How Fit Is Associated with Teacher Mobility and Attrition

How Fit is Associated with Teacher Mobility and Attrition

Dan Player, Peter Youngs, Frank Perrone, and Erin Grogan

The knowledge and skills that teachers bring to their schools – that is, their human capital – are key organizational assets (Coleman, 1988; Wellman & Frank, 2001) and the ability of a school to retain a sufficient number of high-performing teachers has a significant impact on its functioning over time

(Allensworth, Ponisciak, & Mazzeo, 2009; Ingersoll & May, 2012). In addition, research indicates that teachers have a stronger influence on student achievement than any other school-based factor (Chetty,

Friedman, & Rockoff, 2011; Nye, Konstantopoulos, & Hedges, 2004; Rivkin, Hanushek, & Kain, 2005).

Therefore, efforts to strengthen public education must address the human capital teachers bring to their classrooms as well as the organizational processes within schools that shape their work experiences. One way for schools and school districts to do this is to take steps to increase the likelihood that strong teachers are retained in their schools over time.

Research on teacher retention has typically focused on how student demographics, teacher characteristics, and/or teachers’ working conditions (i.e., school contextual factors) have affected teachers’ decisions to remain in their schools, move to other schools, or leave teaching (Allensworth,

Ponisciak, & Mazzeo, 2009; Boyd, Grossman, Ing, Lankford, Loeb, & Wyckoff, 2011; Ingersoll & May,

2012; Ladd, 2011; for reviews of this literature, see Borman & Dowling, 2008; Guarino, Santibanez, &

Daley, 2006). But perhaps surprisingly, there has been relatively little focus in research on K-12 education on the role of person-environment fit in explaining teacher turnover. Theories of fit emerged from a robust research base in industrial organizational (I-O) psychology that has explored how employees interact with their work environments in an attempt to understand factors that lead to retention and other desirable outcomes (Chatman, 1989; Kristof-Brown, Zimmerman, & Johnson, 2005). Meta- analytic reviews of I-O research have found moderate associations between employee retention and different types of person-environment fit (Hoffman & Woehr, 2006; Kristof-Brown et al., 2005; Verquer,

Beehr, & Wagner, 2003).

Please do not cite without permission of the authors. 2

While there are several ways to conceptualize fit with regard to work environments, this paper uses a nationally representative dataset, the 2011-12 Schools and Staffing Survey, to investigate how two types of fit relate to teacher retention: (a) fit with the prevailing goals and values of the employing organization (i.e., person-organization fit) and (b) fit with the demands of the job (i.e., person-job fit). In our analyses, we found that person-organization (P-O) fit strongly predicted retention in one’s school while person-job (P-J) fit strongly predicted retention in the teaching profession, but did not predict retention in one’s school. We also found that strong principal leadership strengthened the effect of P-J fit on retention. These findings have important implications for district policies and principal leadership practices in the areas of teacher hiring and new teacher induction.

In the first section of this paper, we review previous research on teacher retention and person- organization fit in K-12 education. The second section presents a series of hypotheses regarding fit and retention that we tested in our analyses. In the third section, we introduce our sample, research methods, and analytical strategies. The fourth section describes our main findings regarding the role of fit in teacher retention. Finally, we conclude by considering implications of our findings for efforts to retain effective teachers in their schools and in the profession.

Background and Motivation

Prior research has examined how teacher retention is affected by student demographics, teacher characteristics, and teachers’ working conditions. Studies have found that teachers are more likely to leave schools that serve high percentages of low-income, non-White, and/or low-achieving students

(Lankford, Loeb, & Wyckoff, 2002; Scafidi, Sjoquist, & Stinebrickner, 2007). In addition, teachers’ age, years of experience, and effectiveness have been found to predict turnover. For example, early career teachers and those close to retirement are more likely to leave their positions than mid-career teachers

(Allensworth, Ponisciak, & Mazzeo, 2009; Guarino, Santibanez, & Daley, 2006; Ingersoll, 2001). At the same time, teachers who are more effective (as measured by students’ performance on state tests) are less likely to leave their positions than less effective teachers (Author, 2011; Boyd et al., 2011).

