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Social Sources of Teacher Self-Efficacy: The Potency of Teacher Interactions and Proximity to Instruction


by Sabina Rak Neugebauer, Megan Hopkins & James P. Spillane - 2019

Background: Research over the past two decades documents how social capital, or the resources attained through social relationships, is associated with a range of outcomes at both the individual and organizational levels. Yet few, if any, studies explore the relationship between social capital and teaching self-efficacy. Given that teaching self-efficacy is a significant predictor of instructional effectiveness, identifying the kinds of social interactions that facilitate positive teaching self-efficacy can offer important information with respect to how schools and school systems can bolster teachers’ perceived competence and thus their instructional capacity.

Objective: This study integrates social capital and social cognitive theories to frame an investigation of the social sources that contribute to teachers’ self-efficacy over time. Specifically, we explore how social interactions that vary in their relationship with and proximity to instruction influence teachers’ developing self-efficacy.

Research Design: We analyzed self-report survey data from 345 teachers in the same district over 4 years. These data captured various social sources of teaching self-efficacy, including indicators of verbal persuasion and vicarious experiences, and allowed us to account for contextual variables found to influence teachers’ sense of mastery. We used the multilevel model for change framework to explore associations between these types of social interactions and teacher self-efficacy over time.

Findings: Results suggest that interactions firmly rooted in actual teaching practice—namely, those focused on a specific instructional episode (i.e., feedback about a class) or on particular teaching practices (i.e., discussions about specific teaching resources and artifacts)—were associated with higher reports of teaching self-efficacy over time. On the other hand, interactions that reflected more general or less targeted interactions about teaching (i.e., being sought out for general instructional advice or observing someone else teach) were not.

Conclusions: To further the capacity of individual teachers, school and system leaders should invest in supporting social interactions among teachers that afford direct and targeted opportunities to learn about particular instructional practices and to discuss specific teaching episodes. Interactions less proximal to classroom practice may be ineffective for promoting individual teachers’ feelings of teaching competence.



Research over the past two decades documents how social capital, generally defined as resources attained through social relationships (Coleman, 1988; Lin, 1999), is associated with valued school outcomes including student achievement (Leana & Pil, 2006; Supovitz, Sirinides, & May, 2010). For example, the extent to which teachers interact with one another about instruction has been positively associated with change in teachers’ practices and beliefs, as well as in student learning (Moolenaar, Sleegers, & Daly, 2012; Siciliano, 2016; Spillane, Hopkins, & Sweet, 2017; Supovitz et al., 2010). Studies have also identified diverse mechanisms through which social capital enables productivity at both the individual and organizational levels (Penuel et al., 2010; Penuel, Riel, Krause, & Frank, 2009; Pil & Leana, 2009; Spillane, Hopkins, & Sweet, 2015; Spillane, Shirrell, & Sweet, 2017; Supovitz et al., 2010). Social capital can contribute to teachers’ knowledge about instruction, their motivation to learn and improve their practice, as well as their implementation of instructional reforms (Bryk & Schneider, 2002; Daly, Moolenaar, Bolivar, & Burke, 2010; Frank, Zhao, & Borman, 2004; Frank, Zhao, Penuel, Ellefson, & Porter, 2011). In this paper, we contribute to this burgeoning body of scholarship and focus on the relationship between social capital and teachers’ self-efficacy, specifically the social sources of teaching self-efficacy.


We center our work on self-efficacy because teachers’ self-efficacy, that is, their perceived competence in their teaching, is predictive of instructional productivity and effectiveness (Gibson & Dembo, 1984; Ross, 1998; Tschannen-Moran, Woolfolk Hoy, & Hoy, 1998). Teachers who perceive themselves to be more effective are more likely to adopt interactive instructional methods and supportive practices and to be more amenable to new pedagogies; as a result, teachers with greater self-efficacy tend to have higher achieving students (Anderson, Greene, & Loewen, 1988; Ashton & Webb, 1986; Midgley, Feldlaufer, & Eccles, 1989; Ross, 1992). Believing that one can make a difference influences one’s performance in the classroom.


Much of the literature tends to focus on how teachers’ individual attributes (e.g., knowledge, experience) and attributes of their students (e.g., achievement) are associated with their self-efficacy (Bates & Khasawneh, 2007; Gibbs, 2003; Walter, 2015; Walter & Amasha, 2013). Yet the literature on social capital in schools would suggest that the social or situational aspects of teachers’ performance may yield potentially powerful predictors of their self-efficacy. Although existing studies on teacher self-efficacy have considered situation-related variables such as school climate, the role of the principal, collective efficacy, or district or school context (Chester & Beaudin, 1996; Hoy & Woolfolk, 1993; Lee, Dedrick, & Smith, 1991), few studies examine teachers’ self-efficacy as a function of the resources they attain through social relationships (see Siciliano, 2016, for an exception). Our study thus addresses the following research questions: Does social capital influence teachers’ self-efficacy? If so, what kind of social relations are most predictive of self-efficacy? To identify social sources of teachers’ self-efficacy, our longitudinal analysis controls to the extent possible for individual teacher and student characteristics.


Our contributions are twofold. First, we show that social capital does indeed influence self-efficacy in that teachers’ access to resources through their relations with others contributes to increases in their self-efficacy over time. This finding contributes to the literature by identifying another mechanism through which social capital enables improvement in individual productivity: self-efficacy. Second, we show that social relations are not all equal when it comes to developing teachers’ self-efficacy. Specifically, social relations that are most proximal to teaching practice, that is, firmly anchored in classroom instruction and involving direct feedback or discussion about specific teaching activities, are more likely to be associated with increases in teachers’ self-efficacy than are less instructionally focused interactions. Thus, while facilitating social interactions among teachers is important for supporting instructional improvement (Coburn & Russell, 2008; Frank et al., 2011; Hopkins & Spillane, 2015; Hopkins, Spillane, Jakopovic, & Heaton, 2013; Penuel et al., 2010), considerations of the nature and substance of those interactions are also critical.


FRAMING THE WORK


Our study builds on research on social capital in schools by exploring the social sources of teachers’ self-efficacy through the lens of social cognitive theory (Bandura, 1986, 1997).


SOCIAL CAPITAL IN SCHOOLS


Teachers’ interactions matter for supporting instructional improvement. The extant research on social capital in schools, particularly studies focused on social influence, highlights the importance of teachers’ collegial interactions for facilitating changes in their instructional practice and reform implementation (e.g., Frank et al., 2011; Penuel, Frank, Sun, Kim, & Singleton, 2013; Sun, Wilhelm, Larson, & Frank, 2014). In one study of reading reform implementation, for example, the more the colleagues with whom a teacher interacted implemented reform-aligned practices, the more likely she was to implement similar practices (Penuel et al., 2013). Other studies focused on mathematics education found that teachers’ exposure to colleagues’ knowledge or beliefs related to reform-oriented mathematics instruction—via their social interactions—were significantly related to their reported practices in or beliefs about mathematics (Spillane, Hopkins, & Sweet, 2017; Sun et al., 2014). Moreover, one recent study specifically exploring self-efficacy beliefs showed that the self-efficacy of a teacher’s peers, or those colleagues with whom she was connected to in an advice network, was positively associated with her own self-efficacy (Siciliano, 2016). Given that this body of research tends to focus primarily on teachers’ instructional advice (i.e., whether and how often teachers seek out colleagues for instructional advice), it does not afford comparisons between different types of interactions among teachers or explore how these differences might matter for teachers’ practices or beliefs. Our study builds on this scholarship by examining how engagement in different kinds of social interactions influences teachers’ self-efficacy, an important predictor of instructional effectiveness. To capture various social sources of self-efficacy, we employ Bandura's social cognitive theory, to which we now turn.


