Teacher and student relationship 2013 dodge

teacher and student relationship 2013 dodge

Reciprocal Relations Between Student–Teacher Relationship and Children's. Behavioral Problems: .. ior from peers (Laird, Jordan, Dodge, Pettit, &. Bates, ). There is also 2nd year of life (Statistics Norway, a). Many aspects of. affective teacher; student relationships; externalizing behavior problems; mephistolessiveur.info; Deater-Deckard, K., Dodge, K. A., mephistolessiveur.info; Gyllborg, A. B. ( ). Understanding Teacher-Student Relationships, StudentStudent Relationships, The sample included 3, students and teachers in China and 2, students .. American and Chinese schools in the study of students' Bierman, K. L., Coie, J. D., Dodge, K. A., Foster, E. M., Greenberg, M. T.

Other explanations are possible as well.

teacher and student relationship 2013 dodge

Given these unanticipated findings, more research is needed to clarify and interpret results. Strengths and Limitations The findings from this study contribute a better understanding of the independent and interactive relations between teacher-student relationships, literacy skills, and aggressive behavior among low-income kindergarten children.

In addition, students with high academic skills and high teacher-student conflict may be the most likely to display aggression in their classrooms.

Both findings provide evidence of the predictors of student aggression in kindergarten classrooms. The evidence in this study may help indicate which predictive factors to target when attempting to reduce or prevent early aggression in schools.

There are several study limitations to consider. First, two of the measures used in the study were teacher reported, which may lead to bias in the responses. A teacher who has high conflict with a student may be more likely to assess the student as having behavioral problems.

Future studies could also use a triangulated measure of behavior problems and teacher-student relationships to explore these constructs from multiple points of view. Second, a more rigorous analysis plan could be used. This study used robust standard errors to account for some of the nesting. Further research should use multilevel modeling to better account for the nesting and ensure the most robust and rigorous analysis. Similarly, the scores for aggression were significantly positively skewed.

In the analysis, aggression at both time points was corrected for skewness thus making results more difficult to interpret.

Third, the study only measures aggression in one very specific setting — school. Although the measure is used to indicate overall behaviors, the reporting in this study is limited to the school setting.

School-based aggression may not be associated with aggression in other settings, such as home. Similarly, although early aggression is predictive of later aggression and even delinquency, this may not be true for aggression limited to the school setting.

Future research should look at aggression in multiple settings, specifically the school and home. Finally, this study only looks at one specific aspect of behavioral disruption — overt aggression. Future research should examine other types of behavioral disruption, such as inattention or impulsivity. Similarly, testing effects on overall behavioral problems might be critical as the overall score might be most predictive of future negative outcomes for participants and have more important implications.

Implications Aggression at a young age can be highly predictive of future aggressive behaviors thus making this study of particular interest to interventionists and policy makers. Taken together, these studies suggest that aggression at a young age should not be overlooked. A key aspect in addressing this issue may be early intervention for students who exhibit aggression. By addressing aggression at an early age, students may be more likely to change their aggressive behavior thus leading them off the path of aggression at older ages and possible delinquency.

Due to the predictive nature of teacher-student conflict on aggression, interventions targeting teacher-student conflict may be one place to start in the prevention of aggression. Interventions aimed at students and teachers with high teacher-student conflict may help reduce aggression for at-risk students.

In addition to targeting conflict, interventions aimed at academically engaging higher achieving students in more challenging classroom activities may help reduce disruptive behaviors. School-based interventions aimed at the predictive factors in this study may be key in helping young students reduce their levels of aggression during the important early school years.

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The short-term impact of two classroom-based preventive interventions on aggressive and shy behaviors and poor achievement. Journal of Applied Developmental Psychology, 14 3 Reciprocal relations between teacher—child conflict and aggressive behavior in kindergarten: A three-wave longitudinal study.

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American Journal of Orthopsychiatry, 65, 87— Psychological Assessment Resources, Inc. Kindergarten classroom quality, behavioral engagement, and reading achievement. School Psychology Review, 38 1 Silver, R. Trajectories of classroom externalizing behavior: Contributions of child characteristics, family characteristics, and the teacher—child relationship during the school transition. Journal of School Psychology, 43 1 Specifically, positive indicators of affective TSRs comprise closeness, support, liking, warmth, and trust.

In contrast, negative indicators comprise conflict, anger, and dislike. According to stage—environment fit theory, individual development requires an interpersonal relationship that has trust, support, caring, self-expression, self-choice, and self-determination; in cases where. A teacher who did not provide these interpersonal relationships and opportunities created an environmental mismatch with individual development, thus leading to students showing EBPs Wang, ; van Lier et al.

Moreover, many empirical studies have found that positive indicators of TSRs were negatively correlated with students' EBPs Gest et al. However, correlations varied across studies. To resolve this issue, several researchers have summarized research results with reviews Baker et al.

Their limitations include convenience samples, various sample sizes, or ignoring moderators, which led to inconsistencies and low reliability.

Our review of past empirical studies showed that many effect sizes were heterogeneous, suggesting that moderating factors might account for different links between affective TSRs and students' EBPs. Thus, we hypothesized that one or more variables may moderate the effect sizes of the correlation between affective TSRs and students' EBPs, such as differences in students' cultures, ages, genders, and the report types of EBPs.