Research on teachers’ working conditions has consistently found that effective principal

Please do not cite without permission of the authors. 3 leadership can increase teacher retention even in contexts where student and teacher characteristics predict that turnover is likely. These studies indicate that principals can promote retention by enacting effective student behavior policies, providing instructional support, facilitating their collaboration with other colleagues, evaluating teachers in meaningful and fair ways, and fostering trust between themselves and their staffs (Allensworth, Ponisciak, & Mazzeo, 2009; Boyd et al., 2011; Ingersoll & May, 2012;

Ladd, 2011). With regard to early career teachers, there is some evidence that formal mentoring and opportunities to collaborate with colleagues are associated with retention (Kapadia, Coca, & Easton,

2007; Smith & Ingersoll, 2004). At the same time, a multiyear randomized control trial study by

Glazerman and colleagues (2010) reported no significant effects of comprehensive induction on retention in teachers’ first two years. In the study by Glazerman et al. (2010), comprehensive induction programs were characterized by full-time mentors who received extensive training, weekly meetings between mentors and mentees, professional development opportunities, and formative assessments of novice teachers.

These studies indicate ways in which organizational features of schools (such as principal leadership, mentoring, and opportunities for collaboration) are related to teacher retention. At the same time, the fit framework is unique in that it concentrates specifically on the match of the employee to organizational goals and values (P-O fit) as well as job requirements (P-J fit). In teaching, P-O fit would refer to whether a focal teacher’s beliefs about the school’s main goals and mission are similar to those of their colleagues; whether the focal teacher is satisfied with their work environment; and whether they plan to transfer to another school. In teaching, P-J fit would refer to whether the focal teacher has the skills and abilities required to complete the tasks of the job, whether they are enthusiastic about their work, whether they feel their effort is worthwhile, and whether they would leave teaching for a higher-paying job.

In many ways, student demographic factors might also be categorized as an element of teachers’ assessment of fit (Cannata, 2010; Lankford, Loeb, & Wyckoff, 2002); i.e., part of their overall judgment regarding whether the requirements of the job are in line with their personal expectations and needs. If

Please do not cite without permission of the authors. 4 teachers feel that their own background (i.e., personal characteristics, pre-service preparation, professional experience) does not adequately prepare them to meet the needs of the students they are assigned to teach, they may perceive a lack of fit with their school. For example, a white, female teacher from a middle-class background may not initially perceive a strong sense of fit with students who are diverse with regard to race/ethnicity, language ability, socio-economic status (SES), and/or special education needs.

A growing number of studies have examined how fit is associated with teachers’ commitment to their schools or to the teaching profession. For example, in a study conducted in Singapore, Chan and colleagues (2008) reported strong correlations between teachers’ fit with their school and their commitment to the profession. In research conducted in the U.S., Author (2013) found moderate correlations between early career teachers’ fit with their school and their commitment to their school; in the study by Author (2013), the early career teachers were in their first three years of teaching.

But aside from this limited number of studies, few others within K-12 education have examined associations between fit and teacher retention. This contrasts with the field of I-O psychology, which has studied employee fit extensively. Several meta-analyses of I-O research have reported moderate correlations between fit and the degree to which workers in a variety of professions are likely to remain in their positions (Hoffman & Woehr, 2006; Kristof-Brown, Zimmerman, & Johnson, 2005; Verquer, Beehr,

& Wagner, 2003). These findings indicate that when employees’ values, goals, or knowledge and skills do not match those reflected or needed in the work environment, the likelihood of turnover increases.

Methods

Data and Sample

Data for this study came from the 2011-12 Schools and Staffing Survey (SASS) and the 2012-13

Teacher Follow-Up Survey (TFS). The SASS is a very comprehensive data source for research on the organization and staffing of elementary and secondary schools. It consists of a series of linked surveys administered to district administrators, school principals, and teachers. In this study, we used data from

Please do not cite without permission of the authors. 5 the public school Teacher, Principal, School, and District Questionnaires; we did not include data from questionnaires administered to private schools because the factors that affect teacher retention in private schools are likely to differ from those that affect retention in public schools.

Data for the 2011-12 SASS and the 2012-13 TFS were collected using a stratified probability sample design with schools sampled first, followed by school districts. Schools were selected with a probability proportionate to the square root of the number of teachers and they were selected to be representative at the national and state levels. The weighted school response rate was 72.5 percent. To obtain the teacher sample, principals were contacted and asked to submit a list of all teachers currently working in their building, with a weighted response rate of 79.6 percent. From these lists, teachers were assigned to strata based on race/ethnicity, assignment in a classroom where students had Limited English

Proficiency, and “beginning teacher” status (i.e., they had been teaching for 3 years or less). For each sampled school, one to 20 teachers were sampled and the weighted teacher response was 77.7 percent.