SOCIAL COGNITIVE THEORY


We draw on Bandura’s (1986, 1997) social cognitive theory to delineate differences in social sources of teacher self-efficacy. In particular, we concentrate on two of the four sources of self-efficacy Bandura identifies that are explicitly related to the nature of social interactions and our focus on social capital: vicarious experiences (i.e., seeing others model the target activity) and verbal persuasion (i.e., feedback from others about specific performance). The two additional sources of self-efficacy include mastery experiences (i.e., successful previous performance) and physiological arousal (i.e., feelings of vulnerability or comfort during the target activity), the former of which we also include in our analysis. Bandura’s theory postulates that these four sources of information influence one’s interpretation of one’s self-efficacy. We focus primarily on vicarious experience and verbal persuasion and examine whether and how these different types of social interactions influence teachers’ self-efficacy over time.


Empirical research to expressly support the association between these sources and teacher self-efficacy has focused most robustly on mastery experiences, a source found to be particularly predictive of teacher self-efficacy (Tschannen-Moran & Woolfolk Hoy, 2007). Research most closely aligned with Bandura’s theory examines mastery using items that ask individuals to rate their present and past performance (Lent, Lopez, & Bieschke, 1991), and other studies use actual performance as a proxy for interpretations of competence (Chin & Kameoka, 2002; Johnson, 2005). Less research explores the remaining three sources (i.e., vicarious experience, verbal persuasion, and physiological arousal), with the former two of most interest to our present investigation of different types of social interactions.


Vicarious experience and verbal persuasion are the constructs most directly influenced by social resources, i.e., they involve targeted kinds of interactions with others that inform one’s sense of efficacy. By contrast, physiological arousal can reflect a variety of stimuli. Vicarious experience is commonly assessed with items that capture the degree to which one sees the target task modeled by others and thus is provided with an opportunity to see efficacious performance (Lent et al., 1991; Usher & Pajares, 2008). Verbal persuasion is generally assessed with items that ask individuals to rate whether they receive validating messages of their ability from others (Lent et al., 1991; Matsui, Matsui, & Ohnishi, 1990) or with items that ask individuals to mark the extent to which they receive regular feedback from others (Bates & Khasawneh, 2007). Studies on these two constructs vary in how strictly aligned they are with Bandura’s conceptualization of these sources of efficacy, with Bandura’s conceptualizations focused on individuals’ interpretations above and beyond actual outcomes.


Overall, research on the association between these sources and teachers’ self-efficacy remains inconclusive. While researchers have found a positive association between interpretations of mastery and self-efficacy (Lent et al., 1991; Lopez & Lent, 1992) as well as past performance and self-efficacy (Chin & Kameoka, 2002; Matsui et al., 1990), findings on the role of verbal persuasion and vicarious experience has been mixed. Results from one study indicated that mastery experiences, verbal persuasion, and physiological arousal explained self-efficacy, while vicarious experience did not (Anderson & Bentz, 2001); however, other studies determined that vicarious experience was a robust predictor of efficacy (Hampton, 1998; Klassen, 2004). In these same studies, the role of verbal persuasion was also debated (Anderson & Betz, 2001; Hampton, 1998; Klassen, 2004; Lopez & Lent, 1992).


These contradictory findings involve research with participants of varying ages and do not specifically focus on teachers. In one study that did focus on teachers, Uzuntiryaki (2008) used a qualitative interview approach to examine sources of efficacy and found that all four sources were evident across preservice chemistry teachers. Yet scant quantitative research with teachers has focused on the two sources of efficacy—vicarious experience and verbal persuasion—that reflect inputs (observed or communicated) that are conceptualized to influence self-efficacy. One recent study used a single item to capture verbal persuasion—“rate the interpersonal support provided by your colleagues at your school”—with response options ranging from nonexistent to excellent (Tschannen-Moran & Woolfolk Hoy, 2007). However, few studies have extended this exploration related to the social sources of teaching self-efficacy.


A growing body of research suggests that social interactions are an important consideration in understanding teachers’ self-efficacy (Fulle & Izu, 1986; Goddard, Hoy, & Woolfolk Hoy, 2000; Hipp & Bredeson, 1995; Lee et al., 1991; Newman, Rutter, & Smith, 1989; Rosenholtz, 1989; Tschannen-Moran & Barr, 2004). In one study, collective efficacy was associated with teachers’ individual efficacy and performance (Goddard et al., 2000), suggesting that teachers’ interactions in schools were related to their perceived competence. Yet few studies explicitly examine the influence of vicarious experiences and verbal persuasion on self-efficacy (Tschannen-Moran & Woolfolk Hoy, 2007), and none have conceptualized these factors within a social capital framework, in which these social exchanges serve as resources through which teachers can improve their sense of efficacy.


These social aspects of Bandura’s theory, when viewed within a social capital framework—whereby resources garnered via social relations influence one’s self-efficacy—may be seen as falling along a continuum with regard to their proximity or direct relation to teaching practice. Thus, these distinctive social relations may offer different benefits; for example, seeing others model the target activity and receiving feedback about one’s performance may offer more specific and targeted input that enables instructional improvement than other types of social interactions. We seek to better understand these social sources of self-efficacy and conceptualize these sources with regard to teachers’ access to social sources that are more or less anchored in instruction. Identifying social sources associated with teacher self-efficacy is a crucial first step for providing schools with an opportunity to foster social interactions among teachers that bolster teachers’ perceived competence and, in turn, increase their responsiveness to instructional improvement.


METHODS


To examine social sources that may serve as mechanisms for improving self-efficacy in schools, we followed teachers longitudinally in the same district setting over 4 years. Our study thus deviates from more common research designs that use cross-sectional data to examine teacher efficacy (Holzberger, Philipp, & Kunter, 2013) and accounts for multiple years of data across several school contexts. This approach reflects the reasonable assumption that the longer a teacher participates as a member of a community or social network, the more solidified and established social relationships become (Bridwell-Mitchell & Cooc, 2016). Using longitudinal analyses, we were able to comprehensively and robustly capture the potential explanatory power of social sources for teachers’ developing efficacy over time and account for time-sensitive factors that might alter this potential association. We were interested in exploring whether it could be the case that social relationships provide an initial boost in efficacy as teachers procure resources through these relationships, but continued exposure to the same resources may produce smaller effects over time. Alternatively, it could be the case that as teachers develop stronger and deeper relationships, the resources procured through these ongoing relationships might also deepen and recur, creating continued growth in self-efficacy. The relative absence of studies that explore teacher self-efficacy over time has limited the existing understanding of causal relationships and the role of these potentially time-varying sources of self-efficacy.


