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A multilevel analysis of the relationship between teacher and collective efficacy in urban schools
Teaching and Teacher Education 17 (2001) 807–818
A multilevel analysis of the relationship between teacher and collective efficacy in urban schools Roger D. Goddarda,*, Yvonne L. Goddardb a
University of Michigan, 4204 School of Education, 610 East University Avenue, Ann Arbor, MI 48109-1259, USA b University of Toledo, 5005 Gillham Hall, College of Education, Toledo, OH 43606, USA Received 21 September 2000; received in revised form 29 January 2001; accepted 15 March 2001
Abstract Although a great deal of research has linked both teacher and collective efficacy to student achievement, one overlooked question concerns the nested association between teacher and collective efficacy. The authors apply social cognitive theory to offer a theoretical analysis of this relationship. Next, using hierarchical linear modeling, they empirically test the strength of the relationship between these two theoretically related yet conceptually distinct constructs. Analysis of data collected from 438 teachers in 47 schools in a large urban school district shows that collective efficacy predicts variation in teacher efficacy above and beyond the variance explained by a number of school contextual factors including socioeconomic status and student achievement. The implications of these findings for future research are discussed. r 2001 Elsevier Science Ltd. All rights reserved. Keywords: Teacher efficacy; Collective efficacy; Student achievement; Social cognitive theory
1. A multilevel analysis of the relationship between teacher and collective efficacy in urban schools Bandura (1997) developed social cognitive theory to explain that the control humans exercise over their lives through agentive actions is powerfully influenced by the strength of their efficacy beliefs. Bandura defines efficacy as ‘‘beliefs in one’s capabilities to organize and execute the courses of action required to produce to given attainments’’ (p. 3). Perceptions of efficacy are important to individual and organizational behavior and change. *Corresponding author. Tel.: +1-734-764-7488; fax: +1734-763-1504. E-mail address: [email protected] (R.D. Goddard).
Notably, there are two distinct, but theoretically-related, types of efficacyFindividual and collective. For more than two decades researchers interested in individual teacher efficacy have investigated its correlates and argued that teachers’ perceptions of self-capability are important to student learning (e.g., Armor et al., 1976; Gibson & Dembo, 1984; Ross, 1992). More recently, researchers have shown that collective efficacy is also related to student achievement differences among schools (Bandura, 1993; Goddard, Hoy, & Woolfolk, 2000). But despite the promise of these constructs when considered independently, researchers have yet to consider their interrelationship. Our focus on teacher and collective efficacy was also motivated by troubling evidence indicating
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that, depending on personal characteristics and experiences, teachers new to urban schools sometimes experience declines in teacher efficacy during their first year (Chester & Beaudin, 1996). Notably, Chester and Beaudin’s study offers insight into individual-level predictors of variation in teacher efficacy, but they did not consider variation among schools in teacher efficacy. This made us curious to know whether teacher efficacy varied systematically among schools and, if so, to what extent a school’s collective efficacy in particular was predictive of this variation. As we discuss more fully later, collective efficacy is a potent way of characterizing the social influence of a school. In their review of the historical and theoretical development of teacher efficacy research, Tschannen-Moran, Woolfolk Hoy, and Hoy (1998) observed that ‘‘the effect of collective efficacy may be especially pronounced for novice teachers as they are socialized into the teaching profession’’ (p. 221). This indicated to us that other researchers were also interested in the relationship between teacher and collective efficacy. We decided to examine whether a school’s collective efficacy is systematically related to differences in teacher efficacy among schools. To inform this inquiry, we offer a theoretical analysis of the relationship between teacher and collective efficacy. Next, we report the results of a multilevel analysis of the relationship between teacher and collective efficacy observed in the elementary schools of a large urban district. Finally, we discuss the implications of the important connections we found between teacher and collective efficacy.
2. The effects of teacher and collective efficacy: research evidence Over more than 20 years, researchers have shown that teachers’ perceptions of their selfcapability to educate students are significantly and positively related to teacher behaviors that promote student achievement. The earliest connection between teacher efficacy and student achievement was established by Armor et al. (1976) in a study of reading gains among students in Los Angeles
schools. Using reading scores obtained from the 1974 and 1975 administrations of the California Test of Basic Skills, Armor et al. found that the higher the efficacy of teachers in a special reading program, the higher the reading gain of their students. Since then, other researchers have provided additional support linking teacher efficacy to student achievement (e.g., Anderson, Greene, & Loewen, 1988; Ashton & Webb, 1986; Ross, 1992). Notably, the relationship between teacher efficacy and student achievement appears to be indirect, with teacher efficacy influencing numerous teacher behaviors that, in turn, promote student achievement. According to Gibson and Dembo (1984), teacher efficacy ‘‘may influence certain patterns of behavior known to influence achievement gains’’ (p. 579). For example, Gibson and Dembo found that highly efficacious teachers tend to persist in helping struggling students arrive at correct answers rather than simply giving students answers or allowing others to provide the correct answers. Similarly, in their study of the relationship between teacher efficacy and student achievement, Ashton and Webb (1986) observed that ‘‘teachers with a high sense of efficacy seemed to employ a pattern of strategies that minimized negative affect, promoted an expectation of achievement, and provided a definition of the classroom situation characterized by warm interpersonal relationships and academic work’’ (p. 125). Since these earlier observations were made, several studies have confirmed that teacher efficacy is indeed associated with a number of important variables. These variables include organized and planful teaching (Allinder, 1994), the use of activity-based learning (Enochs, Scharmann, & Riggs, 1995), and student-centered learning (Czerniak & Schriver, 1994). Moreover, the higher teachers’ efficacy, the more humanistic their approach to pupil control (Woolfolk & Hoy, 1990). Teacher efficacy may also have an indirect effect on student achievement through its positive association with trust (Da Costa & Riordan, 1996; Goddard, Tschannen-Moran, & Hoy, in press), openness to educational consultation (DeForest & Hughes, 1992), positive attitudes toward educational reform (DeMesquita & Drake, 1994;
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Guskey, 1988; Smylie, 1988), teacher satisfaction (Lee, Dedrick, & Smith, 1991), and increased levels of parental involvement in schooling (HooverDempsey, Bassler, & Brissie, 1992, 1987). In light of the powerful findings about individual teacher efficacy, several researchers have considered efficacy at the organizational, or collective, level. For schools, collective efficacy refers to the perceptions of teachers in a school that the faculty as a whole can organize and execute the courses of action required to have a positive effect on students. Perceptions of efficacy serve to influence the behavior of individuals and the normative environment of collectives by providing expectations about the likelihood of success for various pursuits. The study of collective efficacy is relatively new. Indeed, Bandura (1997) observes that ‘‘although perceived collective efficacy is widely recognized to be highly important to a full understanding of organizational functioning, it has been the subject of little research’’ (p. 468).1 So far, these studies have investigated the relationship between collective efficacy and student achievement. One of the earliest collective efficacy studies was by Bandura (1993), who showed that collective efficacy is significantly and positively related to school-level achievement. More recently, two studies by Goddard and his colleagues (Goddard, 2000; Goddard, Hoy, & Woolfolk, 2000) showed that collective efficacy perceptions are an important predictor of differences among schools in studentlevel achievement. To summarize, several teacher efficacy studies and an emerging body of work on collective efficacy suggest that these constructs are related positively to student achievement. To date, however, no study has considered how efficacy perceptions interact across levelsFindividual and collective. Since they have the same theoretical underpinnings, teacher and collective efficacy are indeed potentially related. We turn now to a careful consideration of the shared theoretical 1 For a more detailed discussion of research on collective efficacy in other fields, and social cognitive theory at the group level, readers are referred to Chapter 11 of Bandura (1997) and Goddard, Hoy, and Woolfolk Hoy (2000).
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underpinnings and then a discussion of the relationship between teacher and collective efficacy.
