Few studies explain the relationships between teaching quality and student engagement in a large dataset. This study conducted a secondary analysis on the Measurement of Effective Teaching (MET) project by comparing the original CLASS data from MET and a subset of its data. Hierarchical regression models were performed to explore indicators (e.g., dimensions and domains) that could predict student engagement. Two conceptual frameworks were tested in structural equation modeling analysis to investigate the relationships among domains with student engagement. Results showed that while both frameworks could account for student engagement, good classroom organization is the prerequisite for realizing other domains. This study is significant in using different theoretical and statistical analyses to conduct a secondary analysis of a large dataset. Copyright © 2023 AERA.
|Publication status||Published - Apr 2023|
|Event||2023 Annual Meeting of American Educational Research Association: "Interrogating Consequential Education Research in Pursuit of Truth" - Chicago, United States|
Duration: 13 Apr 2023 → 16 Apr 2023
|Conference||2023 Annual Meeting of American Educational Research Association: "Interrogating Consequential Education Research in Pursuit of Truth"|
|Abbreviated title||AERA 2023|
|Period||13/04/23 → 16/04/23|