In addition to the longitudinal nature of our study, our methodological approach aimed to triangulate diverse information about the social environment in which teachers work. To this end, we incorporated social network analysis looking at teachers’ exchange of advice, an indicator of well-connected teacher networks in a school and an essential form of social interaction for receiving information and social support (Moolenaar et al., 2012). In so doing, we took seriously how social interactions may contribute to teachers’ self-efficacy and included these aspects of social dynamics that are more behavioral in nature in addition to teachers’ self-efficacy appraisals.


SAMPLE


Our study involved a mid-sized suburban school district in a Midwestern state. The district served approximately 5,800 students in 14 elementary schools during the 2012–2013 school year. We focused our work at the elementary level given that these teachers are more likely to have similar responsibilities in terms of the subjects they teach, and thus in terms of how they conceptualize their work, than teachers at the secondary level (Grossman & Stodolsky, 1994; Spillane & Hopkins, 2013). Across the 14 schools, the majority of students were white (80%), with about one quarter receiving free or reduced-price lunch. During our study, the district undertook a series of reforms focused on instructional improvement at the elementary level, including a new mathematics curriculum, a mathematics instructional coaching initiative, a redesigned professional learning community (PLC) routine for grade-level teams, district-level curriculum development committees composed of teachers from across the district, and multischool professional development activities (see Spillane, Hopkins, & Sweet, 2017, for more details).


Our dataset included teacher survey data in addition to student-level achievement and demographic data. All elementary (grades K–6) school staff members were asked to complete a survey each spring (i.e., toward the end of the school year) between 2010 and 2013 that asked a series of questions related to school organization and culture, efficacy, and advice and information networks. Response rates on the survey were as follows: 81% in 2010 (n=331), 95% in 2011 (n=393), 94% in 2012 (n=375), and 94% in 2013 (n=384), with only teachers who filled out more than 1 year of data included in the final dataset (n=345). Additionally, district administrators provided student-level demographic and achievement data for each year, including race/ethnicity, English learner (EL) status, receipt of free or reduced-price lunch, and achievement scores on district and state reading assessments. State standards require that all teachers be teachers of reading—that is, attend to students’ language and literacy development across content areas (National Governors Association Center for Best Practices & Council of Chief State School Officers, 2010). Thus, student reading assessment scores were also included as potential indicators of teachers’ self-efficacy in addition to the other listed student-level variables associated with teachers’ instructional context. We merged these student-level data, matched to teachers, with our survey data.


MEASURES


Dependent Variable


Teacher self-efficacy. We constructed our dependent variable of interest from a five-item scale (a=0.85) that was adapted from Goddard and LoGerfo’s (2007) efficacy survey. Each item asked teachers to indicate the extent to which they agreed with statements such as “When I try, I can get through to the most difficult students” and “If one of my students couldn’t do a class assignment, I would be able to assess accurately whether the assignment was at the correct level of difficulty.” Teachers’ scores were calculated as an average self-efficacy score across items for each survey year with responses ranging from 1 (“strongly disagree”) to 5 (“strongly agree”).


Independent Variables


Classroom demographic composition. Using the student-level demographic data provided by district administrators, we created a teacher-level variable that indicated the percentage of students in a teacher’s classroom who qualified for free or reduced-price lunch in each year of the study, which we used as a measure of socioeconomic status. We also created variables for the percentage of students in each teacher’s classroom identified as ELs, the percentage of nonwhite students, and the percentage of female students.


Mastery. Efficacy beliefs develop as teachers interpret information about their own attainment, i.e., mastery experiences (Bandura, 1997). To capture these experiences of mastery that influence teachers’ interpretations, we used several indicators of attainment: years of teaching experience, amount of professional development, the achievement of one’s students, and the accomplishment of receiving a leadership role at one’s school.


Teacher experience. Though less aligned with our focus on the social nature of efficacy, years of teaching experience could potentially serve as a behavioral indicator of mastery and is thus included in our models. The survey asked teachers: “How many years of teaching experience do you have?” We included responses as a continuous variable ranging from 1–30.


Professional development hours. Another indicator of mastery likely to explain teachers’ perceived efficacy is their frequency of attending professional development. Specifically, we asked teachers: “Please indicate approximately how many hours of professional development you participated in during the past summer and this school year in each of the following topics. Please treat these categories as mutually exclusive and report hours for each activity under one category only.” Areas included mathematics, reading/English language arts, science, student assessment, classroom management, and school leadership. We explored the professional development hours as the total number of hours reported by a teacher.


Classroom reading achievement. Using student-level achievement data, we created a classroom average score for district assessments in reading. First, we standardized all subscores for each test in each year. Then, those standardized scores were averaged together to make one average standardized score for each student. Finally, those scores were averaged for each teacher in each year to create an average classroom score for that year. Our analysis explored the effects of classroom average score on the district reading test. We included average scores on the district assessment as a context variable to understand how student performance in a given year (i.e., the extent to which students are performing below or above grade-level standards) influences self-efficacy. These scores were treated as z-scores, i.e., standardized to have a mean of zero and standard deviation of one.


Leadership role. Noticeably absent from the field of efficacy research are studies that capture messages sent to the individual by the school more broadly or by public figures (Usher & Pajares, 2008). In our study, we assess how having a formal leadership role sends messages of mastery to teachers. On the survey, we asked: “Are you assigned to a leadership role, such as curriculum coach, grade-level team leader, building math liaison, or school-based specialist?” We assigned a value of 1 if respondents indicated “yes” and a value of 0 if they responded “no.”


Social sources of self-efficacy. We used four variables to explore social sources of self-efficacy. Three of these variables pertained to verbal persuasion or feedback from others and allowed us to explore the effects of the nature and substance of teachers’ social interactions on self-efficacy: being sought out for instructional advice, instructional feedback, and engagement in instructionally focused interactions. We also included one variable to assess vicarious experiences, or how often teachers observed others teaching.


Being sought out for instructional advice. The extent to which teachers are sought out for general instructional advice (i.e., advice providing) offers an indicator of how often they receive more general feedback. We assume that the more other teachers go to a particular teacher for instructional advice and information, the more affirming feedback that teacher receives on his or her teaching. We used social network items to develop this variable, and specifically, a survey question that asked: “During this school year, to whom have you turned to for advice and/or information about curriculum, teaching, and student learning?” Respondents listed up to 12 individuals1, and these names were autopopulated in a follow-up question related to the content area (e.g., reading/language arts, mathematics, or other subjects) that was the focus of the interaction. We used these data to calculate a reading in-degree score, which indicates the number of teachers who indicated seeking out each teacher for advice or information related to reading instruction.


Instructional feedback. As another indicator of verbal persuasion, we created a composite score for each teacher in each year to indicate the frequency at which they received feedback from other teachers, teacher leaders, and administrators. The survey asked, “This school year, how often did the following people give you feedback after observing you teach?” Teachers indicated how often they received feedback from “another classroom teacher,” “a specialist or teacher leader,” “principal,” and “assistant principal” on a scale from 1 (never) to 6 (daily); this was calculated as the total amount of feedback received.