The 2011-12 SASS is linked to the 2012-13 TFS, which was administered 12 months after the

2011-12 Teacher Questionnaire to a sample of teachers who had completed the first questionnaire; the weighted response was 81.3 percent. The TFS was designed to support comparative analysis of teachers who continued teaching in their original schools (“stayers”), teachers who remained in teaching, but switched schools (“movers”), and teachers who left the teaching profession (“leavers”). The TFS was stratified by school levels (elementary vs. secondary), experience (beginning teacher vs. experienced), and school sector (public vs. private).

To create the final sample used in this analysis, data from the TFS were merged with data from the SASS Public School Teacher Questionnaire; this enabled us to determine teachers’ employment status in 2013. Thus, the final dataset was limited to those teachers whose 2013 employment status was known.

We also restricted the dataset to include only full-time teachers in regular public and charter schools.

Finally, we merged data from the Principal and School Questionnaires with this dataset. The resulting dataset used for our analysis included the full-time regular public and charter teachers that could be matched to principal and school survey responses.

Measures

Mobility Measure. In this analysis, we distinguish between complete attrition from the teaching profession and switching schools. Thus, our dependent variable is a three-category variable representing the teacher’s employment status as reported in the TFS: switching schools (“movers”), leaving teaching

(“leavers”), or remaining in the same school (“stayers”). Other studies of teacher retention have used similar outcome measures (Allensworth, Ponisciak, & Mazzeo, 2009; Boyd et al., 2011; Ingersoll, 2001).

Fit Measures. The creation of the P-O fit measure and the P-J fit measure relied on exploratory factor analysis with maximum likelihood (ML) extraction methods and oblique (promax) rotation. Due to the likert-scale structure of the responses, we employed polychoric factor analysis. We estimated the factors by including 11 survey items that we hypothesized would measure fit with both the organization and the profession. We then retained those items that loaded 0.40 or higher on either factor. The emergent

P-O fit factor included 6 of 11 survey items, which loaded at 0.40 or higher, accounting for 87 percent of the variance in the underlying correlations, with an eigenvalue of 5.16. In addition to the P-O fit factor, a

P-J fit factor was identified, in which 5 of 11 items loaded at 0.40 or higher (explaining 18 percent of the variance), with an eigenvalue of 1.06.

After identifying the P-O and P-J fit factors, factor scores were predicted using a least squares regression approach on the full SASS sample. Each factor was then standardized to have a mean of 1 and a standard deviation of 0 across the sample. The weighted TFS analysis sample, a subset of the full SASS sample, had a mean P-O fit of -0.11 and a standard deviation of 1.11 and a mean P-J fit of -0.16 and a standard deviation of 1.10. These two factor scores were used as the primary predictor variables in the analysis below.

Hypotheses

This analysis examined how teacher mobility was affected by P-O fit, P-J fit, and principal leadership. We hypothesized that P-O fit would be related to retention in the following ways:

Hypothesis 1: The higher the level of one’s P-O fit, the lower the likelihood that they will switch

schools or leave teaching. Having a strong match with one’s school is expected to keep a teacher

in the profession at the school where they experienced a high level of fit.

We hypothesized two ways in which P-J fit would be related to retention:

Hypothesis 2A: The lower the level of one’s P-J fit, the more a teacher is misaligned with the

profession and the more likely they are to leave the teaching profession entirely.

Hypothesis 2B: Low P-J fit (misalignment with teaching) will not be significantly related to switching

schools; a teacher who is not well-suited for the demands of teaching will be more likely to leave

the profession completely than to seek out a new school.

We hypothesized that effective principal leadership would relate to retention in two ways:

Hypothesis 3A: When a teacher’s principal is effective at running their school and supporting staff

members, the impact of P-O fit on retention in the school and the profession will be increased.

Hypothesis 3B: When a teacher’s principal is effective at running their school and supporting staff

members, the impact of P-J fit on retention in the profession will be increased.

We hypothesized that school characteristics may influence P-O fit and may explain some of the relationship between P-O fit and retention:

Hypothesis 4A: The relationship between P-O fit and retention will be greater for elementary than

secondary teachers.