3. Shared theoretical underpinnings As explained earlier, Bandura’s social cognitive theory (1997) provides the theoretical framework underlying both teacher and collective efficacy. A fundamental assumption of social cognitive theory is human agency. When humans and organizations (through the collective actions of group members) make choices, they exhibit agency. According to social cognitive theory, efficacy is key to the operation of agency because individuals and collectives are more likely to pursue activities for which they believe they have the capability to succeed. In addition to the assumption of agency, Bandura (1997) postulated four sources of information that influence individual efficacy: mastery experience, vicarious experience, social persuasion, and affective states. Bandura (1997) also emphasized that whether efficacy beliefs are enhanced or diminished after a given level of enactive experience is not simply an artifact of the performance; efficacy beliefs are created when individuals weigh and interpret their performance relative to other information. According to Bandura, ‘‘changes in perceived efficacy result from cognitive processing of the diagnostic information that performances convey about capability rather than the performances per se’’ (p. 81). The same is true for all four sources of efficacy informationFthe role of cognition is critical. Stated another way, individuals’ perceptions of self-efficacy for various pursuits arise from cognitive and metacognitive processing of relevant information. Importantly, Goddard, Hoy, and Woolfolk Hoy (2000) argue that the sources of efficacy information postulated by Bandura operate at both the individual and collective levels. In fact, Goddard (2000) showed that mastery experience explained variation among schools in collective efficacy above and beyond that accounted for by school SES or minority proportion. Similarly, just as schools learn vicariously from other schools, they
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are also influenced by leaders (social persuasion) and affective states that result from collective conditions such as successes or tragedies that impact all school members.
4. Theoretical rationale and hypothesis The findings reviewed above are evidence of a growing body of literature that documents the importance of both teacher and collective efficacy to student achievement. But, in our opinion, an interesting question has not yet been addressed in the research literature. Specifically, how is collective efficacy (an emergent property of schools) related to teacher efficacy (a teacher-level attribute)? Since social cognitive theory specifies that teachers’ perceptions of self and group capability influence their actions, it follows that these actions will be judged by the group relative to group norms such as those set by collective efficacy beliefs. According to Coleman (1985, 1987, 1990), norms develop to permit group members some control over the actions of others when those actions have consequences for the group. When a teacher’s actions are incongruent with the shared beliefs of the group, the teacher’s actions will be sanctioned by group members; in fact, Coleman argues that the severity of the social sanctions delivered to those who break norms will be equal in magnitude to the effect of norm-breaking on the collective. Thus, if most teachers in a school believe the faculty can successfully teach students, the normative and behavioral environment will press teachers to persist in their educational efforts so that students achieve to high levels. Moreover, the press to perform will be accompanied by social sanctions for those who do not. From a sociocognitive perspective, the power of such normative press may be understood as the effect of social persuasion on teachers’ individual efficacy perceptions. Another way to address the relationship between collective and teacher efficacy from a theoretical perspective is to consider how schools have collective mastery experiences. When a school as a unit experiences genuinely high levels
of student achievement, it is axiomatic to conclude that one or more teachers were directly successful with their students. In other words, when a school has a collective mastery experience, so too do one or more teachers. Thus, mastery experienceFone of the most powerful sources of efficacy-shaping information (Bandura, 1997; Pajares, 1997)Fhas the potential to operate in concert at both the individual and collective levels. From this perspective, teacher and collective efficacy may covary positively in response to a given mastery experience. In addition, we believe that evidence of a positive relationship between several school contextual variables and teacher efficacy is important to understanding the relationship between collective efficacy and teacher efficacy. For example, Moore and Esselman (1992) showed that teacher efficacy was positively associated with school climate, lack of impediments to effective instruction, and teacher empowerment. In addition, Hoy and Woolfolk (1993) found that teachers’ efficacy is influenced by the contextual variables of principal influence with superiors and the academic press of a school. Together, these studies suggest that school contextual factors are related to teachers’ perceptions of their self-efficacy for educating students successfully. These findings led us to consider whether collective efficacy, a way of characterizing the normative and behavioral context (i.e., social influence) of a school, would also be related to teacher efficacy. We believe that teachers’ perceptions of self-capability may be either enhanced or attenuated by perceptions of collective capability and related group member expectations for performance. Teachers are aware of and influenced by the social processes and collective beliefs that characterize a school. Indeed, an individual with modest teacher efficacy might persist more in the face of personal obstacles and setbacks in a school where teachers tend to believe in the group’s conjoint capability to educate the students successfully. Conversely, the same individual might experience a decrease in teacher efficacy upon joining a faculty that dwells on past group failures and has little expectation of organizational improvement. In such a context, even a highly
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efficacious teacher may begin to view personal effort and persistence as inconsequential and hence experience a decline in teacher efficacy. These examples are meant to illustrate the theoretical possibility that collective efficacy influences teacher efficacy through its effect on the normative and behavioral environment of the school. From a sociocognitive perspective, the power of such normative press may be understood as the effect of a faculty’s social persuasion (one of the four sources of efficacy-shaping information) on individual teacher efficacy. Based on the theoretical considerations described above, we hypothesized that collective efficacy would be a significant positive predictor of differences among schools in teacher efficacy. Below we describe the method employed to test this hypothesis.
5. Method 5.1. Sample The data for this study were obtained from a survey of teachers in a large urban school district located in the mid-western United States. Fiftytwo elementary schools from the district were randomly selected for inclusion. Of these, three declined to participate. The decision rule for including schools in the final sample was to obtain at least five faculty respondents per school. Since data beyond the scope of the present study were also collected, approximately half of the faculty received a survey assessing teacher and collective efficacy while the other half received a different survey. Within each faculty, survey distribution was randomized. Of the 49 participating schools, two provided fewer than five faculty respondents. This yielded a final sample of 452 teachers in 47 schools. Importantly, to guarantee their anonymity the teachers surveyed were not asked to report any demographic information (e.g., grade-level taught, gender, etc.) that could be used to identify them. The school district provided data indicating students’ free or reduced-price lunch status, gender, minority status, and academic achieve-
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ment measured by a mandatory state assessment administered to 4th grade students. 5.2. Efficacy measures The key distinction between individual and collective efficacy involves the objectFself or groupFof the efficacy perception. Hence, researchers interested in teacher efficacy have developed measures that assess a teacher’s perception of self-capability to educate students successfully (e.g., Gibson & Dembo, 1984). Collective efficacy, on the other hand, differs in that the assessment is not directed at individual capability. This is consistent with the approach taken by Bandura (1997) who observes that ‘‘collective efficacy is concerned with the performance capability of a social system as a whole’’ (p. 469). Hence, collective efficacy measures aggregate teachers’ perceptions of the extent to which the faculty as a whole can teach successfully. It is also important to observe the distinction between efficacy perceptions and outcome expectancies. Efficacy constructs measure a person’s belief in his/her ability to execute the actions required to succeed at a given task. Outcome expectancies, on the other hand, indicate a person’s belief that certain behaviors will lead to desired outcomes. Stated differently, a person may believe that particular behaviors will produce certain results (outcome expectancy), but concurrently believe that she/he is incapable of initiating those behaviors (low self efficacy). In such a case, it is one’s efficacy beliefs as opposed to outcome expectancies that are likely to be more predictive of whether one will successfully achieve some outcome (Bandura, 1997). 5.3. Teacher efficacy measure Teacher efficacy was measured using a five-item personal teacher efficacy scale based on Gibson and Dembo’s (1984) teacher efficacy scale. Scores on the five-item teacher efficacy subscale have been shown to have adequate internal consistency and a one factor structure in previous research (Hoy & Woolfolk, 1993; Woolfolk & Hoy, 1990). ‘‘If I really try hard, I can get through to even the most
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difficult or unmotivated students’’ is a sample item from the scale. 5.4. Collective efficacy measure An important reason for the lack of collective efficacy studies concerns the need for a measure of collective efficacy (Bandura, 1997; Pajares, 1996). This study employed a 21-item collective efficacy scale recently developed by Goddard, Hoy, and Woolfolk Hoy (in press). ‘‘Teachers in this school are able to get through to difficult students’’ is a sample item from the collective efficacy scale. 5.5. School-level control variables We were interested in controlling for other school contextual factors that might, in addition to collective efficacy, be related to differences among schools in teacher efficacy. Therefore, we used data provided by the district to construct measures of the proportion of students who received a free or reduced-price lunch and the minority student concentration. To produce a mean prior achievement score for each school, we aggregated 3rd grade students’ normal curve equivalent scores in mathematics on the 7th Edition of the Metropolitan Achievement Test administered one year before we surveyed faculty. In addition, we obtained a measure of school size that represented each school’s official student attendance as reported to the state department of education for the year. 5.6. Multilevel analyses An important consideration for any study that examines the relationship between teacher and collective efficacy is the unit of analysis problem. Conventional methods require single-level analysis which leads to the conceptual and empirical problems associated with either examining teacher-level perceptions of collective efficacy or school-level perceptions of teacher efficacy. To avoid these problems, we employed hierarchical linear modeling (HLM) (Bryk & Raudenbush, 1992). HLM avoids the aggregation bias, misestimated standard errors, and heterogeneity of
regression problems that sometimes compromise the results of ordinary least squares regression analyses of data in which (typically) one or more individual-level characteristics are aggregated to the group level. 5.7. Unconditional model Since we were interested in predicting variation between schools in teacher efficacy with schoollevel characteristics, we began our analysis with an unconditional multilevel model of the variation in teacher efficacy. This analysis allowed us to determine that there was statistically significant variation in teacher efficacy among the schools we sampled. Therefore, we proceeded with our multilevel modeling to explain this variation as a function of school contextual features and collective efficacy. 5.8. Predicting variation among schools in teacher efficacy The multilevel modeling approach employed to investigate the between-school variation in teacher efficacy was the means-as-outcomes analysis (Bryk & Raudenbush, 1992). Using this approach we were able to test several school contextual features and collective efficacy as predictors of teacher efficacy. At the teacher-level, variation within schools in teacher efficacy was modeled as follows: ð1Þ Teacher level: YðTEACHER
EFFICACYÞij
¼ B0j þ rij :
Since teachers were anonymous, no teacher-level variables were included in the level-1 model, hence level-1 variation in teacher efficacy is estimated by rij : Since we modeled variation among rather than within schools, rij was constant throughout our analyses. At the school-level, we first separately tested the effects of each of our school-level contextual controls (mean SES, minority concentration, school size, and mean prior achievement) and collective efficacy. This process allowed us to identify which of these variables was significantly related to variation among schools in teacher efficacy. As an example, the structural equation specifying variation among schools in teacher
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efficacy as a function of mean SES was as follows: ð2Þ School level: B0j ¼ g00 þ g01 WðMeanSESÞj þ m0j : Models of the effects of minority concentration, school size, mean prior achievement, and collective efficacy were analogous. Next, we combined the statistically significant predictors identified in the first five models to produce a parsimonious combined model that explained variation among schools in teacher efficacy. The results of these analyses are reported below.