Engagement in instructionally focused discussions. To understand the quality of teachers’ social interactions and to address the diversity of social sources and appraisals teachers receive from others, we captured how often teachers shared information and engaged in instructionally focused discussions with one another. Specifically, the survey included nine items related to the following stem: “With other teachers in this school, I….” Teachers rated their frequency of engagement in the following activities on a scale from never (1) to daily (4): share ideas on teaching, discuss what they learned at a workshop, share and discuss research on effective teaching methods, share and discuss research on effective instruction practices for ELs, explore new teaching approaches for underperforming students, analyze samples of work done by your students, develop teaching materials or activities for particular class, seek each other’s advice about instructional issues or problems, and discuss assessment data to make decisions about instruction. We created a summed score across items.


Observations of others’ teaching. To capture teachers’ vicarious experiences, or the extent to which they observed instructional practices modeled, we also included survey responses related to how often they observed their colleagues teaching. The survey asked: “This school year, how often did you observe any of the following people teach?” We used teachers’ responses specific to observing “another classroom teacher,” “a specialist or teacher leader,” “the principal,” and “assistant principal” from 1 (never) to 6 (daily) and created a summed score of total frequency.


DATA ANALYSIS


Growth Models


We fit a growth model, or a multilevel model for change (Singer & Willett, 2003) to examine teacher self-efficacy across four waves of data, from 2010 to 2013. This model provides a useful tool for understanding questions regarding systematic interindividual differences over time using longitudinal data. To address our research questions related to self-efficacy, we fit a taxonomy of multilevel models for change to a person-period dataset that included longitudinal data on all sampled teachers, using SAS PROC MIXED with maximum likelihood estimation.


Though common in other studies that employ growth modeling, our central focus was not specifically on the population average growth trajectory for teachers’ self-efficacy, as self-efficacy likely ebbs and flows based on a range of school-based experiences. Instead, our focus was on the explanatory power of various social sources for explaining individual differences in teachers’ self-efficacy trajectories over time. Below is an example of a conditional growth model equation for one of the social sources we examined: instructional feedback.


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                              [39_22611.htm_g/00004.jpg]

                              [39_22611.htm_g/00006.jpg]

[39_22611.htm_g/00008.jpg]                                                                                                                              [39_22611.htm_g/00010.jpg]


This multilevel model in its linear mixed model format is as follows:


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In this model, Y is self-efficacy for teacher i at time j. The intercept, [39_22611.htm_g/00014.jpg], represents the average self-efficacy in 2010 (time=0), for teachers who received no feedback in that year. Then,[39_22611.htm_g/00016.jpg] represents the population average yearly rate of change in self-efficacy, controlling for instructional feedback, and [39_22611.htm_g/00018.jpg] captures the association between instructional feedback and self-efficacy across individuals. Additional variables (e.g.,[39_22611.htm_g/00020.jpg]) represent the other independent variables added in subsequent models. Next, [39_22611.htm_g/00022.jpg]represents teacher i’s deviation from the overall self-efficacy score at baseline[39_22611.htm_g/00024.jpg] represents the deviation in teacher i’s rate of change in self-efficacy over time from the average rate of change across teachers, and [39_22611.htm_g/00026.jpg] represents the error term for teacher i at time j. We assume that teacher i’s self-efficacy score at time j depends on: a) the year of teaching in which they were assessed, and b) the amount of feedback received in that year. This equation also allows teachers to have unique intercepts and slopes, assuming the true trajectory for every teacher is linear regardless of the level or rate of change in self-efficacy. Indeed, an exploration of the person-period data and individual growth trajectories supported a linear trajectory, as did preliminary model building.


In addition to this basic model intended to capture associations between various measures of social sources and self-efficacy scores across individuals, we also tested for potential cross-product effects. Specifically, ([39_22611.htm_g/00028.jpg]feedbac[39_22611.htm_g/00030.jpg]* Year[39_22611.htm_g/00032.jpg]) was included to explore whether or not the rate of change (i.e., slope) in self-efficacy scores differed as a function of instructional feedback, that is, whether the impact of feedback (or other measures) varied over time. We investigated cross-product terms for each social source measure as well as relevant controls to explore both the main effect and the cross-product. The parameters in the second set of brackets in the linear mixed model equation represent the three person-specific residuals. All variables for which zero was a possible value were uncentered, and those that did not include zero as a possible value were grand-mean centered to make interpretations more feasible (Luke, 2004).


Model Taxonomy


We explored a taxonomy of models, commencing with an unconditional means model to determine the average self-efficacy score across all teachers and years, followed by an unconditional growth model. We then modeled multiple conditional growth models including our control variables. Specifically, we examined the main effect of predictors capturing classroom composition (i.e., percent of students who are ELs, students of color, and female, as well as average class achievement) that have been found to be related to teachers’ perceived competence (Tschannen-Moran & Woolfolk Hoy, 2007). Although we estimated models exploring interactions between these variables and time, that is, models exploring whether the rate of change in self-efficacy over time might differ by these time-varying control predictors, these interactions were not statistically significant.


Next, we fit four covariates to the data to explore the potential explanatory power of mastery experiences for teacher self-efficacy over time. State reading scores from the previous year were included as a time-varying lagged predictor, allowing us to explore whether teachers’ self-efficacy differed at initial status as a function of previous mastery, or if the elevation of self-efficacy at initial status differed as a function of state scores. We included additional time-varying predictors capturing whether a teacher held a formal leadership role and reported professional development hours. Years of teaching experience at the first wave of data was also included as a potential predictor of self-efficacy over time. An interaction between these predictors and the linear effect of time was estimated, but no statistically significant effects were determined.


Lastly, we fit a series of models exploring predictors related to social sources of self-efficacy. The first set of models in this series explored more direct and proximal social sources, including frequency of instructional feedback and engagement in instructionally focused discussions. A subsequent model included our social network variable capturing which individuals are approached most frequently for instructional advice or information. Then, we fit a model including less direct interaction about practice, that is, frequency with which teachers observed other teachers (i.e., vicarious experience). We also fit interactions between these time-varying predictors and time. We retained and included statistically significant predictors in subsequent models.


RESULTS


To contextualize our findings, we first present descriptive statistics for the teachers in the sample. Then, we describe results from our model building, highlighting the influence of classroom composition, mastery, and social source variables on teachers’ self-efficacy over time.


DESCRIPTIVE STATISTICS


The teachers in our sample were generally very experienced and had a variety of opportunities to engage in professional development and leadership activities. On average, teachers had 12 years of teaching experience (ranging from 1 to 30 years) and participated in an average of 13 hours of professional development (ranging from 8 to 40 hours) over the course of a given year (see Table 1). Participants identified as 90% female, and approximately 20% had a leadership role over the course of the years of the study, such as curriculum coach, grade-level team leader, building math liaison, or school-based specialist. With respect to teachers’ classroom contexts, an average of 16% of their students were students of color, 3% were ELs, and 25% received free or reduced-price lunch across years of the study. The average classroom standardized district reading z-score of .008 indicates that the average classroom reading score was close to zero, with scores ranging from -1.028 to 0.93.


