SELF-REGULATION, EMOTION EXPRESSION & CLASSROOM ...

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visual representation of the overall model used in this study (see figure 1). To determine whether the various facets of self-regulation, on-task involvement, and moderating effects of gender and school have a predictive influence on classroom learning behaviors in kindergarten a series of PLS models will be developed. PLS allows one to estimate constructs or Latent Variables (LVs) based on the shared variance of the manifest variables; individual variable residuals and unreliability associated with measurement error are minimized. That is, scores for the composite LVs are computed from principal components weights, derived from analyses of the manifest variables. Thus, a smaller set of theoretical variables is created, whose relations can be investigated without sacrificing information from the larger group of manifest variables. PLS is a method for modeling relations between sets of observed variables by means of latent variables, where a measurement (outer) model and a structural (inner) model is specified. Outer models demonstrate psychometric reliability of our latent variables. Whereas the inner models allow for estimation of predictivity utilizing both the inner and outer models, which allow us to test for discriminant validity when LVs are compared to the square root Average Variance Extracted (AVE), which represent the variance extracted by the LV from its indicator items (Esposito Vinzi, et al., 2010). It is favorable to use PLS in the current investigation because it allows for the creation of multiple linear regression path models without imposing the restrictions employed by other analyses, such as structural equation modeling, discriminant 45
analysis, and principal components regression. In fact, PLS is probably the least restrictive of the various multivariate extensions of multiple linear regression, and its flexibility allows it to be used in situations where the use of traditional multivariate methods is severely limited, such as when the data is assumed to be non-normal, where there is a smaller than desirable sample size, or there are fewer observations than predictor variables. SmartPLS software will be used to run the PLS analysis (Ringle, Wende, & Will, 2005). Measurement Models. For Hypothesis 1 (H1), self-regulation is measured by hot and cool executive control. The tasks that function as the observed indicators for hot executive control include: Toy peek task, Snack delay task, Tongue snack task and Toy wrap task. The tasks that function as the observed indicator for cool executive control include: Balance beam task, Pencil tap task, Tower building task. Teacher report of classroom learning behaviors, with the sub-constructs of competence motivation, attitude towards learning and attention/ persistence will be used as our criterion variable. The analysis of H2 is an effort to understand whether the relation from model H1 is partially mediated by ontask involvement. Considering the moderating effects of the model, H3 and H4 suggest that the relations between self-regulation and positive learning behaviors moderated by gender and school type. 46
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SELF-REGULATION IN PRESCHOOL CHILDR
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This work is licensed under a Creat
Page 5 and 6: Acknowledgements I would like to ac
Page 7 and 8: List of Tables Table Page 1 Summary
Page 9 and 10: List of Abbreviations AP ATL AVE CM
Page 11 and 12: child’s on-task involvement, gend
Page 13 and 14: Shields, 2004) and exhibit more pos
Page 15 and 16: support and caregiving may serve as
Page 17 and 18: care - which will be used as a prox
Page 19 and 20: these self-regulatory functions (Ca
Page 21 and 22: Kaufmann et al., 2000). In fact, re
Page 23 and 24: “activated”. The current framew
Page 25 and 26: eginning of preschool or child care
Page 27 and 28: such as family problems, lower pare
Page 29 and 30: Schiefele, Roeser, & Davis-Kean, 20
Page 31 and 32: significantly behind their peers in
Page 33 and 34: environments, which may be further
Page 35 and 36: to suggest that there is noted soci
Page 37 and 38: Chapter 3: Statement of Problem Ove
Page 39 and 40: potential gender and socioeconomic
Page 41 and 42: Chapter 4: Research Questions Resea
Page 43 and 44: children’s demonstration of learn
Page 45 and 46: Kochanska and colleagues (2000) sug
Page 47 and 48: in poverty are more likely than the
Page 49 and 50: Miller et al., 2004). I am confiden
Page 51 and 52: the difference between the slow and
Page 53 and 54: when other kids are absent, seeks c
Page 55: The measure yields three reliable l
Page 59 and 60: Vinzi, et al., 2010). Without satis
Page 61 and 62: ehaviors. However, cool executive c
Page 63 and 64: diminished, where on-task involveme
Page 65 and 66: that although self-regulation is im
Page 67 and 68: from the current model. Although th
Page 69 and 70: In addition to the moderation of ge
Page 71 and 72: child no longer being affiliated wi
Page 73 and 74: produced a model linking self-regul
Page 75 and 76: demonstrate difficulty with self-re
Page 77 and 78: academic success, but to demand tha
Page 79 and 80: Table 2 Outer Model and Final R 2 s
Page 81 and 82: Table 3 Inner Model LV Correlations
Page 83 and 84: Table 5 Significance of Moderating
Page 85 and 86: Figure 2: Final partial least squar
Page 87 and 88: Figure 3b: Moderated Model - Female
Page 89 and 90: Figure 4b: Moderated Model - Head S
Page 91 and 92: Once the child is in position: “R
Page 93 and 94: 4) 2 taps 8) 2 taps 12) 1 tap 16) 1
Page 95 and 96: “Okay, now let’s build a really
Page 97 and 98: If the child asks if s/he is sortin
Page 99 and 100: If child offers you a turn: “Than
Page 101 and 102: If child waits for the timer, “Ni
Page 103 and 104: ** ** TIMER/COUNTDOWN: Set the time
Page 105 and 106: If child waits the full length of t
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2= Certainly Applies adjust7 Is eas
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adjust23 Accepts teacher’s author
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1= Applies Sometimes 2= Certainly A
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Appendix 3: Preschool Learning Beha
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Attitude Towards Learning Attention
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N/A Invents silly ways of doing thi
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References Adelman, H.S., & Taylor,
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Bronson, M.B., Tivnan, T., & Seppan
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Denham, S.A., Blair, K.A., & DeMuld
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Fabes, R.A., Martin, C.L. Hanish, L
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Hu, L., & Bentler, P.M. (1999). Cut
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Lin, H., Lawrence, F.R., & Gorrell,
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Normandeau, S., & Guay, F. (1998).
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Rothbart, M.K., Ahadi, S.A., & Hers
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Swanson, H.L. (1999). Reading compr
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Curriculum Vitae Todd M. Wyatt grad
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