6. Results The main question in this research concerned the effect of collective efficacy on teacher efficacy. We decided that to address this question, we should control for school contextual factors other than collective efficacy that might be related to betweenschool variation in teacher efficacy. Our contextual control variables included mean SES, mean prior mathematics achievement, minority concentration, and school size. Descriptive statistics for these variables and others relevant to the study are reported in Table 1. Notably, there is considerable variation across teachers in teacher efficacy with scores ranging from 1.40 (low teacher efficacy) to 6.0 (high teacher efficacy). The extent to which this variability in teacher efficacy is systematically associated with school membership was the focus of the multilevel analyses that followed. Also, over half the students in the schools surveyed were minority and nearly two-thirds received a free or reduced price lunch while the average normal curve equivalent score in mathematics across the 47 sampled schools was slightly below the 44th percentile. Thus, the urban schools sampled for this research served a large number of minority and poor students with slightly below average achievement. Correlations among select school-level variables are reported in Table 2. 6.1. Psychometric analysis and construction of efficacy scales Of the 452 sampled teachers, 438 (approximately 97%) returned usable answers to the
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teacher efficacy questionnaire. Teacher responses to the teacher efficacy scale items were submitted to a principal axis factor analysis. One factor was extracted with an eigenvalue of 2.106 explaining 42.12% of the variance. Factor loadings ranged from 0.62 to 0.70. The alpha coefficient of reliability for the teacher efficacy scale was 0.79. This is consistent with the reliability of scores on the scale in previous research (e.g., 0.77 in Hoy & Woolfolk, 1993; 0.81 in Woolfolk, Rosoff, & Hoy, 1990; 0.82 in Woolfolk & Hoy, 1990). The teacher efficacy score for each teacher was constructed as the mean of the teacher’s responses to all items in the teacher efficacy scale. The collective efficacy score for each school was obtained from a process that began by calculating a mean score for each of the collective efficacy scale items for each school. This produced 21 mean item scores for each school. At the school level, these 21 items were submitted to a principal axis factor analysis. A single factor was extracted with an eigenvalue of 12.00 that explained 57.13% of the variance. Factor loadings ranged from 0.61 to 0.93, with all but five items loading above 0.70. The alpha coefficient of reliability for scores on the collective efficacy scale was 0.96. Next, within each school the 21 mean scores were averaged to yield an overall collective efficacy score for each school.2
6.2. Multilevel results An unconditional analysis (one-way ANOVA with random effects) indicated significant variation among schools in teacher efficacy. Specifically, variation among the school means for teacher efficacy (Var (B0j )) was 0.04758 (w2=67.33, df=46, po0:05). This finding confirmed that teacher efficacy does indeed vary systematically with school characteristics. Given that teacher efficacy varied significantly among schools, we continued our analysis by building a school-level model to explain that variation. 2 Interested readers are directed to a validation study for a 12 item short form of the collective efficacy scale by Goddard (in press) that may be used in lieu of the 21 item scale employed for this research.
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Table 1 Descriptive statistics for teacher and school variablesa Mean Teacher level (n ¼ 452): Teacher efficacyb School level (n ¼ 47): Collective efficacyb School size Faculty size Faculty members surveyed Proportion of students receiving a free or reduced-price lunch Proportion of minority students Prior mathematics achievement
Std dev.
Min.
Max.
4.66
0.77
1.40
6.00
4.31 401.40 21.24 9.62 0.62 0.56 43.86
0.48 107.26 5.51 2.58 0.20 0.28 10.17
3.43 229 13 5 0.10 0.08 29.21
5.30 710 37 15 0.89 1.00 73.40
a
Variables used in multilevel analyses were subsequently standardized to a mean of zero and standard deviation of one. Teacher efficacy and collective efficacy were measured using Likert-type scales with items scaled from 1 (strongly disagree) to 6 (strongly agree). b
Table 2 Correlations among school-level variables (n ¼ 47) Variable
Collective efficacy
School size
SES
Minority concentrn.
Prior math achieve.
Collective efficacy School size Proportion low SES Minority concentration Prior mathematics achievement
F 0.279 0.726a 0.479a 0.731a
F 0.188 0.058 0.060
F 0.521a 0.867a
F 0.550a
F
a
po0.01.
We began by first separately testing each of the school-level contextual variables and collective efficacy as predictors of between-school variation in teacher efficacy. To facilitate comparison of their effect sizes, all school-level variables were standardized to a mean of zero and a standard deviation of one. These five analyses identified mean SES, mean prior mathematics achievement, and collective efficacy as significant predictors of variation among schools in teacher efficacy while school size and minority concentration were statistically unrelated to teacher efficacy. In the final step of the multilevel examination we considered the effects of the three statistically significant predictors simultaneously. The findings of this analysis (Combined Model) confirmed the main hypothesis of the study. The results indicated that a one standard deviation increase in collective
efficacy was associated with a 0.248 standard deviation increase in teacher efficacy. Importantly, when considered together, only collective efficacy was a significant predictor of differences between schools in teacher efficacy; neither mean prior achievement nor mean SES were significant predictors of teacher efficacy in the combined model. Thus, variation in collective efficacy explained variance in teacher efficacy above and beyond that accounted for by our school contextual controls. The effect sizes and associated p-values from these analyses are reported in Table 3. Another interesting question that we investigated in our multilevel analyses was the extent to which our various models explained betweenschool variation in teacher efficacy. Table 4 displays the proportion of variance explained by each model with a statistically significant predictor. Notably, mean SES and mean prior
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Table 3 Prediction of variation in teacher efficacy among school means with selected school characteristics (n ¼ 438 teachers in 47 schools) Model 1 Intercept Proportion minority Proportion low SES Number of students Prior math achievement Collective efficacy a b
0.005 0.082
2
3 0.008
0.011
4
5
Combined
0.009
0.020
0.023 F 0.042 F 0.035 0.247a
0.104b 0.045 0.108b 0.191a
po0.01. po0.05.
achievement alone each explain just under 25% of the variation among schools in teacher efficacy. Moreover, after accounting for the effects of mean SES (Model 2) and mean prior achievement (Model 4), in each case the remaining variation among schools in teacher efficacy is statistically non-zero. In other words, neither mean SES nor mean prior achievement explained all of the systematic variation among schools in teacher efficacy. The case is different, however, when assessing the relationship between collective efficacy and teacher efficacy (Model 5). As shown in Table 4, collective efficacy accounts for nearly three-fourths of the variation among schools in teacher efficacy. In addition, when collective efficacy is considered, the remaining variance is not statistically different from zero. In other words, collective efficacy predicts all of the variation in teacher efficacy detected in our sample. The results of the combined model are consistent with those of Models 2, 4, and 5. Namely, when considered with mean SES and mean prior achievement, collective efficacy is the lone statistically significant predictor of variation among schools in teacher efficacy and the model explains all of the between-school variation in teacher efficacy.
