education.…”

“…Studies examining students' perceptions are new, particularly in the field of technical education. Previous researches has investigated the relationship between students' perceptions of the learning environment and its impact on learning outcomes [56,31,1,28,15,2,21,23] For example, in a recent study by [48] three factors; teacher support, cognitive activation, and classroom management were studied and they identified these factors as the most fundamental in teaching quality. The study evaluates different latent variable modelling approaches (confirmatory factor analysis, exploratory structural equation modelling and bi-factor modelling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance and the relationships to selected educational outcomes (achievement, selfconcept, and motivation).…”