The influence of teachers’ self-efficacy on perceptions: Perceived teacher competence and respect and student effort and achievement

Teaching and Teacher Education 64 (2017) 260e269

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The influence of teachers’ self-efficacy on perceptions: Perceived teacher competence and respect and student effort and achievement Angela D. Miller a, *, Erin M. Ramirez a, 1, Tamera B. Murdock b a b

George Mason University, United States University of Missouri-Kansas City, United States

h i g h l i g h t s
Teacher and student perceptions are crucial to understanding classroom processes.
Teacher self-reported efficacy is related to student perceptions of teacher traits.
Teacher efficacy interacts with class difficulty to predict teachers' perceptions.
Higher efficacy teachers rate remedial students as increasing in effort.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 16 August 2016 Received in revised form 20 January 2017 Accepted 9 February 2017

In the current study the authors examine how teachers' self-reported level of self-efficacy influences students' perceptions of two aspects of the instructional environment, perceived teaching competence and perceived teacher respect. The relationship of teacher self-efficacy to teachers' perceptions of their students' achievement and effort is also considered. Data were collected at two time points from 51 teachers and 427 students in high school mathematics and science classrooms. A series of multi-level models found that teaching self-efficacy and course level were significantly associated with students' perceived teacher competence and perceived teacher respect as well as teachers’ ratings of student characteristics. © 2017 Elsevier Ltd. All rights reserved.

Keywords: Self-efficacy Motivation Perceptions Multi-level model

Teacher sense of efficacy is a critical component to successful classrooms and ranks as a significant teacher characteristic associated with instructional quality and student achievement (Guo, Connor, Yang, Roehrig, & Morrison, 2012; Tucker et al., 2005). Accordingly, it is one of the most studied aspects of the classroom context. Teacher self-efficacy has been shown to positively affect teachers' beliefs about teaching and behaviors (Cho & Shim, 2013; Skaalvik & Skaalvik, 2007; Tschannen-Moran & Woolfok-Hoy, 2001); thereby influencing the classroom instruction and ultimately affecting student outcomes (Zee & Koomen, 2016). More specifically, high teacher self-efficacy has been found to be related to higher end of the year goals for students, positive teacher practices and policies used in the classroom, and innovative

* Corresponding author. George Mason University, West Building 2007, 4400 University Drive MS 6D2, Fairfax, VA 22030, United States. E-mail address: [email protected] (A.D. Miller). 1 Present Address: California State University-Monterey Bay. http://dx.doi.org/10.1016/j.tate.2017.02.008 0742-051X/© 2017 Elsevier Ltd. All rights reserved.

classroom methods (Caprara, Barbaranelli, Steca, & Malone, 2006; Evers, Brouwers, & Tomic, 2002). The first aim of this paper is to better understand how variations in teachers' reported level of self-efficacy influence students' perceptions of two aspects of the instructional environment, perceived teaching competence, and perceived respect. Teacher self-efficacy has an additional potential impact on classrooms as the lens through which teachers view their students. Teachers' views of student motivation will influence the expectations that they have for their students and influence a teacher's interactions with her students. The second goal of the present study is therefore to examine teachers' self-efficacy in relationship to their perceptions of their students' achievement and effort.

1. Theoretical framework The primary conceptual framework of this study is Bandura's social cognitive theory (1986) which defines teacher self-efficacy as