7. Discussion A great number of researchers have investigated the correlates of teacher efficacy and the relation-
ship of this important construct to student achievement. Far fewer have considered how school context is related to teacher efficacy. The findings of this study indicate that teacher efficacy does vary systematically among schools, at least in the urban elementary schools we sampled. Hence, organizations appear to play a role in teachers’ reported levels of efficacy. Next, our results provide initial evidence that the variation between schools in teacher efficacy may be explained by the collective efficacy of a school. Teacher efficacy was higher in the schools where collective efficacy was higher. Indeed, after accounting for the effects of mean prior achievement and mean SES, a one standard deviation increase in collective efficacy was associated with a quarter standard deviation increase in teacher efficacy. Moreover, collective efficacy explained all of the variation among schools in teacher efficacy in the schools we sampled. When considered together with the effects of school contextual features such as mean SES and mean prior achievement, collective efficacy was the only significant predictor of teacher efficacy differences among schools. It is not surprising that there exists a significant positive relationship between teacher and collective efficacy. To be sure, teachers ‘‘are not social isolates immune to the influence of those around them’’ (Bandura 1997, p. 469). As postulated by social cognitive theory, social influence shapes selfefficacy. Where teachers tend to think highly of the collective capability of the faculty, they may sense an expectation for successful teaching and hence
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Table 4 Proportion of variation in teacher efficacy among schools explained and remaining for models reported in Table 3 (n ¼ 438 teachers in 47 schools) Model
a,b
Proportion of variation explained Between-school variation remaininga
1
2
3
4
5
Combined
F F
0.247 0.03581c
F F
0.231 0.03657d
0.735 0.01263e
0.823 0.00815f
a
Proportion of variation in teacher efficacy explained and remaining reported only for models with statistically significant predictors. Proportion calculated as the reduction in variation among schools in teacher efficacy found in the unconditional multilevel analysis (0.04758, Chi-square=67.33, df=46, po0:05). c Chi-square=62.30, df=45, po0:05: d Chi-square=62.44, df=45, po0:05: e Chi-square=50.48, df=45, p ¼ 0:266: f Chi-square=49.13, df=43, p ¼ 0:241: b
work to be successful themselves. Conversely, where collective efficacy is low, it is less likely that teachers will be pressed by their colleagues to persist in the face of failure or that they will change their teaching when students do not learn. A minor limitation of this study was that teachers were guaranteed complete anonymity in the survey process. For this reason, no teacher demographic data were collected. Other researchers may wish to consider the possibility of obtaining teacher demographic data to examine the relative effects of these variables on teacher efficacy in a multilevel analysis that also includes collective efficacy at the school level. In addition, although we achieved statistical control by sampling only one type of school (elementary) within one urban school district, this also means that the schools we sampled are probably more homogenous in terms of SES, minority concentration, and student achievement than would be found in the general population. Therefore, we are not convinced by the results reported here that collective efficacy will explain all of the betweenschool variation in teacher efficacy in all types of schools. Future researchers might wish to examine the relationship between teacher and collective efficacy in other settings (e.g., non-urban secondary schools) to determine whether the results extend to demographically dissimilar populations.
Our results do have import, however, for the great many teachers and students who work and learn in urban school districts like the one we sampled. Indeed, our findings suggest that in this urban district, collective perceptions of faculty capability were predictive of the differences among schools in the perceptions that teachers held of their own self-capability. Such a result helps to show that collective efficacy is an important school contextual feature that is systematically related to teacher efficacy, adding to this line of teacher efficacy research. Moreover, building collective efficacy in schools may offer a new possibility for raising teacher efficacy and perhaps at least lessening the declines in teacher efficacy that are sometimes experienced by teachers when they leave their preservice programs (Chester & Beaudin, 1996; Tschannen-Moran, Woolfolk Hoy, & Hoy, 1998). Future researchers might address whether declines in teacher efficacy are attenuated for teachers who join schools with relatively high collective efficacy. The results are also important for the field of organizational studies as they suggest one way in which organizational characteristics may influence member performance. From the perspective of organizational improvement, Bandura (1997) has suggested that a strong leader who can ‘‘unite the community for common cause’’ (p. 501) and who empowers the faculty may be able to increase the collective efficacy of a school. Strong leadership
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and empowerment may indeed be aspects of organizational life that can build collective efficacy. Whether changes in collective efficacy lead to changes in teacher efficacy is, however, an unanswered question. Future researchers might wish to examine this question of causality. One way to do this is to study schools during a period of intense change (Bandura, 1997) to determine whether changes in collective efficacy do cause changes in teacher efficacy. One possibility that is consistent with the correlational evidence in this study is that teacher and collective efficacy have a reciprocal relationshipFa change in one may lead to changes in the other. Such a finding would have import regarding the manner in which teachers and schools influence one another and consequently the students they serve. Hoy & Woolfolk (1993), for example, found that ‘‘schools promoted personal teaching efficacy when teachers perceived that their colleagues (a) set high but achievable goals, (b) create an orderly and serious learning environment, and (c) respect academic excellence’’ (p. 365). They also found that teacher efficacy was higher when school principals are perceived as having influence with their superiors. Such findings suggest that features of school organization and leadership can serve to develop teacher efficacy. At a minimum, we believe the findings of this study illuminate possibilities for building teacher efficacy through school improvement and avenues for a great deal of future research that can further our understanding of both teacher and collective efficacy.
References Allinder, R. M. (1994). The relationship between efficacy and the instructional practices of special education teachers and consultants. Teacher Education and Special Education, 17, 86–95. Anderson, R., Greene, M., & Loewen, P. (1988). Relationships among teachers’ and students’ thinking skills, sense of efficacy, and student achievement. Alberta Journal of Educational Research, 34(2), 148–165. Armor, D., Conroy-Oseguera, P., Cox, M., King, N., McDonnell, L., Pascal, A., Pauly, E., & Zellman, G. (1976). Analysis of the school preferred reading program in selected Los Angeles minority schools [Report No. R-2007-LAUSD;
