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.
Highlights
Instructional quality is considered to be one of the most important predictors of learning outcomes (Seidel and Shavelson, 2007; Creemers and Kyriakides, 2008; Hattie, 2009)
Linking the challenges associated with the modeling of individually perceived instructional quality with the recent methodological advances of exploratory structural equation models (ESEM) and bifactor modeling, we argue that both approaches and their combination may provide powerful tools to evaluate students’ perceptions with respect to their structure, invariance, and relations to external constructs
Making use of a large-scale data set obtained from Programme for International Student Assessment (PISA) 2012, we introduced four modeling approaches that reflect different assumptions about the structure of students’ perceptions of instructional quality, and showed that measurement invariance across three selected countries could be established
Summary
Instructional quality is considered to be one of the most important predictors of learning outcomes (Seidel and Shavelson, 2007; Creemers and Kyriakides, 2008; Hattie, 2009). The conceptual definition of “instructional quality” and the measures need to be aligned This implies that, for instance, the distinction between the three factors of instructional quality, teacher support, cognitive activation, and classroom management should be reflected in students’ perceptions. On the basis of appropriate measurement models, specific degrees of measurement invariance across groups need to be met in order to examine the differences and similarities in individual students’ perceptions (Millsap, 2011) This need has become a major challenge, in international large-scale assessments such as the Programme for International Student Assessment (PISA), which are aimed at comparing countries and educational systems with respect to how instruction is perceived (e.g., Desa, 2014; Rutkowski and Svetina, 2014). Establishing measurement invariance has become essential for comparing students’ perceptions of instructional quality across countries
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
