Cognitive, school, and community factors that influence knowledge acquisition Restricted; Files Only

Abstract

An important aspect of health and development is learning and building a knowledge base. People acquire new knowledge through direct experiences like reading a book or watching a documentary, or through indirect experiences like self-derivation through integration. Self-derivation is the process of integrating or combining two separate learning episodes to acquire information that was not directly taught. In this study, we investigate factors that might influence performance on this important process so that we can better understand how children learn. Based on prior research, we posit that cognitive factors like verbal comprehension, school quality factors like reading proficiency, and community factors like participation in extracurricular activities might influence self-derivation performance. We met with and collected information on 162 children between the ages of 8 and 12 years. Based on results from an exploratory factor analysis (EFA), we were able to define two latent constructs: school which is made up of the indicator variables math proficiency, reading proficiency, and economic disadvantage; and cognitive which is made up of the indicator variables verbal comprehension, visualization, and visual-auditory learning. Next, we evaluated two structural equation models (SEM) and determined that the model design based on results from the EFA was the better fitting model. Finally, we used the better fitting SEM model to predict self-derivation through integration performance. We found that the only predictor of self-derivation performance was the cognitive latent construct. This implies that the individual cognitive strategies employed by the learner are more predictive of indirect learning, as measured through self-derivation performance, above and beyond environmental factors like school quality.

Table of Contents

Introduction……………..…………………………………………………………………….….1

           Knowledge acquisition as measured through the self-derivation paradigm………………2

           Communities and School affect learning………………………………………………….3

Current study………………………………………………………………………………4

Methods…………...………………………………………………………………………………6

Participants………………………………………………………………………………...6

Stimuli and Materials……………………………………………………………………...7

Procedure………………………………………………………………………………….9

Scoring………………………………………………...…………………………………12

Data reduction and variable transformations…………………………………………….12

Results…...…………………………………………………………...………………………….13

           Descriptive statistics…………………………………………..…………………………13

           Exploratory factor analysis………………………………………………………..……..14

           Structural equation models predicting self-derivation……………………………...……15

Discussion……………………………………………………………………………………….17

           Major findings……………………………………………………………………………17

           Implications……………………………………………………………..………………..18

           Limitations and Directions for Future Research…………………………………………20

Conclusions…………………………………………………………………………...….21

References……………………………………………………………………………………….23

Tables and Figures…………………………………………………………………………...…28

           Table 1: Descriptive statistics……………………………………………………………28

           Table 2: Correlation matrix…………………………………………...………………….29

           Table 3: Factor loadings from exploratory factor analysis …………..………………….30

           Table 4: R-Squared values from each SEM model………………………………………31

           Table 5: Factor loadings for Model 1………………………………………..…………..32

           Table 6: Regression coefficients from SEM Model 1…………………………….……..33

           Figure 1: Path diagram from exploratory factor analysis……………………….……….34

           Figure 2: Scree plot for SEM Model 1………………………………………….………..35

           Figure 3: Path diagram for SEM Model 1…………………………………………...…..36

About this Master's Thesis

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School	Rollins School of Public Health
Department	Epidemiology
Subfield / Discipline	Epidemiology - MPH & MSPH
Degree	M.P.H.
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Epidemiology Psychology, Cognitive
Palavra-chave	Knowledge Learning Cognition
Committee Chair / Thesis Advisor	Timothy Lash, Emory University
Committee Members	Patricia Bauer, Emory University

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