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a teacher's belief to execute a specific task and achieve a specific outcome (Tschannen-Moran, Woolfolk-Hoy, & Hoy, 1998). Furthermore, social cognitive theory also encompasses one of the major theories of student achievement motivation, achievement goal theory (Ames & Archer, 1988; Dweck, 1986) from which we also draw for this study. Bandura’s (1986) social cognitive theory explains one's actions through triadic reciprocal determinism, or the idea that personal factors (e.g., cognitive, affective), behavior, and the environment influence one another in a shared manner. According to social cognitive theory, what people think, believe, and feel, impacts how they behave, and these behaviors both influence and are influenced by an individual's personal factors and the environment. In the classroom learning environment, it is these reciprocal interactions that are key to understanding the complex relationship between teacher and students. Achievement goal theory which posits that goals are regulators of behavior (Ames, 1992; Dweck, 1986), considers both student personal factors (e.g., achievement goals) and the environment (e.g., perceived goal structures) in a social cognitive explanation of student motivation. These two sets of concepts within achievement goal theory, classroom goal structures and personal goal orientations, are defined in terms of mastery (e.g., increasing ability) and performance (e.g., demonstrating ability) goals. Personal goal orientations are preferred or adopted behavior patterns used by students in learning situations, whereas classroom goal structures are those structures within the classroom that make different goals salient to the student (Ames, 1992; Ames & Archer, 1988). Achievement goal structure measures can be assessed via students' perceptions of teachers' instructional behaviors conveying the reciprocal determinism of social cognitive theory by examining these perceptions in relationship to behavior outcomes. For example, perceived mastery goals have been found to predict achievement (Roeser & Eccles, 1998), help-seeking (Ryan, Gheen, & Midgley, 1998), and cognitive strategy use (Anderman & Young, 1994). Perceived performance goals have been linked to academic cheating (Anderman & Midgley, 2004) and self-handicapping (Urdan, 2004). This emphasis on perceptions of the classroom environment in making goals more salient for students reinforces the importance of the teacher and teachers’ beliefs and behaviors in the learning process. Consequently, in the classroom environment there are many facets of social cognitive theory at work. Teachers' self-efficacy beliefs influence their behaviors; students' perceptions of these behaviors will in turn influence their behaviors according to social cognitive theory. Moreover, teachers’ views of their own students may influence and be influenced by their personal beliefs which also contributes to the learning environment. 1.1. Teacher self-efficacy and teacher behaviors Teacher self-efficacy has been associated with instructional quality and student support (Guo, Dynia, Pelatti, & Justice, 2014; Holzberger, Philipp, & Kunter, 2013). For example, teachers with higher self-efficacy beliefs are more likely to develop challenging lessons, and teach in a variety of ways to promote student learning (Deemer, 2004; Tschannen-Moran et al., 1998). Teaching selfefficacy beliefs also alter how much effort a teacher puts forth, how long they will persevere when confronting obstacles, and how resilient they are in the face of challenges (Pajares, 1996; Tschannen-Moran et al., 1998; Woolfolk-Hoy & Burke-Spero, 2005). Additionally, teachers with high self-efficacy beliefs are more likely to: (a) implement curriculum innovations, (b) use classroom management and instructional methods that encourage student autonomy, (c) manage classroom problems effectively, (d) keep students on task, and (e) have fruitful collaborative relationships with colleagues and parents that contribute to sustained