Table 1. Average Teacher and Context Variables


Variables

Means (SD)

     

Outcome

2010

2011

2012

2013

Self-Efficacy

4.23 (.41)

4.25(.41)

4.25(.50)

4.28 (.43)

Social Interactions

    

Direct Input

    

Instructional Feedback

    

Teacher Feedback

2.21 (1.42)

2.04 (1.31)

3.08 (2.07)

2.15 (1.25)

Specialist or Teacher Leader Feedback

2.26 (1.33)

2.38 (1.13)

3.77 (1.92)

2.33 (1.12)

Principal Feedback

2.94 (1.03)

2.65 (1.01)

4.22 (1.72)

2.41 (0.98)

Assistant Principal Feedback

1.02 (0.18)

1.02 (0.19)

1.04 (0.42)

1.19 (0.55)

Engagement in Instructional Discussions

23.17 (4.60)

22.80 (4.46)

22.70 (4.62)

22.57 (4.61)

Advice Providing (Degree)

6.90 (4.40)

6.42 (3.75)

5.96 (3.12)

5.58 (3.29)

In Direct Input

    

Observations

    

Observations of Teachers

2.59 (1.62)

2.35 (1.57)

2.94 (1.99)

2.12 (1.23)

Observations of Specialists and Leaders

2.62 (1.35)

2.45 (1.34)

3.11 (2.00)

2.31 (1.23)

Observations of Principal

1.58 (1.01)

1.42 (0.91)

1.89 (1.79)

1.28 (0.74)

Observations of Assistant Principal

1.00 (0.00)

1.01 (0.16)

1.02 (0.12)

1.06 (0.31)

Mastery

2010–2013

   

First Year Teaching Experience

12.25 (9.18)

   

Professional Development

13.35 (4.43)

   

Leadership Role

.20 (.40)

   

Free Lunch

.25 (.20)

   

Female

.50 (.081)

   

Nonwhite

.159 (.11)

   

District Reading

.008 (.358)

   

ELL

.025 (.062)

   


Teachers’ self-efficacy was generally high, although scores ranged from 1 to 5 across years of the study. We observed very modest increases in teachers’ self-efficacy over time. In 2010, teachers reported an average self-efficacy score of 4.23, meaning that on average, teachers agreed with statements such as “When I really try, I can get through to most difficult students.” Teachers subsequently reported an average self-efficacy score of 4.25 in 2011 and 2012 and 4.28 in 2013. In terms of social sources of self-efficacy related to verbal persuasion, teachers reported receiving feedback from other teachers on average once a year in 2010, 2011, and 2013 and a few times a year in 2012. Teachers reported receiving feedback from specialists or teacher leaders on average once a year in 2010, 2011, and 2013, and monthly in 2012. In contrast, principals provided feedback a few times a year in 2010 and 2011, monthly in 2012, and once a year in 2013. Teachers on average reported never receiving feedback from assistant principals across years. Across school stakeholders and years, scores ranged from daily (instructional feedback=6) to never (instructional feedback =1).


Teachers observed other teachers on average a few times a year in 2010, and 2012, and only once a year in 2011, and 2013. They observed specialists and leaders on average a few times a year in 2010 and 2012, and only once a year in 2011 and 2013. Teachers observed principals in the classroom on average once a year in 2010 and 2012 and on average never in 2011 and 2013. Teachers engaged in instructional discussions about a variety of teaching practices on average 2.57, indicating that on average teachers share information with each other weekly and this pattern persisted across years. Across school stakeholders and years scores ranged from daily (observations = 6) to never (observations = 1).


With respect to less proximal social sources, teachers’ average reading in-degree in 2010 was 6.90, indicating that about 7 individuals reported turning to each teacher for instructional advice or information, with scores ranging from 0 to 32 across the sample. The average in-degree decreased over the course of the study, from 6.42 in 2011, and 5.96 in 2012, to 5.58 in 2013.


SOCIAL INTERACTIONS ANCHORED IN PRACTICE THAT INFLUENCE TEACHER SELF-EFFICACY OVER TIME


To illustrate our substantive findings, we first present our unconditional means model, Model 1 in Table 2, which indicates that the mean self-efficacy across all teachers and years was 4.25. More importantly, this model allowed us to observe that 43% of the total variation in self- efficacy scores was attributable to differences between teachers. Our unconditional growth model (Model 2) shows that in 2010, the average teacher had a nonzero self-efficacy score of 4.23 points (p<.001), indicating that teacher efficacy tended toward significance over time (γ=0.02, se=.0009, p <.07). The effect of time appears to be flat in this initial model; however, the statistically significant intercept and residual term indicate variation in intercepts across teachers, and given that time tended toward significance, we continued to explore the impact of time in subsequent models. Indeed, the existence of some random variability in the slope could be the result of some teachers becoming more efficacious over time while others became less efficacious, which resulted in the model showing minimal change over time. To assess whether there is statistically significant variation in teachers’ self-efficacy, and the rate of change in their self-efficacy, we explored our substantive models of interest that included parameters related to a context, mastery, verbal persuasion, and vicarious experiences.



Table 2. Results of Fitting a Taxonomy of Growth Models to the Teacher Self-Efficacy Data



Factors

Unconditional

Means

Model (M1)

Unconditional

Growth Model (M2)

Mastery

Model (M3)

Instructional Feedback

Model (M4)

Instructional Discussions Model

(M5)

Advice Providing

Model (M6)

Observations

Model (M7)

Final Model (M8)

Intercept

4.25 (0.018)

4.23 (.02)***

4.16 (.05)***

3.84 (.10)***

3.43 (0.28)***

4.10 (0.07)***

4.14 (0.09)***

3.33(0.24)***

Time

 

0.02 (.0009)~

0.02(.01)~

0.14 (0.05)**

0.20(0.14)

0.03(0.01)*

-0.03 (0.044)

0.14(0.05)**

Classroom Composition

 

 

 

 

 

 

 

 

Free or reduced lunch

        

English learner

        

Class average reading score

  

0.07 (.05)

0.07 (0.05)

0.09(0.05)~

0.06(0.05)

0.10 (0.055)

0.061(0.06)

Nonwhite

        

Female

        

Mastery

 

 

 

 

 

 

 

 

Years of teaching experience

 

.006 (.003)*

0.007 (.003)**

0.006(0.003)*

0.005(0.003)*

0.005(0.003)

.007 (0.003)**

Social Sources

        

Verbal Persuasion

 

 

 

 

 

 

 

 

Instructional feedback

   

0.04 (0.01)***

   

0.03(0.02)**

Engagement in instructional discussions

      

0.02(0.007)**

  

0.01(0.005)*

Advice providing (In-degree)

     

0.01 (0.007)~

 

0.01(0.007)

Vicarious Experience

 

 

 

 

 

 

 

 

Observations

     

0.004 (0.01)

 

Slopes for Social Sources

 

 

 

 

 

 

 

 

Instructional feedback

     

-0.01 (.006)**

   

-0.01(0.006)*

Observations

        