First, we examine whether students' culture as a latent variable moderates the link between affective TSRs and students' EBPs Chang et al. Baker found a moderate correlation between closeness and students' EBPs among Western students; however, Lywhose sample included Eastern students, found a weak correlation between the two factors. Many studies found a strong correlation between conflict and students' EBPs among Western students Doumen et al.

Thus, in accordance with these findings, this study tests whether the correlation between positive indicators of affective TSRs and students' EBPs for Western students is stronger than that for Eastern students, and whether the correlation between positive indicators of affective TSRs and students' EBPs for Western students is weaker than for Eastern students.

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For example, previous studies indicated that positive indicators for affective TSRs and students' EBPs varied among students in kindergarten lower primary grades LPGand higher primary grades Silver et al. Raters with different ages, standpoints, values, and degrees of understanding a student might rate his or her EBPs inconsistently Van Lier et al. Moreover, several studies have found that different raters might account for the lack of coherence in research on the link between affective TSRs and students' EBPs.

For example, some previous studies have relied on EBPs rated by students, which were only weakly related to positive indicators of affective TSRs Troop-Gordon and Kopp, ; Li et al. In contrast, other researchers found that student EBPs rated by teachers were strongly related to negative indicators of affective TSRs Palermo et al.

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Female students tend to have more affective TSRs than male students do Spilt et al. As a result, gender might influence the correlation between positive or negative indicators of affective TSRs and students' EBPs. Several empirical studies have showed gender differences in the link between indicators of affective TSRs and students' EBPs, such as closeness, support, and warmth Ostrov and Crick, ; Spilt et al. Indexed keywords primarily included terms reflecting affective TSRs relationship scloseness, warmth, support, empathy, trust, sensitivity, conflict, negativity, and anger and students' EBPs behavior problems, externalizing, aggression, conduct problem, hyperactivity, and oppositional.

When articles could not be found online, we obtained full-text versions of articles from libraries. All articles obtained were written in English. We used inclusion and exclusion criteria to analyze and filter the collected studies.

Literature Exclusion Criteria We included articles based on the following criteria: Table 1 summarizes the studies included in the Meta-Analysis. Studies included in the meta-analysis. Coding Study To facilitate meta-analysis, feature coding was conducted on 57 articles.

We considered the following variables: The following criteria guided the coding procedure: When coding was complete, based on principles of meta-analysis Lipsey and Wilson,effect sizes between affective TSRs and students' EBPs were calculated for each sample.

A fixed effects model calculated the homogeneity test and mean effect. Averaged weighted within- and between-inverse variance weights correlation coefficients of independent samples were used to compute mean effect sizes. Moderators were decided by the homogeneity test, which revealed variance in effect sizes between different samples' characteristics.

This study used meta-analysis to test whether each moderator accounted for the variation in the effect sizes. In these reviewed studies, 73, students participated, and the sample sizes ranged from 20 to Furthermore, a fixed effects model was used to homogenize the analysis.

These effect sizes were suitable for moderator analysis.

teacher and student relationship 2013 dodge

Therefore, we used meta-analysis of variance to examine whether culture, age, and report types of EBPs moderated the correlations between affective TSRs and students' EBPs, and we used meta-regression analyses to examine whether gender influenced the relation between affective TSRs and students' EBPs.

Results indicate that the correlation between positive indicators of affective TSRs and EBPs was stronger among LPG students than other students except mixed group and weaker among kindergarten students than other students.

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The correlation between positive indicators of affective TSRs and EBPs were stronger when rated by teachers or parents than by others. These results indicate that the correlation between negative indicators of affective TSRs and EBPs were lower when student rated than when rated by others.

Gender To examine whether gender moderated the links between affective TSRs and students' EBPs, r was meta-regressed onto the percentage of male students in each sample. Meta-regression analyses with effect size regressed onto percentage of male students. Publication Bias To examine whether the results were biased due to effect sizes from various sources, we drew a funnel plot see Figure 1. It showed that the effect sizes were symmetrically distributed on both sides of the average effect size, and an Egger's regression Egger et al.

Egger's regression is an effective method for examining publication bias Teng et al.

teacher and student relationship 2013 dodge

Together, these results indicated stability in the overall correlation between affective TSRs and students' EBPs in this study. Funnel plot of effect sizes of the correlation between affective teacher-student relationships and students' externalizing behavior problems.

teacher and student relationship 2013 dodge

Discussion In the current meta-analysis 57 recent studies, with effect sizes and 73, students are reviewed. We examined the effect sizes of correlations between affective TSRs and students' EBPs, revealing culture, age, report type of EBPs and gender as moderators influencing the links. The correlation coefficients for these results were both medium. As indicated by Masten and GarmezyTSRs are an important support system for students' behavioral development and many studies focusing on improving students' behavior problems with TSRs.

Moreover, students with closer TSRs had fewer antisocial behaviors Birch and Ladd,and high levels of TSR closeness outperformed students' early problem behaviors when predicting their later behavior problems Pianta and Nimetz, Therefore, teachers might explore using diverse communication strategies to help students build positive affective TSRs and reduce negative affective TSRs.

In addition, results suggest that targeted interventions might help students develop affective TSRs when they show EBPs.