Hypothesis 4B: The relationship between P-O fit and retention will be greater in charter schools than

in traditional public schools.

Hypothesis 4C: The relationship between P-O fit and retention will be greater in urban and suburban

schools schools than in rural schools.

Hypothesis 4D: The relationship between P-O fit and retention will be greater in high poverty

schools than in low poverty schools.

Hypothesis 4E: The relationship between P-O fit and retention will be greater for novice teachers

(i.e., teachers in their first 3 years in the profession) than for more experienced teachers.

We use a multinomial logit model to simultaneously model the three possible outcomes of teachers in the TFS: stay in the same school, move to a new school, or leave teaching. The multinomial logit model is specified as

é 2 ù P(y = j | x,t, s) = exp(x¢b j + t¢g j + s¢d j ) /ê1+ åexp(x¢bh + t¢g h + s¢dh )ú j =1, 2 ë h=1 û where x is a vector of fit measures, t is a vector of teacher characteristics, s is a vector of school characteristics, and j equals zero (stay in the same school), one (move schools), or two (leave teaching).

The fit variables are described in greater detail above. As controls, we included various measures to account for teacher characteristics and school characteristics that may also influence teacher mobility.

Teacher controls include indicators for whether the teacher was in the first three years of teaching; the number of years taught at the current school; gender; race/ethnicity; marital status; union membership; age; master’s degree; possessing traditional (i.e., not alternative) certification; being the same race as the majority of students, colleagues, and the principal, respectively; total earnings from teaching; whether the teacher taught special education, mathematics, or science; and the number of Individualized Education

Plan (IEP) and Limited English Proficient (LEP) students taught. School characteristics included size, schoolwide Title I status, school urbanicity, and the percentage of racial/ethnic minority teachers and students. The simultaneous inclusion of these controls results in the estimation of partial effects of P-J fit and P-O fit holding these observable characteristics constant.

The coefficients from multinomial logit models are difficult to interpret in their raw form. For ease of interpretation, we report the exponentiated values of the coefficients, which represent relative risk ratios (RRR) relative to the base outcome of staying in the current school. Relative risk ratios are interpreted as the ratio of odds of the two outcomes that are being compared. For example, a RRR of 1.0 indicates that the variable influences the odds of mobility (moving schools or leaving teaching) at the same rate as it influences the base outcome (staying in the same school). Values of the RRR less than1.0

Please do not cite without permission of the authors. 9 indicate that the variable reduces the odds of mobility more than it reduces the odds of staying in the school. Likewise, RRRs greater than 1.0 indicate the variable increases the odds of mobility more than it increases the odds of staying in the same school. Throughout what follows we focus on the RRRs using the value of 1.0 as the benchmark, and statistical significance is always reported to indicate whether the

RRR is statistically different from 1.0. All models employ sampling weights to make the results nationally representative and to account for the complex sampling design of the SASS and TFS.

Results

The TFS survey included approximately 3,800 respondents of which approximately 3,000 could be matched to their principal and school surveys from the prior year.1 Because we expect the TFS sample to be representative of the nation as a whole, the weighted means should be roughly equivalent to what would be observed in the teaching population at large. However, because of non-response at various survey levels, some differences may have emerged. In our sample, approximately 9 percent of the sample were novice teachers in 2011-12 (in their first three years of teaching), roughly 4 percent of the sample taught in charter schools, and almost 67 percent taught in elementary schools (defined as schools serving grades K-5) (Table 1). Teachers had an average of 4.2 years of teaching experience in their schools.

Does P-O Fit Predict Mobility?

As hypothesized, teachers who reported strong P-O fit were much less likely to leave their schools (Table 2, Column B). To illustrate, teachers who reported a level of P-O fit that is one standard deviation greater than average had 36 percent lower odds of switching schools in the following school year (RRR=0.643, p<.01). However, teachers with higher P-O fit were no more or less likely to leave the profession altogether; the coefficient was less than 1.0, but was not close to being statistically significant.

Taken together, these findings confirm the hypothesis that teachers who reported greater P-O fit were less likely to switch from one school to another than teachers who reported lower P-O fit, but P-O fit did not necessarily predict transitions out of the profession holding other factors (including P-J fit) constant.

Does P-J Fit Predict Mobility?