0.008 (0.006)

 

Advice providing

          

Engagement in Instruction discussions

      

-0.004(0.003)

   

Random Effects

 

 

 

 

 

 

 

 

Intercept

0.082(.009)***

0.08(.009)***

.07 (.012)***

0.07 (0.01)***

0.07(0.01)***

0.06(0.01)***

0.07(0.01)***

0.07(0.01)***

Time

 

.001 (.0002)

0.004 (.002)~

0.004 (0.003)*

0.003(0.002)~

0.004(0.002)*

0.004(0.003)~

0.004(0.003)*

Residual

0.11(.005)***

0.11(.001)***

.09 (.007)***

0.09(.008)***

0.09(0.008)***

0.09(0.007)***

0.09(0.008)**

0.09(0.008)***

2 log likelihood

1173.4

1170.5

480.8

419.0

455.80

455.70

413.80

363.30


Classroom Composition


Of the variables we explored related to classroom composition, only average reading scores on the district assessment were positively associated with teachers’ self-efficacy (γ=0.09, se=.05, p < .05), and thus was retained in our final model. This initial main effect finding provided some support that a class’ average ability level, as measured by district assessments, explained teacher self-efficacy in that year above and beyond classroom demographic composition.


Mastery


Once the mastery-related variable of teachers’ years of experience was added to our control model (γ =0.006, se=.003, p <.05), the average score on the district reading assessment was no longer statistically significant (γ = 0.70, se=.05, p=ns). Reading scores were no longer statistically significantly associated with self-efficacy once a teacher’s experience was taken into account. The significant effect of experience indicates that teachers with more years of teaching experience at the start of the study had higher levels of self-efficacy. Moreover, teachers with more years of experience continued to have higher levels of self-efficacy over time compared to teachers with fewer years of experience (see Model 3 in Table 2). The variance component for time was also significant in Model 3, indicating significant variation in slopes across teachers, individual trajectory differences that we were most interested in understanding. Notably, neither of the other two mastery-related variables, leadership role and professional development, were statistically significant predictors of the intercept or growth in teacher self-efficacy.


Social Sources of Self-Efficacy


Our findings related to verbal persuasion and vicarious experiences reveal that social sources more proximal to instruction were more influential on teachers’ self-efficacy than less proximal sources. First, Model 4 in Table 2 indicates that the main effect (γ =0.04, se=0.01, p <.0001) and interaction (γ = -0.01, se=.006, p < .001) of instructional feedback explained teachers’ self-efficacy scores over time. Thus, teachers who received more feedback about their instruction from other teachers, teacher leaders, and the school principal had higher levels of self-efficacy over time. However, the effect of instructional feedback decreased over time, as demonstrated by the negative slope coefficient (γ =-0.01), when accounting for years of experience at the start of the study as well as students’ average scores on district reading assessments. To illustrate this effect, we plotted prototypical values for teachers based on results from Model 4 (see Figure 1). For teachers who reported receiving the average amount of instructional feedback at the start of the study (feedback=8), the figure shows three different trajectories, holding constant years of experience and students’ average reading scores: (1) teachers who received consistent feedback over time, (2) teachers who declined by one unit of feedback each year, and (3) teachers who received increasing feedback each year. These results reveal that while there is a main effect for time alone, teachers who received higher levels of instructional feedback had higher self-efficacy scores across time.


Figure 1. Prototypical growth plots for teachers with increasing, decreasing, and consistent feedback about their teaching across time

[39_22611.htm_g/00034.jpg]


When we isolated the negative slope parameter of instructional feedback, however, we saw that the effect decreased over time, and by the final year of the study was zero. That is, the main effect parameter of 0.04 for instructional feedback is successively influenced by the negative interaction parameter, -0.01, with each additional year (see Model 4). Thus, while on average in 2010 the impact of instructional feedback is 0.03, in 2011 it is 0.02, in 2012 it is 0.01, and in 2013 it is 0.00. Stated differently, although teachers who received more instructional feedback had higher self-efficacy scores, the contribution of this feedback to self-efficacy lessened over time. This finding suggests that while feedback is beneficial, it is most beneficial for one’s developing efficacy beliefs when it is first received; with repeated exposure over time, feedback does not provide additional benefits.


Second, results from Model 5 in Table 2 related to teachers’ engagement in instructionally focused conversations revealed only a main effect for this variable (γ =0.02, se=0.007, p <.001). This finding suggests that teachers who engaged more frequently in instructionally focused conversations with their colleagues reported higher self-efficacy scores over time. The slope was not statistically significant (γ =0.004, se=0.003, p=ns), indicating that this effect did not change over time, in contrast with the effect for instructional feedback.   


Third, we found that the main effect of instructional advice providing was statistically significant (γ =0.005, se=0.003, p. < .05), yet the growth parameter was only marginally statistically significant (see Model 6). Although this finding suggests that teachers who were approached by more of their colleagues for instructional advice had higher self-efficacy over time, the effects of advice providing were no longer significant in our subsequent model, which included our vicarious experience measure focused on observing others teach. Results from Model 7 show that neither the main effect nor the interaction term for instructional observations were statistically significant, nor were the effects for advice providing. Overall, these findings suggest that interactions less proximal to instruction (i.e., routine interactions and observations versus instructionally focused conversations and feedback) may be less influential on teachers’ self-efficacy over time.


To test these emergent findings, we built a final model including all parameters that were uniquely statistically significant in Models 1 through 7. In Model 8, the main effect and interaction parameter for instructional feedback remained statistically significant, as did the main effect for engaging in instructionally focused discussions with colleagues, and years of teaching experience. Thus, those variables closely related to a teachers’ actual classroom instruction were more positively associated with teachers’ level of self-efficacy. In the case of instructional feedback, however, the effect became less impactful over time. We elaborate on these findings in the next section.


DISCUSSION


Our findings contribute to the theoretical and empirical literature about social capital and self-efficacy. Related to the former, our findings support the idea that social capital can serve as a mechanism for improving school outcomes via increases in teacher self-efficacy. While most prior empirical work on the returns to social capital in education focuses on how social relations enable knowledge development (Coburn, 2001; Daly & Finnigan, 2010; Frank et al., 2004; Frank et al., 2011; Spillane, 2004), our analysis identifies yet another return—improvement in teachers’ sense of self-efficacy. With respect to self-efficacy, we showed that verbal persuasion can bolster teachers’ feelings of perceived efficacy via more direct and proximal forms of input from other educators, even after controlling for various types of mastery (i.e., professional development, years of experience). We elaborate on these findings below and discuss their implications for practice.


