Influence of Positive Parenting Styles on Self-Regulated Learning in Chinese Adolescents Testing the Mediating Effects of Self-Esteem

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Abstract

The positive parenting styles and the self-esteem of the parents are two factors that affect Self-regulated learning (SRL). Moreover, the variable of self-esteem is influenced by the positive parenting styles. However, previous studies have investigated only the cross-sectional relationship between positive parenting styles and SRL and that between positive parenting styles and self-esteem. This study explored the relationship between positive parenting styles and self-regulated learning in Chinese adolescents and verified the mediating role of self-esteem in this relationship. The study used the panel data of 1180 1 adolescents (age, 10–15 years) from the 2014 China Family Panel Studies. The main variables were positive parenting styles, self-esteem, and SRL. The results showed that self-esteem plays a partial, but significant, mediating role in the relationship between parents’ positive parenting styles and adolescents’ SRL ability. This study emphasised that self-esteem is a variable that influences the SRL ability. The more active the parents are, the better the SRL ability of the adolescents is. Positive parenting styles have been proven to promote self-esteem development and can affect the SRL ability of adolescents.

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Mediation in experimental and nonexperimental studies: new procedures and recommendations.

Patrick E Shrout, Niall Bolger (2002)

Mediation is said to occur when a causal effect of some variable X on an outcome Y is explained by some intervening variable M. The authors recommend that with small to moderate samples, bootstrap methods (B. Efron & R. Tibshirani, 1993) be used to assess mediation. Bootstrap tests are powerful because they detect that the sampling distribution of the mediated effect is skewed away from 0. They argue that R. M. Baron and D. A. Kenny's (1986) recommendation of first testing the X --> Y association for statistical significance should not be a requirement when there is a priori belief that the effect size is small or suppression is a possibility. Empirical examples and computer setups for bootstrap analyses are provided.