Psychometric properties of the Cognitive and Metacognitive Learning Strategies Scales among preservice physical education teachers: A bifactor analysis

Jiling Liu, Ping Xiang, Ron McBride, Han Chen
  • European Physical Education Review, February 2018, SAGE Publications
  • DOI: 10.1177/1356336x18755087

Validation of the Motivated Strategies of Learning Questionnaire (MSLQ) using bifactor analysis

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.

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.


Jiling Liu
Texas A&M University System

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.

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