PDF | Introduction The teacher student relationship is very important for a good learning environment. Article (PDF Available) in International Journal of Nursing Education Scholarship 6(1) · February with 7, Reads. Nasir Hussain, Bilal Nawaz, Shaista Nasir, "Nosherwan Kiani" & Mahdi Hussain. maintaining a positive teacher-student relationship with the teacher's . Published online: 06 Oct On the other hand, problematic teacher–student relationships, which are characterized by conflict and low levels of affiliation.
Low-conflict relationships with teachers favor an increase in positive classroom climate and students' perceived teacher support, and a decrease in students' negative experiences Hamre et al.
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Teachers who share a warm relationship with their students tend to develop a positive sense of community in the classroom, as well as to promote cooperation among students by favoring their sharing of skills and ideas. Students seem to interiorize the interactions they have with their teachers and reproduce them with their classmates. In other words, if teachers behave in a consistent, accessible manner with their students, the latter tend to behave in the same way with their classmates Mikami et al.
Conversely, children who are more isolated tend to relate less with their teachers Wu et al. Similarly, aggressive children and those with low interest for school activities tend to relate very little with their teachers Gest and Rodkin, The quality of friendships between peers is often compromised in children that show aggressiveness or lack of respect for others O'Connor, Therefore, improving children's relationships with their teachers and peers is essential, not just to promote motivation and commitment, and to support the resilience of vulnerable students, but also to avoid or interrupt behaviors that threaten positive psychological growth Bronfenbrenner and Morris, Current study In Italy, schools are organized in a way that continuity of the class group is maintained within school cycles.
Each class is formed by a group of students who normally stay together for the whole length of the school cycle, that is, for three consecutive years in middle school, and 5 years in high schools.
Within-cycle changes in the class composition are rare, as there is much less mobility in Italy as compared, for example, to the United States or the United Kingdom.
Teachers are also generally quite stable in the class: The continuity of the class group is significant in psychological terms, since with the passing of time students develop a sense of belonging, share ideas and visions of schooling, teaching, and learning. Moreover, and differently from other countries, no curricular flexibility is allowed to the students in Italian middle and high schools. By the end of middle school, at the age of 13—14 years, students are required to choose the track they intend to follow the next 5 years of high school.
The aim of this study is to investigate the effects of the quality of teacher-student relationships, as perceived by students, on their academic achievement and problem and prosocial behaviors during this important school transition. Regarding behaviors, we consider problematic ones as possible risk factors for school dropout.
Indeed, as posited by many authors, dropping out of school is the culmination of cumulative risk factors over time, including poor academic achievement, school disengagement, and a variety of childhood behavior problems.
In this study we examine whether students' individual relationship with their teachers during the transition from 8th to 9th grade predicts a change in academic achievement and in other behavioral difficulties related to the risk of school failure. Based on previous considerations about the protective role of student-teacher relationship quality in improving students' academic success and psychosocial adjustment, we hypothesize that positive transition-related changes in STR quality will have a positive impact on students' academic achievement and behavioral outcomes.
Methods Participants and procedure Sample consists of Italian 8th grade students recruited from different middle schools in Northern Italy. After 1 year, participants were contacted in their new schools.
However 59 participants were lost to follow-up given that some of the new schools did not give consent for the research to continue. We employed a self-report questionnaire to collect information regarding demographic characteristics age, genderquality of relationship with teachers using the Student Perception of Affective Relationships with Teacher Scale—SPARTS, Koomen and Jellesma,problematic and prosocial behavior Strenghts and Difficulties Questionnaire, SDQ, Goodman, and academic achievement as the average grade across all the school subjects.
Ethical considerations School principals gave their consent for the participation of both teachers and students in our study. Individual informed consent to take part in the research was also collected from teachers, children and their parents, along with written consent describing the nature and objective of the study according to the ethical code of the Italian Association for Psychology AIP.
The consent stated that data confidentiality would be assured and that participation was voluntary.
For the pupils, both parents were asked to sign the consent form in order to have their child participate in our study. Instruments After collecting data about students' age and gender, both students and teachers were asked to fill in a questionnaire including the following instruments. It consists of 25 items investigating 5 different dimensions: Teachers evaluated the degree to which each item such as: A little true, 2: Academic achievement Teachers were asked to report the average grade obtained by each student across all the school subjects.
Each school subject was graded on a 1—10 scale. It consists of 25 items investigating three dimensions, namely Closeness, Conflict, and Negative expectations. The Closeness scale 8 items assesses the students' positive feelings toward and reliance on their teacher e.
Conflict dimension 10 items measures the pupils' perception of the extent of negative behavior, and attitudes experimented with their teacher e. Negative expectations scale 7 items measures the lack of confidence in teacher's responsiveness and availability, e. Cronbach's alphas for this study were adequate, ranging from 0. Analyses revealed presence of outliers on the SDQ subscales T2 assessing emotional symptoms 3conduct problems 1 and peer-relationship problems 1.
Comparison of mean scores of these variables with corresponding means after removing outliers showed that none of these outliers significantly influenced mean scores on the variables at a nominal alpha level of 0. Consequently, univariate outliers were retained within further analyses Pallant, Then, descriptive statistics mean, standard deviation, range were computed on the study variables, both in the overall sample and by gender group. Independent samples t-tests were performed to investigate significance of gender differences on study measures.
In order to investigate the significance of mean changes over time on the study measures, a set of paired-samples t-tests were performed in the overall sample. A measure of effect size Cohen's d was used to convey the size of difference in study measures between the two time points. In order to investigate univariate relationships between study measures, Pearson's correlation coefficients were computed on measures as assessed at T1. Descriptive statistics mean, standard deviation, range were computed on the study variables.
In order to investigate the significance of mean changes over time on the study measures, a set of paired-samples t-tests were additionally performed. A set of multiple linear regression models was utilized to investigate the link between students' relationship quality with teachers and 1-year follow-up measures of achievement and emotional and behavioral difficulties.
Potential collinearity among IVs was controlled by mean-centering the variables Aiken and West, Predictors were then entered in the regressions in the form of both time-averaged levels and change scores. We choose to use this specific parameterization approach as to determine in the analyses the presence of participants who have either stably low or high scores on the predictor variables included in the models Labouvie et al. Thus, we investigated the associations between mean and difference scores for the conflict, negative expectations and closeness facets of student's relationship quality with teachers over a 1-year time lapse and 1-year follow-up measures of students' achievement and emotional and behavioral difficulties.
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.
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.
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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.
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.
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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. In contrast, a negative a2 represents a downward curve and thus lower and higher levels of congruency are related with a lower outcome.
These tests for the dependency of burnout levels on two predictors can be best understood by exploring the response surface visually. Three dimensional plots showing the whole surface in the respective three-dimensional space and contour plots showing the most important part of the surface are provided.
Colors depict the respective burnout level as indicated by the legend. It is important to note that only areas for which data exists should be interpreted.
Results Descriptives and Inter-correlations of the Burnout and Relationship Scales Means, standard deviations and inter-correlations for all burnout and relationship scales are depicted in Table 1.