SELF-REGULATION, EMOTION EXPRESSION & CLASSROOM ...
SELF-REGULATION, EMOTION EXPRESSION & CLASSROOM ...
SELF-REGULATION, EMOTION EXPRESSION & CLASSROOM ...
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analysis, and principal components regression. In fact, PLS is probably the least<br />
restrictive of the various multivariate extensions of multiple linear regression, and its<br />
flexibility allows it to be used in situations where the use of traditional multivariate<br />
methods is severely limited, such as when the data is assumed to be non-normal, where<br />
there is a smaller than desirable sample size, or there are fewer observations than<br />
predictor variables. SmartPLS software will be used to run the PLS analysis (Ringle,<br />
Wende, & Will, 2005).<br />
Measurement Models.<br />
For Hypothesis 1 (H1), self-regulation is measured by hot and cool executive<br />
control. The tasks that function as the observed indicators for hot executive control<br />
include: Toy peek task, Snack delay task, Tongue snack task and Toy wrap task. The tasks<br />
that function as the observed indicator for cool executive control include: Balance beam<br />
task, Pencil tap task, Tower building task. Teacher report of classroom learning<br />
behaviors, with the sub-constructs of competence motivation, attitude towards learning<br />
and attention/ persistence will be used as our criterion variable. The analysis of H2 is an<br />
effort to understand whether the relation from model H1 is partially mediated by ontask<br />
involvement. Considering the moderating effects of the model, H3 and H4 suggest<br />
that the relations between self-regulation and positive learning behaviors moderated by<br />
gender and school type.<br />
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