A teacher’s measure of P-J fit is also predictive of mobility. Teachers who reported P-J fit of one standard deviation above average have 35 percent lower odds of leaving the profession (Table 2, Column

3; RRR=0.654, p-value<.01). Consistent with our hypothesis, P-J fit was not statistically related to the probability that a teacher changes schools. The relative risk ratio was less than 1.0, but was not statistically significant at conventional levels.

While not the focus of our analyses, the regressions presented above provide some important descriptive evidence about other predictors of teacher mobility holding constant the measures of P-O fit and P-J fit. For instance, teachers in their first three years of teaching (i.e., novice teachers) had higher odds of leaving the profession and higher odds of moving schools. Although both coefficients were rather large, neither was statistically significant at the conventional .05 level. The lack of statistical significance suggests that some of the attrition that is seen in novice teachers is captured with the measures of fit and other controls that are included in the regression. This is explored in greater detail below.

As expected due to retirements, teachers over 50 years of age had odds of leaving teaching that were more than four times higher than teachers under 50 (RRR=4.143, p<.01). Indeed, accounting for retirement was the primary motivation for including the indicator for being over 50 in the regression.

Because the coefficient for “over 50” was so large, we also examined whether retirees were affecting our main results for P-O fit and P-J fit by estimating the main regressions for a sample that excluded teachers who were over 50. The results (not shown) were consistent with the main results, providing evidence that the results were not driven by retirees.

Other findings from the main results indicate that teachers with master’s degrees were more likely to move to a new school (RRR=1.81, p-value<.01), but they were no more likely nor less likely to exit the profession than teachers without a master’s degree. Teachers with regular certification were less likely to change schools than teachers who were alternatively certified (RRR=.572, p-value<.05).

Teachers with higher salaries were less likely to move to a new school (8.3 percent reduction in odds per

10% increase, p-value<.01) and not statistically different in terms of their likelihood of exiting the profession. Teachers from large schools (3.4 percent odds reduction per 100 students, p-value<.05) and

Please do not cite without permission of the authors. 11 teachers from rural schools (RRR=.664, p-value<.05) were significantly less likely to move schools, but neither school size nor urbanicity was related to teachers’ decisions to exit the profession.

Does Principal Leadership Influence Mobility?

Some of the measured P-O fit could directly reflect the principal’s leadership in the school. To examine whether specific measures of principal leadership influence teacher mobility, we re-ran the factor analysis omitting three questions that related to the teachers’ assessment of leadership (“I like the way things are run at this school,” “In this school, staff members are recognized for a job well done,” and

“The school administration’s behavior toward the staff is supportive and encouraging”). We conducted a separate polychoric factor analysis with these three items to create a third factor and then included all three factors (Revised P-O fit, Revised P-J fit, Principal Leadership) in the model to examine whether teachers’ perception of their principal’s leadership influenced mobility independent of the other factors that comprised P-O fit.

When principal leadership is separated from the other measures of P-O fit, the new measure of P-

O fit is consistent with prior estimates of the relationship between P-O fit and school movement that included leadership but now significantly predicts teachers’ decisions to exit the profession (Table 2,

Columns D and E). Specifically, the relative risk ratios from the regression indicate that teachers who reported higher measures of P-O fit were less likely to switch schools or exit the profession. The magnitude of effects on leaving the profession were somewhat larger, which may indicate that P-O fit net of principal leadership was a stronger predictor of leaving holding principal leadership constant.

However, the leadership factors themselves were not particularly large nor close to being statistically significant predictors of changing or leaving schools. Thus, it appears that principal leadership alone did not strongly influence leaving or moving holding constant other measures of school fit.

As a second analysis, we interacted principal leadership with measures of P-O fit to determine whether measures of leadership moderate the influence of P-O fit on teacher mobility. The interaction terms are quite modest and are not statistically significant from 1.0 at the conventional .05 level. This

Please do not cite without permission of the authors. 12 suggests that, if anything, principal leadership only plays a very modest role in moderating the effect of P-

O fit on teacher mobility.

Do Teacher and School Characteristics Influence the Role of Fit?

We predicted that a number of teacher and school characteristics could influence the relationship between P-O fit and mobility. In what follows, we first describe whether the average measures of P-O fit vary by teacher and school characteristics by examining the predictive power of such characteristics on measures of P-O fit. In this way, we can determine whether particular teacher or school types tend to report greater measures of P-O fit than others. We then test whether those characteristics influence the relationship between P-O fit and mobility by interacting each characteristic with the P-O fit measure from the primary specification.