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ERIC Document Reproduction No. 130 243]. Santa Monica, CA: Rand Corporation. Ashton, P. T., & Webb, R. B. (1986). Making a difference: Teachers’ sense of efficacy and student achievement. New York: Longman. Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28(2), 117–148. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company. Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage Publications, Inc.. Chester, M. D., & Beaudin, B. Q. (1996). Efficacy beliefs of newly hired teachers in urban schools. American Educational Research Journal, 33(1), 233–257. Coleman, J. S. (1985). Schools and the communities they serve. Phi Delta Kappan, 66, 527–532. Coleman, J. S. (1987). Norms as social capital. In G. Radnitzky, & P. Bernholz (Eds.), Economic imperialism: the economic approach applied outside the field of economics. New York: Paragon House Publishers. Coleman, J. S. (1990). Foundations of social theory. Cambridge, Mass: Harvard University Press. Czerniak, C. M., & Schriver, M. L. (1994). An examination of preservice science teachers’ beliefs and behaviors as related to self-efficacy. Journal of Science Teacher Education, 5(3), 77–86. Da Costa, J. L., Riordan, G. (1996, April). Teacher efficacy and the capacity to trust. Paper presented at the annual meeting of the American Educational Research Association, New York. DeForest, P. A., & Hughes, J. N. (1992). Effect of teacher involvement and teacher self-efficacy on ratings of consultant effectiveness and intervention acceptability. Journal of Educational and Psychological Consultation, 3, 301–316. DeMesquita, P. B., & Drake, J. C. (1994). Educational reform and the self-efficacy beliefs of teachers implementing nongraded primary school programs. Teaching and Teacher Education, 10, 291–302. Enochs, L. G., Scharmann, L. C., & Riggs, I. M. (1995). The relationship of pupil control to preservice elementary science teacher self-efficacy and outcome expectancy. Science Education, 79(1), 63–75. Gibson, S., & Dembo, M. (1984). Teacher efficacy: A construct validation. Journal of Educational Psychology, 76(4), 569– 582. Goddard, R. D. (2000, April). Collective efficacy and student achievement. Paper presented at the annual meeting of the American Educational Research Association, New Orleans. Goddard, R. D. A theoretical and empirical analysis of the measurement of collective efficacy: The development of a short form. Educational and Psychological Measurement, in press. Goddard, R. D., Hoy, W. K., & Woolfolk, A. (2000). Collective teacher efficacy: Its meaning, measure, and effect on student
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achievement. American Education Research Journal, 37(2), 479–507. Goddard, R.D., Tschannen-Moran, M., & Hoy, W.K. (in press). Teacher trust in students and parents: A multilevel examination of the distribution and effects of teacher trust in urban elementary schools. Elementary School Journal. Guskey, T. R. (1988). Teacher efficacy, self-concept, and attitudes toward the implementation of instructional innovation. Teaching and Teacher Education, 4(1), 63–69. Hoover-Dempsey, K., Bassler, O. C., & Brissie, J. S. (1987). Parent involvement: Contributions of teacher efficacy, school socioeconomic status, and other school characteristics. American Educational Research Journal, 24, 417–435. Hoover-Dempsey, K. V., Bassler, O. C., & Brissie, J. S. (1992). Parent efficacy, teacher efficacy, and parent involvement: Explorations in parent-school relations. Journal of Educational Research, 85(5), 287–294. Hoy, W. K., & Woolfolk, A. E. (1993). Teachers’ sense of efficacy and the organizational health of schools. The Elementary School Journal, 93(4), 355–372. Lee, V. E., Dedrick, R., & Smith, J. (1991). The effect of the social organization of schools on teachers’ efficacy and satisfaction. Sociology of Education, 64, 190–208. Moore, W., Esselman, M. (1992). Teacher efficacy, power, school climate and achievement: A desegregating districts
experience. Paper presented at the annual meeting of the American Educational Research Association, San Francisco. Pajares, F. (1996, April). Current directions in self research: Self-efficacy. Paper presented at the annual meeting of the American Educational Research Association, New York. Pajares, F. (1997). Current directions in self-efficacy research. In M. L. Maehr, & P. R. Pintrich (Eds.), Advances in motivation and achievement (pp. 1–49). Greenwich, CT: JAI Press. Ross, J. A. (1992). Teacher efficacy and the effect of coaching on student achievement. Canadian Journal of Education, 17(1), 51–65. Smylie, M. A. (1988). The enhancement function of staff development: organizational and psychological antecedents to individual teacher change. American Educational Research Journal, 25, 1–30. Tschannen-Moran, M., Woolfolk Hoy, A., & Hoy, W. K. (1998). Teacher efficacy: Its meaning and measure. Review of Educational Research, 68, 202–248. Woolfolk, A., & Hoy, W. K. (1990). Prospective teachers’ sense of efficacy and beliefs about control. Journal of Educational Psychology, 82, 81–91. Woolfolk, A. E., Rosoff, B., & Hoy, W. K. (1990). Teachers’ sense of efficacy and their beliefs about managing students. Teaching and Teacher Education, 6, 137–148.
A multilevel analysis of the relationship between teacher and collective efficacy in urban schools Roger D. Goddarda,*, Yvonne L. Goddardb a
University of Michigan, 4204 School of Education, 610 East University Avenue, Ann Arbor, MI 48109-1259, USA b University of Toledo, 5005 Gillham Hall, College of Education, Toledo, OH 43606, USA Received 21 September 2000; received in revised form 29 January 2001; accepted 15 March 2001
Abstract Although a great deal of research has linked both teacher and collective efficacy to student achievement, one overlooked question concerns the nested association between teacher and collective efficacy. The authors apply social cognitive theory to offer a theoretical analysis of this relationship. Next, using hierarchical linear modeling, they empirically test the strength of the relationship between these two theoretically related yet conceptually distinct constructs. Analysis of data collected from 438 teachers in 47 schools in a large urban school district shows that collective efficacy predicts variation in teacher efficacy above and beyond the variance explained by a number of school contextual factors including socioeconomic status and student achievement. The implications of these findings for future research are discussed. r 2001 Elsevier Science Ltd. All rights reserved. Keywords: Teacher efficacy; Collective efficacy; Student achievement; Social cognitive theory
1. A multilevel analysis of the relationship between teacher and collective efficacy in urban schools Bandura (1997) developed social cognitive theory to explain that the control humans exercise over their lives through agentive actions is powerfully influenced by the strength of their efficacy beliefs. Bandura defines efficacy as ‘‘beliefs in one’s capabilities to organize and execute the courses of action required to produce to given attainments’’ (p. 3). Perceptions of efficacy are important to individual and organizational behavior and change. *Corresponding author. Tel.: +1-734-764-7488; fax: +1734-763-1504. E-mail address: [email protected] (R.D. Goddard).
Notably, there are two distinct, but theoretically-related, types of efficacyFindividual and collective. For more than two decades researchers interested in individual teacher efficacy have investigated its correlates and argued that teachers’ perceptions of self-capability are important to student learning (e.g., Armor et al., 1976; Gibson & Dembo, 1984; Ross, 1992). More recently, researchers have shown that collective efficacy is also related to student achievement differences among schools (Bandura, 1993; Goddard, Hoy, & Woolfolk, 2000). But despite the promise of these constructs when considered independently, researchers have yet to consider their interrelationship. Our focus on teacher and collective efficacy was also motivated by troubling evidence indicating
0742-051X/01/$ - see front matter r 2001 Elsevier Science Ltd. All rights reserved. PII: S 0 7 4 2 - 0 5 1 X ( 0 1 ) 0 0 0 3 2 - 4
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that, depending on personal characteristics and experiences, teachers new to urban schools sometimes experience declines in teacher efficacy during their first year (Chester & Beaudin, 1996). Notably, Chester and Beaudin’s study offers insight into individual-level predictors of variation in teacher efficacy, but they did not consider variation among schools in teacher efficacy. This made us curious to know whether teacher efficacy varied systematically among schools and, if so, to what extent a school’s collective efficacy in particular was predictive of this variation. As we discuss more fully later, collective efficacy is a potent way of characterizing the social influence of a school. In their review of the historical and theoretical development of teacher efficacy research, Tschannen-Moran, Woolfolk Hoy, and Hoy (1998) observed that ‘‘the effect of collective efficacy may be especially pronounced for novice teachers as they are socialized into the teaching profession’’ (p. 221). This indicated to us that other researchers were also interested in the relationship between teacher and collective efficacy. We decided to examine whether a school’s collective efficacy is systematically related to differences in teacher efficacy among schools. To inform this inquiry, we offer a theoretical analysis of the relationship between teacher and collective efficacy. Next, we report the results of a multilevel analysis of the relationship between teacher and collective efficacy observed in the elementary schools of a large urban district. Finally, we discuss the implications of the important connections we found between teacher and collective efficacy.