First, we found that teachers who more frequently received instructional feedback and had greater opportunities to engage in instructionally focused discussions with colleagues reported higher levels of self-efficacy. Our study thus provides evidence that interactions firmly rooted in actual teaching practice—namely, those focused on a specific teaching episode (i.e., feedback about a class) or on particular practices (i.e., discussions about specific teaching resources and artifacts)—were associated with higher teaching self-efficacy beliefs. These types of interactions were more influential for teachers’ self-efficacy than interactions that reflected more general or less targeted interactions around teaching (i.e., being sought out for general instructional advice or observing someone else teach). To elaborate, advice about instruction was not what influenced teacher self-efficacy, but advice specifically anchored in actual teaching practice. When teachers received feedback about a specific teaching event or discussed student work samples or teaching materials for a particular class, they experienced higher levels of self-efficacy. This finding indicates that not all social relations about instruction are equal when it comes to supporting teachers’ self-efficacy; social interactions about instruction that are firmly anchored in a teacher’s actual teaching practice are more powerful than social interactions about instruction that are not directly tied to teaching practice and are more general interactions about practice broadly. These results provide additional insight for the existing literature on the benefits of teacher social interactions (Coburn & Russell, 2008; Frank et al., 2011; Penuel et al., 2010; Siciliano, 2016) and colleague advice (Sun et al., 2014) for improving teacher beliefs and practices. Specifically, this study highlights the importance of interactions focused explicitly on particular teaching events and the potential inutility of interactions that center on teaching or pedagogy in broad strokes.


In general, our findings related to feedback are consistent with work on the positive association between verbal persuasion and efficacy beliefs (Anderson & Bentz, 2001; Bandura, 1997; Bates & Khasawneh, 2007) and educational research highlighting the benefits of immediate and specific feedback for supporting change in beginning teachers’ practice (Scheeler, Ruhl, & McAfee, 2004). Moreover, our findings related to teachers’ engagement in instructionally focused discussions align with prior research highlighting the benefits of professional learning communities in schools for teacher learning and development, especially when teachers engage in joint activities focused on improving instructional practice or analyzing student data (Spillane, Shirrell, & Hopkins, 2016; Vescio, Ross, & Adams, 2008). Building on this work, our study points to a potentially important mechanism through which instructional feedback and discussions facilitate improvement: teachers’ self-efficacy.


Second, whereas the impact of engagement in instructionally focused discussions on teachers’ self-efficacy did not change over time, the effect of instructional feedback shifted over the 4 years of our study. To elaborate, while instructional feedback was positively associated with teachers’ self-efficacy, with more feedback at the start of the study associated with higher levels of self-efficacy, the effect of instructional feedback in subsequent years of the study on self-efficacy lessoned over time, with additional feedback having no effect at all on efficacy by the end of our study. One interpretation of this finding is that teachers benefit initially from receiving instructional feedback because they can make immediate changes in their practice to address that feedback and in turn, that generates a sense of being more efficacious. However, as time goes by, teachers may become sufficiently masterful that there is limited feedback to provide (i.e., a ceiling effect), and/or they may consistently receive the same kind of feedback, thus limiting the potential for growth in areas that could be improved. Given the significant relationship between instructional feedback and teachers’ self-efficacy, future research should explore these two possible reasons for the decreasing impact of instructional feedback in more depth. Our study found that the more years of experience a teacher had, the more efficacious they felt over time. In light of this, it might be particularly fruitful for subsequent studies to address the potentially different roles repeated feedback over time may play for novice teachers in particular.


Third, beyond social sources, as mentioned, years of experience was also a statistically significant predictor of teachers’ self-efficacy. It stands to reason that having more time in the classroom and more opportunities to try different practices and to perfect your craft would be associated with higher self-efficacy scores. Indeed, these findings align with other research documenting a positive relationship between mastery, past performance, and self-efficacy (Chin & Kameoka, 2002; Lent et al., 1991; Lopez & Lent, 1992; Matsui et al., 1990; Tschannen-Moran & Woolfolk Hoy, 2007). Further, the majority of teachers in our sample taught the same grade throughout the course of our study. Thus, they may have been able to revise, improve, and become more comfortable with their curriculum and their techniques over that time. In addition, more seasoned teachers may be more forgiving of errors or mistakes made during instruction that otherwise might contribute to decreased feelings of self-efficacy among novice teachers.


LIMITATIONS


Our study, like all research, has limitations. First, the fact that our study took place in one school district represents a threat to external validity, such that findings may not be generalizable to other, dissimilar contexts or teachers. Indeed, school context plays a crucial role in teachers’ developing efficacy beliefs (Chester & Beaudin, 1996; Hoy & Woolfolk, 1993; Lee et al., 1991), with research by Fullan (2011) on instructional feedback highlighting the school culture as a central indicator of teachers’ openness to instructional feedback. Drawing on Hattie’s (2009) findings about the benefits of teacher appraisal, Fullan suggests that in schools where teachers are motivated to learn from one another, teachers may be more likely to integrate feedback into their instructional practice; conversely, “Throw a good appraisal system in a bad culture and you get nothing but increased alienation” (Fullan, 2011, p. 10). There is some evidence to suggest that the teachers in our study worked in positive school cultures that facilitated their professional growth. Many teachers in our study, for example, had been in the district for several years (i.e., with an average of 12 years of experience) and had a variety of opportunities to attend professional development and to assume teacher leadership responsibilities. There was also a high level of interaction among teachers, with each teacher sought out for instructional advice by an average of seven others. It is thus reasonable to assume that the teachers in our study may have benefited from instructional feedback and discussions in ways that might be less common in schools with less positive school climates. Moreover, the teachers in our study may have had higher levels of self-efficacy to start with than teachers in other contexts. For example, in urban under-resourced districts—commonly characterized by high numbers of students of color and students from low socioeconomic backgrounds—where, on average, there are higher rates of teacher turnover, shortages in highly qualified teachers, and fewer appropriate curriculum resources, our findings might have looked very different (Anyon, 1997; Lankford, Loeb, & Wyckoff, 2002; National Center for Education Statistics [NCES), 2017). In such schools, teachers may have fewer opportunities for mastery experiences (given shortages, teacher transience, and limited resources) as well as less time and fewer available resources for rigorous discussions about instruction and its improvement. Nonetheless, the fact that findings from the present context pointed to significant relationships between social capital and self-efficacy warrants investigation in other contexts to understand when and under what conditions social sources of self-efficacy are beneficial.


Second, while we draw from social cognitive theory to frame our analysis of social interactions in schools, the measures we used to capture sources of efficacy beliefs, in some cases, deviated from more traditional ways of operationalizing these constructs. In particular, at the core of social cognitive theory is a focus on individuals’ interpretations of their social environment as opposed to actual outcomes (Bandura, 2006). Assessments grounded in this theoretical tradition commonly capture mastery and verbal persuasion by measuring individuals’ ratings of their past or present performance (Lent et al., 1991) in the case of the former and individuals’ interpretations of whether they received positive messages from others (Lent et al., 1991; Matsui et al., 1990) in the case of the latter. In the present investigation, we operationalized these variables in ways that reflect more recent work capturing teacher self-efficacy beliefs in particular via data collection methods (i.e., self-report) which inherently reflect teachers’ interpretations of their environment and experiences. Similar to work that captured mastery by assessing level of performance (Chin & Kameoka, 2002; Johnson, 2005) and verbal persuasion by asking individuals to mark the extent to which they received regular feedback from others (Bates & Khasawneh, 2007), the present investigation had teachers report on their achievements (i.e., how often they attended professional development, their potential leadership roles), their experience of the frequency of receiving feedback, and their perception of the frequency with which they were observed. We believe by virtue of our means of data collection—where teachers are reporting their perceptions of their social interactions as opposed to a log or data collected through the schools—these data ultimately reflect teachers’ perceptions of their social milieu, a core component of understanding social sources of efficacy beliefs. Future work should explore how these distinct ways of capturing social sources (behavioral or interpretive in nature) provide more or less insight into teachers’ developing efficacy beliefs.