Several factors influenced measures of P-O fit (Table 3). Most notably, elementary teachers reported, on average, measures of P-O fit that were 0.2 higher than non-elementary teachers while novice teachers did not report P-O fit that was statistically different from that of more experienced teachers.

Teachers who were members of a teacher union reported P-O fit that was 0.25 less than that of non-union teachers, and teachers with a master’s degree reported P-O fit that was 0.13 smaller than that of teachers without a master’s degree. Special education teachers reported 0.24 greater P-O fit than that of other teachers while none of the other subject areas were statistically different from zero. Teachers in schoolwide Title I programs reported worse P-O fit, on average, than teachers in other schools while teachers from rural areas reported worse fit than teachers from suburban or urban areas.

Given the differences in P-O fit, we examined whether some of these teacher and school characteristics moderated the influence of P-O fit on teacher mobility. Elementary and secondary schools differ in structure and therefore may differ in the relationships between teachers and subsequently how closely fit is related to teacher mobility decisions. To test this, we interacted measures of P-O fit with the school level taught. Contrary to our hypotheses, the coefficients for both outcomes were positive, which suggests that if anything elementary teachers have a less sensitive connection between P-O fit and

Please do not cite without permission of the authors. 13 mobility than secondary teachers. However, both coefficients were modest and neither was statistically significant at the .05 level.

Compared to traditional public schools, charter schools also vary in their structure in ways that may influence how fit is related to mobility. Regressions that interacted charter school indicators with measures of P-O fit, though, found no statistically significant relationship between P-O fit in charter schools versus P-O fit in traditional public schools. This suggests that P-O fit is no more or less important for charter school teachers than it is for traditional public school teachers as it relates to mobility decisions.

School urbanicity influenced teacher mobility patterns in our primary specifications. Urbanicity could also influence the relationship between fit and mobility since in less-densely populated rural areas, for example, it might be much more difficult to transfer to other schools than it is in suburban or urban settings where schools are more concentrated. When we interacted rural school location with P-O fit measures, we found that urbanicity did not have significant explanatory power in predicting teacher mobility related to P-O fit. This suggests that the relationship between P-O fit and mobility is not different for rural teachers compared to urban or suburban teachers. This is a somewhat surprising result given assumed differences in the availability of opportunities to move.

The demographics of students could influence turnover and feelings of fit. As reported above, teachers from Title I schools reported lower P-O fit than teachers in non-Title I schools. When interacted with P-O fit, however, being in a Title I school did not have a significant influence on the relationship between P-O fit and mobility.

As a final exploration, we examined whether the relationship between P-O fit and mobility was different for novice teachers than it was for non-novice teachers. To test whether novice teacher status moderated the effects of P-O fit on mobility, we interacted such status with P-O fit. Contrary to our hypothesis, the interaction between P-O fit and novice teacher status was not statistically significant, which suggests that the relationship between P-O fit and mobility is no different for novice teachers than it is for more experienced teachers.

Discussion

Due to its potential impact on students and school climate, a substantial body of prior research has examined the determinants of teacher mobility (Borman & Dowling, 2008; Guarino, Santibanez, &

Daley, 2006). While existing studies of teacher retention have primarily attempted to isolate economic and, to a lesser degree, organizational factors that predict teacher turnover, this analysis extended the teacher retention research base by employing a person-environment fit theoretical framework, frequently used in studies of turnover in other professions, but infrequently seen in studies focusing on teachers.

Specifically, we explored how person-organization (P-O) fit and person-job (P-J) fit were associated with teacher retention. The analysis incorporated multiple measures of fit simultaneously, a strategy that has been recommended by some industrial organizational (I-O) psychology researchers, but that is relatively uncommon in fit research (Kristof-Brown, Jansen, & Colbert, 2002; Tak, 2011).