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work satisfaction and higher teacher retention (Betoret, 2006; Caprara et al., 2006; Chan, 2006). Further, increased levels of teaching self-efficacy have been associated with more mastery-oriented approaches to instruction and higher expectations for students (Cho & Shim, 2013; Midgley, Anderman, & Hicks, 1995; Wolters & Daugherty, 2007). More specifically, Deemer (2004) found a significant positive influence of teacher self-efficacy on mastery instructional practices; suggesting that teachers with more confidence in their teaching create classrooms that focus on student learning and effort. Most importantly, this relationship between teacher self-efficacy and classroom behaviors means that teachers with higher sense of efficacy provide more effective classroom instruction resulting in higher student motivation and achievement. Teachers' self-efficacy has also been shown to predict the quality of the relationships teachers have with their students and the type of classroom environment they provide; both of which can influence student outcomes. Teachers with higher self-reported selfefficacy are more positive and responsive to students (Gibson & Dembo, 1984) and promote positive classroom environments as measured by student perceptions of instructional behaviors (Holzberger, Philipp, & Kunter, 2014). The provision of emotional support can influence students' behaviors, leading to a better learning environment for all (Bru, Stephens, & Torsheim, 2002; Sakiz, Pape, & Woolfolk-Hoy, 2012). Studies have shown that classroom practices promoting warm teacher-student relationships have been associated with positive student outcomes (Connor, Son, Hindman, & Morrison, 2005; Hamre & Pianta, 2005). In particular, students' perceptions of their teachers' warmth, responsiveness, and sensitivity predicted gains in children's early language and literacy skills (Connor et al., 2005; Pianta, La Paro, Payne, Cox, & Bradley, 2002). Thus, teacher self-efficacy impacts the type of learning environment a teacher provides which influences student achievement. 1.1.1. Student perceptions Although prior literature has linked teacher self-efficacy to both teachers' behaviors and their relationships with students which in turn influence students' behaviors and achievement, little has been examined about the effects of teachers' efficacy from the perspective of the student. Delineating this link is important to understanding how teachers' self-assessment influence students’ experience of the classroom. The current study examines the relationship between teacher self-efficacy and student perceptions of competence and respect. Given the documented associations between higher teacher self-efficacy and more effective instructional and relationship-building behaviors, we anticipate that teachers with higher self-efficacy will be identified by students as more competent and more respectful. Perceived teacher respect, although rarely directly investigated is frequently included within a broader definition of pedagogical caring. This includes a teacher's social support for students evident through democratic interactions, recognizing individual differences in the context of student expectations, and constructive feedback (Wentzel, 1997). In her study, Wentzel qualitatively examined the students' definitions of caring teachers and concluded that there were both interpersonal and instructional interaction differences between caring and non-caring teachers as defined by students. She found that higher levels of supportive behaviors of teachers resulted in more student effort and greater interest in school. Caring teachers were more democratic, more willing and able to help student learn, and were better models of good teaching while being more fair, honest, and equitable in classroom interactions with students. Respectful environments have also been associated with student engagement and self-regulation strategies (Patrick,

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Ryan, & Kaplan, 2007; Ryan & Patrick, 2001). Respectful classroom environments motivate students to participate in meaningful interactions with classmates and their teacher. Furthermore, beyond the educational psychology motivation literature, students' perceptions of teacher instructional factors has been studied even more extensively. Instructional communications researchers have found that college students identify teacher effectiveness and enthusiasm, opportunity to participate, and teacher competence/knowledge as primary motivators in their classes (Gorham & Christophel, 1992; Teven & Hanson, 2004). In this literature, teacher competence is also defined from the perspective of a student. If a teacher is to be perceived as competent, possessing expertise of a particular subject, then he or she is perceived to know what he or she is talking about (McCroskey, 1992). This research has found that competent teachers can explain complex material, manage classroom behavior, and respond to student questions providing more optimal learning situations for students. Perceived teacher respect and perceived competence are constructs that are key to good pedagogy and should be identifiable and recognized by students. 1.2. Teacher self-efficacy and teachers’ views of students Teachers' perceptions of their students have been shown to influence a teacher's effort and strategy use during instruction (Biddle & Anderson, 1986; Wenglinky, 2000). More directly, it has been found that teachers select their instructional methods based on their perceptions of students' abilities (Snow, 1994; SparksLanger et al., 2004). The perceptions teachers hold about their students influences not only how they teach, but the type of  classroom environment they provide for student learning. Hardre and Sullivan (2009) found that teachers' self-efficacy was significantly positively related to their perceptions of their students' academic motivation. Other studies have examined teachers' perceptions of their special education students' needs for: a) instructional support; b) on-task behavioral support; c) emotional support; and d) peer support (Bruggink, Meijer, Goei, & Koot, 2014; Martin, 2006). Using the 2003 Programme for International Student Assessment (PISA) data, Holzberger et al. (2013) examined German teacher and student ratings of the teacher's instructional quality using three variables: cognitive activation, classroom management, and individual learning support in two different studies. They examined the relationship and predictiveness of teacher self-efficacy on teacher and student ratings of instructional behavior at two time points (i.e., year one and year two). They determined there were significant positive correlations between teachers' self-efficacy beliefs and both the teacher and student ratings of instructional quality at both time points. Further, they found teacher ratings of instructional quality predicted learning support, but not cognitive activation nor classroom management (Holzberger et al., 2013). In a follow-up study, they found that teacher's self-efficacy beliefs were significantly positively correlated with student perceptions on the three instructional behaviors. Using latent regression modeling, the authors found teachers' self-efficacy predicted: 14% of the variance in perceived cognitive activation, 12% of the variance in perceived classroom management, and 8% of the variance perceived quality of the teacher-student relationship (Holzberger et al., 2014). Although these studies contribute to the teacher self-efficacy and student perception literature, most are with special populations or are international studies. Thus, there is generally a paucity of studies including student perception data in relationship to teacher selfefficacy. There is also evidence to suggest that teachers' self-efficacy is correlated to their perceptions about class/type of students they are

