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The present study explores teacher emotions, in particular how they are predicted by students' behaviour and the interpersonal aspect of the teacher-student relationship (TSR). One hundred thirty-two secondary teachers participated in a quantitative study relying on self-report questionnaire data. Based on the model of teacher emotions by Frenzel (2014), teachers rated their experienced joy, anger and anxiety during classroom instruction (dependent variable). Students' motivational behaviour (= engagement), socio-emotional behaviour (= discipline in class) and relational behaviour (= closeness; interpersonal TSR) were assessed as the independent variables. Teachers' self-efficacy beliefs served as a control variable. Hierarchical regression analysis revealed that the interpersonal relationship formed between teachers and students was the strongest predictor for teachers' joy (positive relation) and anxiety (negative relation), whereas lack of discipline in class best predicted teachers' anger experiences. Students' engagement also proved a significant predictor of teacher emotions. The results suggest that interpersonal TSR plays a particularly important role in teachers' emotional experiences in class.

Teacher turnover occurs during and at the end of the school year, although documentation of within-year turnover currently rests on anecdotal evidence. On average, over 4.6% of teachers turn over during the school year, which amounts to 25% of total annual turnover. Teachers transfer within districts at higher rates at the beginning of the school year and leave teaching at higher rates at the beginning of the spring semester. Higher performing teachers are less likely to turn over during the school year and less likely to turn over within the year than at the end of the year. Teach for America corps members are much less likely and teachers from out of state much more likely to turn over during the school year than traditionally prepared teachers.

Transfer of responsibility for learning from the teacher to the learner has been considered the final aim of successful scaffolding. Despite this importance, few studies have been conducted in this area. The present conversation analytic study examined the scaffolding interactions of a sample of Iranian English language teachers to identify how responsibility for learning was transferred in scaffolding interactions. The teachers were divided into two groups of novice and experienced based on the criteria proposed in the extant literature. The results showed that the novice and experienced language teachers enacted transfer differently. The novice teachers used more high-support moves, like models and questions with scarce use of low-support moves, thereby mostly curbing the transfer process. However, the experienced teachers used a wider range of scaffolding strategies especially low-support moves to encourage learners to use their learning potentials. The novice teachers mismanaged repair-initiations while experienced teachers mainly ended repair-initiations in self-repairs. The study suggests that the teachers’ experience level can significantly impact their scaffolding interactions with students. Further, it highlights the significance of providing ongoing professional development and training opportunities for language teachers to improve their ability to provide effective scaffolding. Overall, the study highlights the need for continued research in this domain.

The federal Race to the Top initiative signified a shift in American education policy whereby accountability efforts moved from the school to the teacher level. Using administrative data from Tennessee, we explore whether evaluation reforms differentially influenced mobility patterns for teachers of varying effectiveness. We find that the rollout of a statewide evaluation system, even without punitive consequences, was associated with increased turnover; however, there was comparably greater retention of more effective teachers, with larger differences in turnover between highly and minimally effective teachers confined to urban districts and low-performing schools. These results imply that states and districts can increase exit rates of low-performing instructors in the absence of automatic dismissals, which is a pattern that our analyses suggest may not generalize beyond urban school settings.

Substantial teacher turnover poses a challenge to staffing public schools with effective teachers. The scope of the teacher retention challenge across school districts, however, remains poorly defined. Applying consistent data practices and analytical techniques to administrative data sets from 16 urban districts, we document substantial cross-district variation in teacher retention rates. Observable characteristics do not easily explain this cross-district variation. We also find considerable crossdistrict variation in key results from the retention literature, including the relationship between retention and both experience and estimated effectiveness. Finally, we explore the influence of temporary leaves of absence and cross-district, within-state movement on retention estimates. Accounting for cross-district movement matters little, while accounting for temporary leaves matters a great deal in many districts and tends to exacerbate cross-district differences in retention rates.

Student peer effects are well documented; however, we knowfar less about peer effects among teachers. We hypothesize that a relatively effective teacher can positively affect the performance of his or her peers, whereas a relatively ineffective teacher may negatively affect the performance of other teachers with whom he or she works closely. Utilizing a decade of data on teacher transfers between schools that result in changes of peers when transfer teachers enter grade-level team in the new school, we find evidence of strong positive spillover effects associated with the introduction of peers who are more effective than the incumbent teacher himself or herself. However, the incumbent teachers students are not meaningfully disadvantaged by the entry of relatively ineffective peers. This finding provides initial evidence that mixing teachers with diverse performance levels can increase student achievement in the aggregate. These results are robust to several student sorting and teacher selection issues.

Many large urban school districts are rethinking their personnel management strategies, often giving increased control to schools in the hiring of teachers, reducing, for example, the importance of seniority. If school hiring authorities are able to make good decisions about whom to hire, these reforms have the potential to benefit schools and students. Prior research on teacher transfers uses career history data, identifying the school in which a teacher teaches in each year. When such data are used to see which teachers transfer, it is unclear the extent to which the patterns are driven by teacher preferences or school preferences, because the matching of teachers to schools is a two‐sided choice. This study uses applications‐to‐transfer data to examine separately which teachers apply for transfer and which get hired and, in so doing, differentiates teacher from school preferences. Holding all else equal, we find that teachers with better pre‐service qualifications (certification exam scores, college competitiveness) are more likely to apply for transfer, while teachers whose students demonstrate higher achievement growth are less likely. On the other hand, schools prefer to hire “higher quality” teachers across measures that signal quality. The results suggest that not only do more effective teachers prefer to stay in their schools but that schools are able to identify and hire the best candidates when given the opportunity © 2010 by the Association for Public Policy Analysis and Management.

Computer science is often integrated within early childhood education (ECE) through the use of educational robots. This requires adequate preparation of ECE teachers to program and debug, which can be done with scaffolding. In this paper, we use a QUANT + qual mixed method approach incorporating lag sequential analysis, ICAP framework coding, sentiment analysis, and supplementary qualitative analysis. Students tended to engage more with tasks in the revision and evaluation phases than in the exploration phase, and became less dependent on scaffolding prompts and more competent in debugging, as debugging task complexity increased. This study addresses a key gap in the scaffolding literature in that it examined learners’ interactions with scaffolding for evidence of decreased reliance on scaffolding.