Through multiple models and specifications, the results confirm that P-O fit and P-J fit predict retention in one’s school and retention in the teaching profession, respectively. Since P-O fit is a measure of the teacher’s fit with the school in which they are teaching, and less a measure of their general satisfaction with teaching, it makes intuitive sense that strong P-O fit is negatively correlated with a teacher’s decision to move from school to another. Likewise, P-J fit is a measure of how well the teacher fits with the larger teaching profession. These findings are consistent with research in I-O psychology on the relationship between P-O fit and employee retention ((Hoffman & Woehr, 2006; Kristof-Brown,

Zimmerman, & Johnson, 2005; Verquer, Beehr, & Wagner, 2003) and these results also build on research that has documented associations between P-O fit and teacher commitment (i.e., planned retention)

(Author, 2013; Chan et al., 2008).

At the same time, in our analyses P-O fit did nor predict retention in the profession. In addition, we found no statistically significant differences with regard to the relationship between P-O fit and retention in one’s school when comparing novice and experienced teachers, elementary and secondary teachers, teachers in charter schools and those in traditional public schools, teachers in rural schools versus those in suburban or urban schools, or teachers in Title I schools and those in non-Title I schools.

These findings suggest that the strength of the association between P-O fit and retention is remarkably consistent across a wide variety of teaching contexts.

P-J fit is a measure of how well the teacher fits with the larger teaching profession. As expected, we found a strong association between high P-J fit and a reduced likelihood that teachers would leave the profession. This finding is consistent with findings from I-O psychology research (Kristof-Brown,

Zimmerman, & Johnson, 2005). On the other hand, P-J fit was not associated with retention in one’s school. This makes intuitive sense in that an individual who very much enjoys working as a teacher is likely to remain committed to the teaching profession over time while being no more nor less likely to switch schools than an individual who is ambivalent about the teaching profession.

One of the surprising findings that emerges from these analyses is that principal leadership did not predict teacher mobility after accounting for other measures of fit with the school. This suggests that teacher mobility is more sensitive to general P-O fit than it is just to a teacher’s perception of the principal’s leadership. This finding provides additional context for interpreting recent research that has examined the relationship between leadership and teachers’ exit decisions (Allensworth, Ponisciak, &

Mazzeo, 2009; Boyd et al., 2011; Ingersoll & May, 2012; Ladd, 2011). In particular, while these studies have documented strong relationships between principal leadership and teacher retention, our findings suggest that P-O fit may help explain the positive effect of leadership on retention.

Limitations. While these results offer useful evidence of relationships between P-O fit, P-J fit, and teacher retention, there are some limitations to our analysis that warrant discussion. First, this study did not include any measures of student achievement or teacher effectiveness. Recent studies have focused on differential retention and have found that teachers who are deemed to be “more effective” than their peers are more likely to be retained, while those who are “least effective” are more likely to leave (Author,

2011; Boyd et al., 2011). An important step for future research will be to build on these studies by integrating teacher effectiveness measures into analysis of fit and retention and examining how fit interacts with teacher effectiveness to shape retention, migration, and attrition.

Second, the SASS and TFS data make it impossible to distinguish between permanent leavers and those who “stop out” to pursue other opportunities (e.g., graduate school, caring for a relative, having a baby) for a period of time before returning to teach in the classroom. In this analysis, these individuals can only be considered “leavers.” Ingersoll and May (2012) note that temporary attrition leads to school- level staffing challenges that are similar to complete exit, but do not quantify the percentage of teachers who leave a school who eventually re-enter the classroom. Estimates of the percentage of teachers who

“stop out” are scarce, but Provasnik and Dorfman (2005) estimated that about 4 percent of the teachers who entered a new school in the 1999-2000 academic year were returning to the classroom after taking time off, which was relatively consistent with estimates from the prior 10 years. Given that “stopping out” is typically related to life circumstances such as child rearing, it is unlikely that this form of temporary attrition would be significantly related to the types of fit used in this analysis.

Moving forward, fit and teacher retention warrant continued attention in educational policy and research, particularly when one aim is to increase retention of highly effective teachers while minimizing costly efforts to retain lower performers who are unlikely to improve. Even the most talented teachers will be unable to reach their full potential if their teaching positions are not a good fit. Using recruitment and selection policies to match teachers with the environment in which they are most likely to be successful is a promising strategy for improving both retention and student achievement. As policy continues to emphasize using teacher effectiveness as a component of teacher and school evaluation, fit with one’s school and with the teaching profession should also remain a focus of policymakers, practitioners, and researchers.

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Endnotes

1. All sample sizes are rounded to the nearest 10 to comply with NCES data reporting.

Please do not cite without permission of the authors.