teaching. Raudenbush, Rowan, and Cheong (1992) found that the track of student (i.e., academic honors vs. non-honors) significantly contributed to teachers' sense of efficacy; teachers reported higher levels of self-efficacy when teaching higher tracks of students. Moreover, the effect of track was moderated by subject area: for science and mathematics teachers', their sense of efficacy was heavily influenced by teaching honors' level classes; whereas, this relationship was almost nonexistent for social studies and English teachers. Additionally, in this study, teachers reported their perceptions about students' motivation and engagement level. Once the researchers controlled for teacher-rated student engagement, the effects of academic track on teachers' self-efficacy diminished (Raudenbush et al., 1992); thus, teachers’ perceptions of their students' engagement was related to the track of students they were teaching. Although these studies suggest that teachers' views of their students influence their behavior in the classroom, there has been limited empirical research linking teacher self-efficacy to their perceptions of students. However, it appears as though teacher selfefficacy is also a lens through which teachers view their students. Therefore there is not only a direct link between teacher selfefficacy and a teacher's behaviors, but also an indirect relationship through how they perceive their students. The literature suggests that teacher self-efficacy is related to both teacher perceptions of students and students' perceptions of teachers, and both views of the classroom are key to better understanding the complex dynamics of motivation and learning and warrant further investigation. 2. The present study In the present study, student perceptions of teacher competence and teacher respect were examined as outcomes of teachers' selfefficacy in order to better understand how this teacher characteristic impacts student perceptions of these perceived affective and cognitive traits of their teachers. Furthermore, the classroom environment variables of perceived goal structures (i.e., mastery goal structures and performance goal structures) were also examined as dependent variables to determine the discriminant impact of teacher self-efficacy on these student perceived classroom characteristics. We hypothesized that teacher self-efficacy would likely influence students' perceptions of competence and respect, whereas we did not expect teacher self-efficacy to necessarily impact students' perceived goal structures. Although the theoretical literature has tended to find that mastery goal structures are superior to performance goals, classroom studies have found mixed results and the nature of our high stakes culture seems to support performance environments. Therefore, we expected to find teachers of varying self-efficacy levels in classrooms perceived by students as both performance and mastery focused. In all analyses, we controlled for students’ self-efficacy and personal goals and we also considered the type of classroom (i.e., advanced or remedial versus typical) in each analysis. Finally, we also considered the interaction between teacher self-efficacy and the type of class, as previous literature has suggested that teacher self-efficacy is a function of the class level (Raudenbush et al., 1992). Next, we examined the influence of teacher self-efficacy on teachers' perceptions of their students; specifically considering how teacher self-efficacy impacted the teachers' perceptions of change in their students’ effort, achievement, and aptitude. We completed this analysis by examining teacher ratings of these variables at the end of the school year controlling for the same rating at the beginning of the school year. We hypothesized that teacher self-efficacy would influence changes in perceived achievement and effort but not influence perceived aptitude, as

