Items 1 - 11 International Education by an authorized administrator of Trace: Tennessee ferently on the items that reveal or reflect teacher-student relationship. . Set in the above historical and cultural background, J. Liu () reviews. 22 items Findings suggest that teachers' relationships towards students are a resource for the The world's most-cited Multidisciplinary Psychology journal . with an increased level of teacher's emotional exhaustion (Keller et al., ). Published online: 06 Oct On the other hand, problematic teacher–student relationships, which are characterized by conflict and low levels of affiliation.
Impact of Students-Teacher Relationship on Student's Learning: A Review of Literature
Although both perspectives can be regarded as valid, this result could also imply the possibility that teachers are unaware of their differential behavior. Also, Kuklinski and Weinstein reported that teachers differ in their propensities to treat high and low achievers differently: The second condition, i. However, Weinstein et al. Results of a recent meta-analysis by Stroet et al. However, in the small body of studies that used observations or teacher perceptions as a measure of need supportive teaching, much smaller associations or even no associations were found.
Teacher—student relationship and its relation to academic achievement in different grade levels The nature of the teacher—student relationship and its meaning for students change over the school years. Studies mostly report a decrease in the quality of teacher—student relationships Chang et al. However, research has mostly been focused on students at a single age, ignoring the age-related differences in the magnitude of the relation between teacher perceptions and achievement.
They also found a significant decline in direct teacher expectancy effects on achievement from first to fifth grade, although the effect still remained significant in the fifth grade. The current study In the majority of studies mentioned previously, the teacher—student relationship was assumed to be a predictor and academic variables were seen as an outcome, thus hypothe- sizing that academic outcomes are influenced by relations with teachers.
Tement student relationship quality. Research shows that students with higher academic motivation, achieve- ment, and self-regulation and stronger identity as a student form better relations with their teachers Babad ; Davis ; Wentzel and Asher Thus, it is possible that teachers just prefer students who are easier to work with and more rewarding for their effort. This is the relation that Skinner et al.
In that way, the initial dynamics are amplified Hughes et al. In contrast, individuals with insecure or anxious strategies have internalized that the partner reacts insufficiently to their support request which increases insecurity and anxiety as well as fear of rejection. Thus, anxious attachment in combination with a low quality relationship with the most attached student might lead to more negative emotional experiences and thus might increases the risk of suffering from emotional ill-being Horppu and Ikonen-Varila, ; Spilt et al.
On the contrary, secure individuals with a high quality relationship toward the most attached student might profit most regarding their wellbeing. Similarly to prior considerations about incongruent relational experiences, a negative effect on wellbeing can be assumed based on findings of motive-incongruence Shanock et al.
As far as we know, there is only one study providing evidence that pre-service teachers who experienced harsh Parental Discipline, an indicator in the Attachment History Questionnaire, were more likely to experience decreased relationship closeness toward students Kesner, In order to address the proposed research questions of how the relationship range with students as well as how the most significant student combined with attachment security impacts teachers wellbeing, some methodological considerations of how to investigate the combined effect of two predictors on a third outcome variable needs to be addressed.
Thus, in the following section, response surface analysis RSA is introduced as a powerful and statistical elaborated way to investigate the combined effect of two predictor variables on an outcome Edwards, Testing for Combined Effects of Attachment: Response Surface Analysis RSA Difference scores as predictors reflecting congruence or discrepancy are of limited use because no effects of how each predictor contributes to the outcome can be estimated and thus researchers cannot derive whether one predictor is more important than the other.
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Moreover, the level of the predictors, such as extent of closeness of the most and least attached student, which is assumed to affect the outcome, cannot be considered.
Thus, no so called mean level effect can be estimated. Another problematic issue is that scale equivalence of the two predictors is often not met or not possible to obtain. As a consequence, effect interpretation of difference scores is ambiguous and the possible research questions which can be addressed are restricted. A huge disadvantage of moderated regression analysis is that no effect of how the discrepancy of two predictors affects the outcome can be estimated, e.
Furthermore, only linear relationships between outcome and predictors are tested and not quadratic effects Shanock et al.
