What is it about?
Through a series statistical model testing comparison, we found a bifactor model best fit our data. Since a single composite score can represent the level of self-regulated learning, we proposed a more parsimonious questionnaire for future research and practice use.
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Why is it important?
This study is important because it utilized bifactor analysis which was never used in previous MSLQ validation studies. The study explained and modeled current standards of conducting a bifactor analysis. Also, it focused on preservice PE teachers that previously were not paid much attention to.
Perspectives
The bifactor approach clarified inconsistencies about the questionnaire's factorial structure among previous validation studies. It shows that although learning strategies can be theoretically distinguished, they are statistically inseparable. Often, people believe high correlations between factors are normal because the correlations can be explained away by theory. Unfortunately, justifications can not be imported to a math equation; only numbers can. Ignoring small problems can generate endless headaches in further model testing. I hope this paper can inspire more vigor and rigor in future research.
Jiling Liu
Texas A&M University System
Read the Original
This page is a summary of: Psychometric properties of the Cognitive and Metacognitive Learning Strategies Scales among preservice physical education teachers: A bifactor analysis, European Physical Education Review, February 2018, SAGE Publications,
DOI: 10.1177/1356336x18755087.
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