2. The effects of teacher and collective efficacy: research evidence Over more than 20 years, researchers have shown that teachers’ perceptions of their selfcapability to educate students are significantly and positively related to teacher behaviors that promote student achievement. The earliest connection between teacher efficacy and student achievement was established by Armor et al. (1976) in a study of reading gains among students in Los Angeles
schools. Using reading scores obtained from the 1974 and 1975 administrations of the California Test of Basic Skills, Armor et al. found that the higher the efficacy of teachers in a special reading program, the higher the reading gain of their students. Since then, other researchers have provided additional support linking teacher efficacy to student achievement (e.g., Anderson, Greene, & Loewen, 1988; Ashton & Webb, 1986; Ross, 1992). Notably, the relationship between teacher efficacy and student achievement appears to be indirect, with teacher efficacy influencing numerous teacher behaviors that, in turn, promote student achievement. According to Gibson and Dembo (1984), teacher efficacy ‘‘may influence certain patterns of behavior known to influence achievement gains’’ (p. 579). For example, Gibson and Dembo found that highly efficacious teachers tend to persist in helping struggling students arrive at correct answers rather than simply giving students answers or allowing others to provide the correct answers. Similarly, in their study of the relationship between teacher efficacy and student achievement, Ashton and Webb (1986) observed that ‘‘teachers with a high sense of efficacy seemed to employ a pattern of strategies that minimized negative affect, promoted an expectation of achievement, and provided a definition of the classroom situation characterized by warm interpersonal relationships and academic work’’ (p. 125). Since these earlier observations were made, several studies have confirmed that teacher efficacy is indeed associated with a number of important variables. These variables include organized and planful teaching (Allinder, 1994), the use of activity-based learning (Enochs, Scharmann, & Riggs, 1995), and student-centered learning (Czerniak & Schriver, 1994). Moreover, the higher teachers’ efficacy, the more humanistic their approach to pupil control (Woolfolk & Hoy, 1990). Teacher efficacy may also have an indirect effect on student achievement through its positive association with trust (Da Costa & Riordan, 1996; Goddard, Tschannen-Moran, & Hoy, in press), openness to educational consultation (DeForest & Hughes, 1992), positive attitudes toward educational reform (DeMesquita & Drake, 1994;
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Guskey, 1988; Smylie, 1988), teacher satisfaction (Lee, Dedrick, & Smith, 1991), and increased levels of parental involvement in schooling (HooverDempsey, Bassler, & Brissie, 1992, 1987). In light of the powerful findings about individual teacher efficacy, several researchers have considered efficacy at the organizational, or collective, level. For schools, collective efficacy refers to the perceptions of teachers in a school that the faculty as a whole can organize and execute the courses of action required to have a positive effect on students. Perceptions of efficacy serve to influence the behavior of individuals and the normative environment of collectives by providing expectations about the likelihood of success for various pursuits. The study of collective efficacy is relatively new. Indeed, Bandura (1997) observes that ‘‘although perceived collective efficacy is widely recognized to be highly important to a full understanding of organizational functioning, it has been the subject of little research’’ (p. 468).1 So far, these studies have investigated the relationship between collective efficacy and student achievement. One of the earliest collective efficacy studies was by Bandura (1993), who showed that collective efficacy is significantly and positively related to school-level achievement. More recently, two studies by Goddard and his colleagues (Goddard, 2000; Goddard, Hoy, & Woolfolk, 2000) showed that collective efficacy perceptions are an important predictor of differences among schools in studentlevel achievement. To summarize, several teacher efficacy studies and an emerging body of work on collective efficacy suggest that these constructs are related positively to student achievement. To date, however, no study has considered how efficacy perceptions interact across levelsFindividual and collective. Since they have the same theoretical underpinnings, teacher and collective efficacy are indeed potentially related. We turn now to a careful consideration of the shared theoretical 1 For a more detailed discussion of research on collective efficacy in other fields, and social cognitive theory at the group level, readers are referred to Chapter 11 of Bandura (1997) and Goddard, Hoy, and Woolfolk Hoy (2000).
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underpinnings and then a discussion of the relationship between teacher and collective efficacy.
3. Shared theoretical underpinnings As explained earlier, Bandura’s social cognitive theory (1997) provides the theoretical framework underlying both teacher and collective efficacy. A fundamental assumption of social cognitive theory is human agency. When humans and organizations (through the collective actions of group members) make choices, they exhibit agency. According to social cognitive theory, efficacy is key to the operation of agency because individuals and collectives are more likely to pursue activities for which they believe they have the capability to succeed. In addition to the assumption of agency, Bandura (1997) postulated four sources of information that influence individual efficacy: mastery experience, vicarious experience, social persuasion, and affective states. Bandura (1997) also emphasized that whether efficacy beliefs are enhanced or diminished after a given level of enactive experience is not simply an artifact of the performance; efficacy beliefs are created when individuals weigh and interpret their performance relative to other information. According to Bandura, ‘‘changes in perceived efficacy result from cognitive processing of the diagnostic information that performances convey about capability rather than the performances per se’’ (p. 81). The same is true for all four sources of efficacy informationFthe role of cognition is critical. Stated another way, individuals’ perceptions of self-efficacy for various pursuits arise from cognitive and metacognitive processing of relevant information. Importantly, Goddard, Hoy, and Woolfolk Hoy (2000) argue that the sources of efficacy information postulated by Bandura operate at both the individual and collective levels. In fact, Goddard (2000) showed that mastery experience explained variation among schools in collective efficacy above and beyond that accounted for by school SES or minority proportion. Similarly, just as schools learn vicariously from other schools, they
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are also influenced by leaders (social persuasion) and affective states that result from collective conditions such as successes or tragedies that impact all school members.
4. Theoretical rationale and hypothesis The findings reviewed above are evidence of a growing body of literature that documents the importance of both teacher and collective efficacy to student achievement. But, in our opinion, an interesting question has not yet been addressed in the research literature. Specifically, how is collective efficacy (an emergent property of schools) related to teacher efficacy (a teacher-level attribute)? Since social cognitive theory specifies that teachers’ perceptions of self and group capability influence their actions, it follows that these actions will be judged by the group relative to group norms such as those set by collective efficacy beliefs. According to Coleman (1985, 1987, 1990), norms develop to permit group members some control over the actions of others when those actions have consequences for the group. When a teacher’s actions are incongruent with the shared beliefs of the group, the teacher’s actions will be sanctioned by group members; in fact, Coleman argues that the severity of the social sanctions delivered to those who break norms will be equal in magnitude to the effect of norm-breaking on the collective. Thus, if most teachers in a school believe the faculty can successfully teach students, the normative and behavioral environment will press teachers to persist in their educational efforts so that students achieve to high levels. Moreover, the press to perform will be accompanied by social sanctions for those who do not. From a sociocognitive perspective, the power of such normative press may be understood as the effect of social persuasion on teachers’ individual efficacy perceptions. Another way to address the relationship between collective and teacher efficacy from a theoretical perspective is to consider how schools have collective mastery experiences. When a school as a unit experiences genuinely high levels
of student achievement, it is axiomatic to conclude that one or more teachers were directly successful with their students. In other words, when a school has a collective mastery experience, so too do one or more teachers. Thus, mastery experienceFone of the most powerful sources of efficacy-shaping information (Bandura, 1997; Pajares, 1997)Fhas the potential to operate in concert at both the individual and collective levels. From this perspective, teacher and collective efficacy may covary positively in response to a given mastery experience. In addition, we believe that evidence of a positive relationship between several school contextual variables and teacher efficacy is important to understanding the relationship between collective efficacy and teacher efficacy. For example, Moore and Esselman (1992) showed that teacher efficacy was positively associated with school climate, lack of impediments to effective instruction, and teacher empowerment. In addition, Hoy and Woolfolk (1993) found that teachers’ efficacy is influenced by the contextual variables of principal influence with superiors and the academic press of a school. Together, these studies suggest that school contextual factors are related to teachers’ perceptions of their self-efficacy for educating students successfully. These findings led us to consider whether collective efficacy, a way of characterizing the normative and behavioral context (i.e., social influence) of a school, would also be related to teacher efficacy. We believe that teachers’ perceptions of self-capability may be either enhanced or attenuated by perceptions of collective capability and related group member expectations for performance. Teachers are aware of and influenced by the social processes and collective beliefs that characterize a school. Indeed, an individual with modest teacher efficacy might persist more in the face of personal obstacles and setbacks in a school where teachers tend to believe in the group’s conjoint capability to educate the students successfully. Conversely, the same individual might experience a decrease in teacher efficacy upon joining a faculty that dwells on past group failures and has little expectation of organizational improvement. In such a context, even a highly
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efficacious teacher may begin to view personal effort and persistence as inconsequential and hence experience a decline in teacher efficacy. These examples are meant to illustrate the theoretical possibility that collective efficacy influences teacher efficacy through its effect on the normative and behavioral environment of the school. From a sociocognitive perspective, the power of such normative press may be understood as the effect of a faculty’s social persuasion (one of the four sources of efficacy-shaping information) on individual teacher efficacy. Based on the theoretical considerations described above, we hypothesized that collective efficacy would be a significant positive predictor of differences among schools in teacher efficacy. Below we describe the method employed to test this hypothesis.