All those limitations of difference scores and regression models can be overcome when using RSAs. By applying RSA models, researchers can overcome difficulties with traditional approaches such as using absolute or quadratic difference scores of the two predictors and by applying moderated regression models Edwards, ; Shanock et al. RSA models also allow to test for mean-level effects and fit-effects. Moreover, the results are illustrated in a three-dimensional surface plot and a respective contour plot see Figures 1 — 4 which facilitate and guide interpretation.
All in all, RSA models are a powerful way to explore level-effect and fit-effect hypotheses as aimed in the current paper more details in the method section. A contour and B surface plot Model 1. Impact of attachment and student—teacher relationship closeness on depersonalization: A contour and B surface plot Model 2.
Impact of attachment and student—teacher relationship closeness on emotional exhaustion: Thus, the following aims addressing this gap in the literature motivated the current study: We assume lowest burnout levels when teachers in general develop homogenous close relationships toward their students low range and high levels of closeness and highest burnout levels when teachers experience homogenous low connectedness toward their students low range and low levels of closeness.
Also we explored whether relational incongruence negatively impacts teacher burnout. We assume a high connectedness in combination with secure attachment experiences to be associated with the lowest burnout whereas attachment anxiety combined with low relational closeness with the student is assumed to be associated with the highest burnout levels. Before addressing the main research questions, we aimed to explore intercorrelations of all scales.
Materials and Methods Procedure and Sample The sample is a convenience sample since teachers were contacted personally by student research assistants in the first quarter of Accordingly, prior to participation, teachers were informed about the goals of the study, its duration, procedure and the anonymity of their data by the respective student research assistants during the first appointment in school.
Participation was voluntarily at any time.
After informed consent was provided, teachers were interviewed individually this data is not presented in the current paper. Afterward teachers were asked to fill in the questionnaires within 2 weeks, which were then collected personally by student research assistants. Teachers were asked to fill in a paper—pencil questionnaire survey including sociodemographics, the Maslach Burnout Inventory MBI, Enzmann and Kleiber,attachment security scale Asendorpf et al.
Accordingly, prior to participation, teachers were informed about the goals of the research, duration, procedure and anonymity of their data, participation was voluntarily at any time and informed consent was provided.
Data was collected and analyzed anonymously. On average, teachers were The teachers spend on average Their total work load per week comprised on average On average, students were 7. The scale assesses emotional strain and accomplishment by asking how often certain work-related emotions and cognitions are present.
(PDF) Impact of Students-Teacher Relationship on Student's Learning: A Review of Literature
Data Analysis Strategy All analyses were conducted using the software R 3. First, descriptive results such as mean and standard deviation and intercorrelations of all scales are presented. Each set of models tested for the best model among eight candidate models: Since a meaningful zero point is important, all scales were centered. Robust SEs, p-values and CIs are reported. Checking for multivariate outliers and violations of normality assumption of residuals via qqplot revealed no strong violations Bollen and Jackman, RSA Methodology Since the application of RSA models is still rather rare in the literature, a short overview of the methodology is provided here.
Congruence or agreement means that both predictors are more or less on the same level, e. Thus, the congruence hypothesis, based on the full polynomial model, tests linear a1 and quadratic a2 relationships of how the level of congruence is related to the outcome level effect.
In conclusion, discrepancy hypothesis, based on the full polynomial model, tests whether the general extent of incongruence quadratic effect: For example, it can be investigated as to whether discrepant or incongruent relationship experiences of teachers with students and mothers have an impact on their wellbeing fit-effect. Compared to the full polynomial model, those new models are statistically simpler but allow for the testing of more complex relationships and thus statistical power to detect fit patterns is enhanced.
RSA Model Selection In order to select the best fitting model among the candidate models, several widely applied fit statistics were used.
Model weights, which is the probability that the respective model is the best among candidates and evidence ratios, indicating how many times a model is more likely than the other, are also reported Burnham and Anderson, ; Wagenmakers and Farrell, In order to evaluate the general impact of the model, R2 was evaluated as well as the general model significance test. Interpretation of RSA Parameters In order to test congruence or incongruence effects, so-called surface coefficients a1—a4 derived from the regression coefficients b1—b5 can be computed for the full polynomial model Shanock et al.
Thus, a significant a2 coefficient indicates that the two predictors are not linearly but curve-linearly related to the outcome. In general, a positive a2 suggests an upward curve, which means that higher and lower levels of congruency of the two predictors go along with an increase of the outcome.