Finally, another limitation is the restricted response scale of the self-efficacy outcome and, by extension, the constrained variability in the outcome to be explained by our social variables of interest. To elaborate, the average teaching self-efficacy rating in the first year of the study was already above the midpoint of the scale, reducing potential variability in growth to be explained over time. This is a common problem with affective measures that include a restricted Likert scale (Bandura, 2006; Gable & Wolf, 1993). However, it is noteworthy that even in the context of this limited variability in the outcome, the present investigation still found statistically significant associations between instructional feedback as well as engagement in instructional discussions and teaching self-efficacy over time. The present study used a commonly administered measure of teacher self-efficacy, yet for future longitudinal work where the aim is to capture incremental growth in self-efficacy as a function of a teacher’s school context, we would encourage the design of additional instruments with revised and extended rating scales that might provide more subtle gradations in self-perceptions. Including a larger range of response options may shed light on incremental changes in self-efficacy over time and across experiences.


IMPLICATIONS


Our emphasis on understanding the social sources of teachers’ self-efficacy has important implications for schools as social organizations and for higher education institutions serving preservice teachers. In our data, teachers’ access to resources through their relations with others contributed to increases in their self-efficacy over time, with the effect of those interactions lessening with repeated exposure in some cases. On the other hand, passive observations of classroom instruction, as well as general advice-related interactions, were not as predictive of teachers’ self-efficacy over time. Given the positive relationship between teachers’ self-efficacy and productivity (Gibson & Dembo, 1984; Ross, 1998; Tschannen-Moran et al., 1998), schools might do well to provide structures that help teachers engage with one another in purposeful and meaningful ways that are directly tied to and anchored in their actual instructional practice (Datnow, 2011). Such structures might require release time for teachers to observe one another and provide immediate and specific feedback. Or, they might require the involvement of a coach or teacher leader who can facilitate teachers’ engagement in instructionally focused discussions, perhaps within professional learning communities or grade-level or departmental teams. Such is the nature of an intervention like instructional rounds (City, Elmore, Fiarman, & Teitel, 2016), which can help schools develop cultures supportive of instructional improvement efforts and engage teachers in the kinds of social interactions that facilitate feelings of self-efficacy. Similarly, these findings are also relevant for teacher education programs and specifically lend support for field experiences where preservice teachers have the opportunity to teach in the field and thus, receive feedback and engage in discussions with inservice teachers and higher education faculty about specific practicum teaching episodes.


CONCLUSION


Combining social capital and social cognitive theory to frame an empirical investigation of change in teacher self-efficacy over time, our analysis underscores how school systems can contribute to the development of individual teacher capacity, even among the most experienced teachers, by developing social capital. Our account suggests that social interactions firmly anchored in instructional practice can move teachers beyond contrived collegiality to a culture of collaboration (Datnow, 2011) that can in turn influence teachers’ sense of efficacy.


Our study suggests that in order to further the capacity of individual teachers, school systems must invest in supporting social interactions in schools that are grounded in feedback about specific practices and discussions about actual teaching episodes. The present investigation indicates that more generic interactions around instruction that are not anchored in actual teaching episodes may be ineffective for promoting individual teachers’ feelings of teaching competence. Certainly, as others have shown, these kinds of interactions can have other highly beneficial returns for instruction and the school community (Coburn & Russell, 2008; Frank et al., 2011; Grossman, Wineburg, & Woolworth, 2001; Hopkins & Spillane, 2015; Hopkins et al., 2013). This study supports an important avenue for understanding the resources procured through social interactions that can contribute to self-efficacy: interactions that are most proximal and centered in actual teaching practices are more beneficial for improving teachers’ self-efficacy.


Note


1. Based on prior iterations of the survey, we found that limiting the list to 12 did not lead to significant omission of network actors. In the 2013 survey administration, for example, respondents listed an average of 6 people from whom they sought advice or information related to mathematics, ranging from 3 to 10.


Acknowledgment


Work on this article was supported by the Nebraska Math Study and the Distributed Leadership Studies (http://www.distributedleadership.org), funded by research grants from the National Science Foundation (DUE–0831835, REC–9873583, RETA Grant #EHR–0412510). Northwestern University’s School of Education and Social Policy and Institute for Policy Research also supported this work. We also wish to acknowledge and thank our collaborators at the University of Nebraska-Lincoln. All opinions and conclusions expressed in this article are those of the authors, and do not necessarily reflect the views of any funding agency.


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Cite This Article as: Teachers College Record Volume 121 Number 4, 2019, p. 1-32
https://www.tcrecord.org ID Number: 22611, Date Accessed: 1/25/2022 3:27:06 PM

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About the Author
  • Sabina Neugebauer
    Temple University
    E-mail Author
    SABINA RAK NEUGEBAUER is an assistant professor in the College of Education at Temple University. Dr. Neugebauer’s research focuses on teacher practices and instructional programs that support students’ language and literacy development. Two recent publications: “Teaching beyond the Intervention: The Contribution of Teacher Language Extensions to Vocabulary Learning in Urban Kindergarten Classrooms” in Reading and Writing with Michael Coyne, Betsy McCoach, and Sharon Ware and “Promoting Word Consciousness to Close the Vocabulary Gap in Young Word Learners” in the Elementary School Journal with Perla Gamez, Michael Coyne, Ingrid Colon, Betsy McCoach and Sharon Ware.
  • Megan Hopkins
    University of California, San Diego
    E-mail Author
    MEGAN HOPKINS is an assistant professor in the Department of Education Studies at the University of California, San Diego. Her research explores systems-level approaches to educational change and instructional improvement, with an emphasis on designing school systems that support equity and inclusion and that facilitate teacher learning and development. Two recent publications: "School system educational infrastructure and change at scale: Teacher peer interactions and their beliefs about mathematics instruction," with James P. Spillane and Tracy Sweet, and "Organizing English learner instruction in new immigrant destinations: District infrastructure and subject-specific school practice," with Rebecca Lowenhaupt and Tracy Sweet, both of which can be found in the American Educational Research Journal.
  • James Spillane
    Northwestern University
    E-mail Author
    JAMES P. SPILLANE is the Spencer T. and Ann W. Olin Professor in Learning and Organizational Change at the School of Education and Social Policy at Northwestern University. Spillane has published extensively on issues of education policy, policy implementation, school reform, and school leadership. His work explores the policy implementation process at the state, district, school, and classroom levels, focusing on intergovernmental and policy-practice relations. Two recent publications: “Educational reform as system building” in Educational Researcher with David Cohen and Don Peurach, and “The elephant in the schoolhouse: The role of propinquity in school staff interactions about teaching” in Sociology of Education with Matt Shirrell and Tracy Sweet.
 
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