5. Method 5.1. Sample The data for this study were obtained from a survey of teachers in a large urban school district located in the mid-western United States. Fiftytwo elementary schools from the district were randomly selected for inclusion. Of these, three declined to participate. The decision rule for including schools in the final sample was to obtain at least five faculty respondents per school. Since data beyond the scope of the present study were also collected, approximately half of the faculty received a survey assessing teacher and collective efficacy while the other half received a different survey. Within each faculty, survey distribution was randomized. Of the 49 participating schools, two provided fewer than five faculty respondents. This yielded a final sample of 452 teachers in 47 schools. Importantly, to guarantee their anonymity the teachers surveyed were not asked to report any demographic information (e.g., grade-level taught, gender, etc.) that could be used to identify them. The school district provided data indicating students’ free or reduced-price lunch status, gender, minority status, and academic achieve-
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ment measured by a mandatory state assessment administered to 4th grade students. 5.2. Efficacy measures The key distinction between individual and collective efficacy involves the objectFself or groupFof the efficacy perception. Hence, researchers interested in teacher efficacy have developed measures that assess a teacher’s perception of self-capability to educate students successfully (e.g., Gibson & Dembo, 1984). Collective efficacy, on the other hand, differs in that the assessment is not directed at individual capability. This is consistent with the approach taken by Bandura (1997) who observes that ‘‘collective efficacy is concerned with the performance capability of a social system as a whole’’ (p. 469). Hence, collective efficacy measures aggregate teachers’ perceptions of the extent to which the faculty as a whole can teach successfully. It is also important to observe the distinction between efficacy perceptions and outcome expectancies. Efficacy constructs measure a person’s belief in his/her ability to execute the actions required to succeed at a given task. Outcome expectancies, on the other hand, indicate a person’s belief that certain behaviors will lead to desired outcomes. Stated differently, a person may believe that particular behaviors will produce certain results (outcome expectancy), but concurrently believe that she/he is incapable of initiating those behaviors (low self efficacy). In such a case, it is one’s efficacy beliefs as opposed to outcome expectancies that are likely to be more predictive of whether one will successfully achieve some outcome (Bandura, 1997). 5.3. Teacher efficacy measure Teacher efficacy was measured using a five-item personal teacher efficacy scale based on Gibson and Dembo’s (1984) teacher efficacy scale. Scores on the five-item teacher efficacy subscale have been shown to have adequate internal consistency and a one factor structure in previous research (Hoy & Woolfolk, 1993; Woolfolk & Hoy, 1990). ‘‘If I really try hard, I can get through to even the most
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difficult or unmotivated students’’ is a sample item from the scale. 5.4. Collective efficacy measure An important reason for the lack of collective efficacy studies concerns the need for a measure of collective efficacy (Bandura, 1997; Pajares, 1996). This study employed a 21-item collective efficacy scale recently developed by Goddard, Hoy, and Woolfolk Hoy (in press). ‘‘Teachers in this school are able to get through to difficult students’’ is a sample item from the collective efficacy scale. 5.5. School-level control variables We were interested in controlling for other school contextual factors that might, in addition to collective efficacy, be related to differences among schools in teacher efficacy. Therefore, we used data provided by the district to construct measures of the proportion of students who received a free or reduced-price lunch and the minority student concentration. To produce a mean prior achievement score for each school, we aggregated 3rd grade students’ normal curve equivalent scores in mathematics on the 7th Edition of the Metropolitan Achievement Test administered one year before we surveyed faculty. In addition, we obtained a measure of school size that represented each school’s official student attendance as reported to the state department of education for the year. 5.6. Multilevel analyses An important consideration for any study that examines the relationship between teacher and collective efficacy is the unit of analysis problem. Conventional methods require single-level analysis which leads to the conceptual and empirical problems associated with either examining teacher-level perceptions of collective efficacy or school-level perceptions of teacher efficacy. To avoid these problems, we employed hierarchical linear modeling (HLM) (Bryk & Raudenbush, 1992). HLM avoids the aggregation bias, misestimated standard errors, and heterogeneity of
regression problems that sometimes compromise the results of ordinary least squares regression analyses of data in which (typically) one or more individual-level characteristics are aggregated to the group level. 5.7. Unconditional model Since we were interested in predicting variation between schools in teacher efficacy with schoollevel characteristics, we began our analysis with an unconditional multilevel model of the variation in teacher efficacy. This analysis allowed us to determine that there was statistically significant variation in teacher efficacy among the schools we sampled. Therefore, we proceeded with our multilevel modeling to explain this variation as a function of school contextual features and collective efficacy. 5.8. Predicting variation among schools in teacher efficacy The multilevel modeling approach employed to investigate the between-school variation in teacher efficacy was the means-as-outcomes analysis (Bryk & Raudenbush, 1992). Using this approach we were able to test several school contextual features and collective efficacy as predictors of teacher efficacy. At the teacher-level, variation within schools in teacher efficacy was modeled as follows: ð1Þ Teacher level: YðTEACHER
EFFICACYÞij
¼ B0j þ rij :
Since teachers were anonymous, no teacher-level variables were included in the level-1 model, hence level-1 variation in teacher efficacy is estimated by rij : Since we modeled variation among rather than within schools, rij was constant throughout our analyses. At the school-level, we first separately tested the effects of each of our school-level contextual controls (mean SES, minority concentration, school size, and mean prior achievement) and collective efficacy. This process allowed us to identify which of these variables was significantly related to variation among schools in teacher efficacy. As an example, the structural equation specifying variation among schools in teacher
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efficacy as a function of mean SES was as follows: ð2Þ School level: B0j ¼ g00 þ g01 WðMeanSESÞj þ m0j : Models of the effects of minority concentration, school size, mean prior achievement, and collective efficacy were analogous. Next, we combined the statistically significant predictors identified in the first five models to produce a parsimonious combined model that explained variation among schools in teacher efficacy. The results of these analyses are reported below.
6. Results The main question in this research concerned the effect of collective efficacy on teacher efficacy. We decided that to address this question, we should control for school contextual factors other than collective efficacy that might be related to betweenschool variation in teacher efficacy. Our contextual control variables included mean SES, mean prior mathematics achievement, minority concentration, and school size. Descriptive statistics for these variables and others relevant to the study are reported in Table 1. Notably, there is considerable variation across teachers in teacher efficacy with scores ranging from 1.40 (low teacher efficacy) to 6.0 (high teacher efficacy). The extent to which this variability in teacher efficacy is systematically associated with school membership was the focus of the multilevel analyses that followed. Also, over half the students in the schools surveyed were minority and nearly two-thirds received a free or reduced price lunch while the average normal curve equivalent score in mathematics across the 47 sampled schools was slightly below the 44th percentile. Thus, the urban schools sampled for this research served a large number of minority and poor students with slightly below average achievement. Correlations among select school-level variables are reported in Table 2. 6.1. Psychometric analysis and construction of efficacy scales Of the 452 sampled teachers, 438 (approximately 97%) returned usable answers to the
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teacher efficacy questionnaire. Teacher responses to the teacher efficacy scale items were submitted to a principal axis factor analysis. One factor was extracted with an eigenvalue of 2.106 explaining 42.12% of the variance. Factor loadings ranged from 0.62 to 0.70. The alpha coefficient of reliability for the teacher efficacy scale was 0.79. This is consistent with the reliability of scores on the scale in previous research (e.g., 0.77 in Hoy & Woolfolk, 1993; 0.81 in Woolfolk, Rosoff, & Hoy, 1990; 0.82 in Woolfolk & Hoy, 1990). The teacher efficacy score for each teacher was constructed as the mean of the teacher’s responses to all items in the teacher efficacy scale. The collective efficacy score for each school was obtained from a process that began by calculating a mean score for each of the collective efficacy scale items for each school. This produced 21 mean item scores for each school. At the school level, these 21 items were submitted to a principal axis factor analysis. A single factor was extracted with an eigenvalue of 12.00 that explained 57.13% of the variance. Factor loadings ranged from 0.61 to 0.93, with all but five items loading above 0.70. The alpha coefficient of reliability for scores on the collective efficacy scale was 0.96. Next, within each school the 21 mean scores were averaged to yield an overall collective efficacy score for each school.2
6.2. Multilevel results An unconditional analysis (one-way ANOVA with random effects) indicated significant variation among schools in teacher efficacy. Specifically, variation among the school means for teacher efficacy (Var (B0j )) was 0.04758 (w2=67.33, df=46, po0:05). This finding confirmed that teacher efficacy does indeed vary systematically with school characteristics. Given that teacher efficacy varied significantly among schools, we continued our analysis by building a school-level model to explain that variation. 2 Interested readers are directed to a validation study for a 12 item short form of the collective efficacy scale by Goddard (in press) that may be used in lieu of the 21 item scale employed for this research.
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Table 1 Descriptive statistics for teacher and school variablesa Mean Teacher level (n ¼ 452): Teacher efficacyb School level (n ¼ 47): Collective efficacyb School size Faculty size Faculty members surveyed Proportion of students receiving a free or reduced-price lunch Proportion of minority students Prior mathematics achievement
Std dev.
Min.
Max.
4.66
0.77
1.40
6.00
4.31 401.40 21.24 9.62 0.62 0.56 43.86
0.48 107.26 5.51 2.58 0.20 0.28 10.17
3.43 229 13 5 0.10 0.08 29.21
5.30 710 37 15 0.89 1.00 73.40
a
Variables used in multilevel analyses were subsequently standardized to a mean of zero and standard deviation of one. Teacher efficacy and collective efficacy were measured using Likert-type scales with items scaled from 1 (strongly disagree) to 6 (strongly agree). b
Table 2 Correlations among school-level variables (n ¼ 47) Variable
Collective efficacy
School size
SES
Minority concentrn.
Prior math achieve.
Collective efficacy School size Proportion low SES Minority concentration Prior mathematics achievement
F 0.279 0.726a 0.479a 0.731a
F 0.188 0.058 0.060
F 0.521a 0.867a
F 0.550a
F
a
po0.01.
We began by first separately testing each of the school-level contextual variables and collective efficacy as predictors of between-school variation in teacher efficacy. To facilitate comparison of their effect sizes, all school-level variables were standardized to a mean of zero and a standard deviation of one. These five analyses identified mean SES, mean prior mathematics achievement, and collective efficacy as significant predictors of variation among schools in teacher efficacy while school size and minority concentration were statistically unrelated to teacher efficacy. In the final step of the multilevel examination we considered the effects of the three statistically significant predictors simultaneously. The findings of this analysis (Combined Model) confirmed the main hypothesis of the study. The results indicated that a one standard deviation increase in collective
efficacy was associated with a 0.248 standard deviation increase in teacher efficacy. Importantly, when considered together, only collective efficacy was a significant predictor of differences between schools in teacher efficacy; neither mean prior achievement nor mean SES were significant predictors of teacher efficacy in the combined model. Thus, variation in collective efficacy explained variance in teacher efficacy above and beyond that accounted for by our school contextual controls. The effect sizes and associated p-values from these analyses are reported in Table 3. Another interesting question that we investigated in our multilevel analyses was the extent to which our various models explained betweenschool variation in teacher efficacy. Table 4 displays the proportion of variance explained by each model with a statistically significant predictor. Notably, mean SES and mean prior
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Table 3 Prediction of variation in teacher efficacy among school means with selected school characteristics (n ¼ 438 teachers in 47 schools) Model 1 Intercept Proportion minority Proportion low SES Number of students Prior math achievement Collective efficacy a b
0.005 0.082
2
3 0.008
0.011
4
5
Combined
0.009
0.020
0.023 F 0.042 F 0.035 0.247a
0.104b 0.045 0.108b 0.191a
po0.01. po0.05.
achievement alone each explain just under 25% of the variation among schools in teacher efficacy. Moreover, after accounting for the effects of mean SES (Model 2) and mean prior achievement (Model 4), in each case the remaining variation among schools in teacher efficacy is statistically non-zero. In other words, neither mean SES nor mean prior achievement explained all of the systematic variation among schools in teacher efficacy. The case is different, however, when assessing the relationship between collective efficacy and teacher efficacy (Model 5). As shown in Table 4, collective efficacy accounts for nearly three-fourths of the variation among schools in teacher efficacy. In addition, when collective efficacy is considered, the remaining variance is not statistically different from zero. In other words, collective efficacy predicts all of the variation in teacher efficacy detected in our sample. The results of the combined model are consistent with those of Models 2, 4, and 5. Namely, when considered with mean SES and mean prior achievement, collective efficacy is the lone statistically significant predictor of variation among schools in teacher efficacy and the model explains all of the between-school variation in teacher efficacy.
7. Discussion A great number of researchers have investigated the correlates of teacher efficacy and the relation-
ship of this important construct to student achievement. Far fewer have considered how school context is related to teacher efficacy. The findings of this study indicate that teacher efficacy does vary systematically among schools, at least in the urban elementary schools we sampled. Hence, organizations appear to play a role in teachers’ reported levels of efficacy. Next, our results provide initial evidence that the variation between schools in teacher efficacy may be explained by the collective efficacy of a school. Teacher efficacy was higher in the schools where collective efficacy was higher. Indeed, after accounting for the effects of mean prior achievement and mean SES, a one standard deviation increase in collective efficacy was associated with a quarter standard deviation increase in teacher efficacy. Moreover, collective efficacy explained all of the variation among schools in teacher efficacy in the schools we sampled. When considered together with the effects of school contextual features such as mean SES and mean prior achievement, collective efficacy was the only significant predictor of teacher efficacy differences among schools. It is not surprising that there exists a significant positive relationship between teacher and collective efficacy. To be sure, teachers ‘‘are not social isolates immune to the influence of those around them’’ (Bandura 1997, p. 469). As postulated by social cognitive theory, social influence shapes selfefficacy. Where teachers tend to think highly of the collective capability of the faculty, they may sense an expectation for successful teaching and hence
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Table 4 Proportion of variation in teacher efficacy among schools explained and remaining for models reported in Table 3 (n ¼ 438 teachers in 47 schools) Model
a,b
Proportion of variation explained Between-school variation remaininga
1
2
3
4
5
Combined
F F
0.247 0.03581c
F F
0.231 0.03657d
0.735 0.01263e
0.823 0.00815f
a
Proportion of variation in teacher efficacy explained and remaining reported only for models with statistically significant predictors. Proportion calculated as the reduction in variation among schools in teacher efficacy found in the unconditional multilevel analysis (0.04758, Chi-square=67.33, df=46, po0:05). c Chi-square=62.30, df=45, po0:05: d Chi-square=62.44, df=45, po0:05: e Chi-square=50.48, df=45, p ¼ 0:266: f Chi-square=49.13, df=43, p ¼ 0:241: b
work to be successful themselves. Conversely, where collective efficacy is low, it is less likely that teachers will be pressed by their colleagues to persist in the face of failure or that they will change their teaching when students do not learn. A minor limitation of this study was that teachers were guaranteed complete anonymity in the survey process. For this reason, no teacher demographic data were collected. Other researchers may wish to consider the possibility of obtaining teacher demographic data to examine the relative effects of these variables on teacher efficacy in a multilevel analysis that also includes collective efficacy at the school level. In addition, although we achieved statistical control by sampling only one type of school (elementary) within one urban school district, this also means that the schools we sampled are probably more homogenous in terms of SES, minority concentration, and student achievement than would be found in the general population. Therefore, we are not convinced by the results reported here that collective efficacy will explain all of the betweenschool variation in teacher efficacy in all types of schools. Future researchers might wish to examine the relationship between teacher and collective efficacy in other settings (e.g., non-urban secondary schools) to determine whether the results extend to demographically dissimilar populations.
Our results do have import, however, for the great many teachers and students who work and learn in urban school districts like the one we sampled. Indeed, our findings suggest that in this urban district, collective perceptions of faculty capability were predictive of the differences among schools in the perceptions that teachers held of their own self-capability. Such a result helps to show that collective efficacy is an important school contextual feature that is systematically related to teacher efficacy, adding to this line of teacher efficacy research. Moreover, building collective efficacy in schools may offer a new possibility for raising teacher efficacy and perhaps at least lessening the declines in teacher efficacy that are sometimes experienced by teachers when they leave their preservice programs (Chester & Beaudin, 1996; Tschannen-Moran, Woolfolk Hoy, & Hoy, 1998). Future researchers might address whether declines in teacher efficacy are attenuated for teachers who join schools with relatively high collective efficacy. The results are also important for the field of organizational studies as they suggest one way in which organizational characteristics may influence member performance. From the perspective of organizational improvement, Bandura (1997) has suggested that a strong leader who can ‘‘unite the community for common cause’’ (p. 501) and who empowers the faculty may be able to increase the collective efficacy of a school. Strong leadership
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and empowerment may indeed be aspects of organizational life that can build collective efficacy. Whether changes in collective efficacy lead to changes in teacher efficacy is, however, an unanswered question. Future researchers might wish to examine this question of causality. One way to do this is to study schools during a period of intense change (Bandura, 1997) to determine whether changes in collective efficacy do cause changes in teacher efficacy. One possibility that is consistent with the correlational evidence in this study is that teacher and collective efficacy have a reciprocal relationshipFa change in one may lead to changes in the other. Such a finding would have import regarding the manner in which teachers and schools influence one another and consequently the students they serve. Hoy & Woolfolk (1993), for example, found that ‘‘schools promoted personal teaching efficacy when teachers perceived that their colleagues (a) set high but achievable goals, (b) create an orderly and serious learning environment, and (c) respect academic excellence’’ (p. 365). They also found that teacher efficacy was higher when school principals are perceived as having influence with their superiors. Such findings suggest that features of school organization and leadership can serve to develop teacher efficacy. At a minimum, we believe the findings of this study illuminate possibilities for building teacher efficacy through school improvement and avenues for a great deal of future research that can further our understanding of both teacher and collective efficacy.
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