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teachers are likely to view aptitude as something that cannot be influenced greatly by their instructional practices. 3. Methods 3.1. Participants and setting The sample consisted of 427 high school students in 51 mathematics (n ¼ 27) and science classrooms (n ¼ 24) from three schools in a Midwestern semi-urban district. 3.1.1. Students The demographic breakdown of the student sample (n ¼ 427) was: 75.7% Caucasian, 4.7% African-American, 6.4% Hispanic, 4.3% Asian, and 7.6% other. Additionally, the sample consisted of 44.1% male and 55.9% female students. Students ages ranged from 13 to 18 years with a mode of 15 (n ¼ 174). The student sample was representative of each grade level: 37.2% freshmen, 34.6% sophomores, 19.3% juniors, and 8.9% seniors. Further, in response to student's self-reported grades: 34.6% obtained mostly A's, 27.6% attained A's and B's, 14.1% reported mostly B's, 13% received B's and C's, and 10.7% earned C's and lower. 3.1.2. Teachers Of the 51 teachers in the study, 98% were Caucasian, 2% were African American and 66.7% were female and 33.3% were male. Further, of the teachers in the sample: 35.3% held a bachelor's of arts, 62.7% held a master's of arts, and 2% held a doctor of philosophy degree. Teachers had between 1 and 31 years of experience with an average of 11.14 (SD ¼ 8.71). Further breakdown of teachers' years of experience demonstrated that 35.1% had between 1 and 5 years of experience (i.e., novices), 29.8% had between 6 and 14 years of experience (i.e., experienced), and 35.1% had 15e31 years of experience (i.e., experts). In regards to teacher's level of experience in teaching the specific mathematics (n ¼ 27) or science (n ¼ 24) course where data were collected: 8.8% were first year teachers, 10.5% were experienced teachers teaching this particular course for the first time, 31.6% had previous experience with the course but had made significant changes, and 49.1% had previous experience and had made minor changes. 3.2. Procedures Teachers in a large urban-suburban school district in the Midwest were approached in their schools during the scheduled mathematics or science faculty meeting times and informed of the purpose of the study. Teachers consented to allowing researchers to visit one of their class periods twice during the academic year to collect data via paper and pencil surveys. Selection of classes was obtained using a proportionate stratified random method across course levels (e.g., algebra I, geometry) at each school. Only one course was selected for each teacher. Parent consent was obtained prior to the data collection and student assent was completed on the day of the survey. Surveys were concealed in manila envelopes marked only with an assigned ID number that was removed from the outside of the packet by the student after the ID number was transferred to the survey and sealed again in the envelope upon completion. Teachers completed their own survey and rated the students in that class at the same time that the students were completing their surveys. Teacher surveys were also marked only with a class ID and sealed in envelopes by the teacher. Data were collected in the fall (time 1) and spring (time 2) of the academic year. Students reported on either their mathematics (n ¼ 260) or science class (n ¼ 167). No students reported on both

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their science and mathematics class. All students and teachers completed surveys at both time points. All 51 teachers completed the survey at both time points. At time 1 there were 541 students and at time 2 there were 482 students reporting. The current analysis includes only those students who have complete data at both time points (n ¼ 427). 3.3. Measures All student items and teacher self-efficacy items were measured on 5-point Likert scales from “Not at all true” to “Very true.” Internal consistency for each multi-item scale was demonstrated with Cronbach's alpha. Additionally, for classroom level aggregate perception variables and teacher rating variables, multilevel reliabilities (labeled as HLM) were also calculated. Dependent perceptions measures (e.g., teacher competence, teacher respect, and goal structure measures) were all measured at time 2. All predictor variables (e.g., student self-efficacy, personal goal orientations, and teacher self-efficacy) were measured at time 1. Teacher ratings of students were completed at both time 1 and time 2. 3.3.1. Student self-efficacy and personal goal orientations From the Patterns of Adaptive Learning Survey (PALS; Midgley et al., 2000), the student self-efficacy scale consisted of five items (a ¼ 0.85). An example item is, “Even if the math/science work is hard, I can learn it.” The personal mastery goal orientation scale had five items (a ¼ 0.85). One sample item is, “It is important to me that I thoroughly understand my math/science work.” The performance orientation goals scale had nine items (a ¼ 0.92). A sample item is, “One of my goals is to look smart in comparison to other students in my math/science class.” 3.3.2. Perceived goal structures Students' perceptions of classroom goal structures were also measured using the PALS measure (Midgley et al., 2000). The mastery goal structure scale consisted of five items (a ¼ 0.80; HLM ¼ 0.77) and the perceived performance goal structure scale had seven items (a ¼ 0.80; HLM ¼ 0.76). Sample items include “In our math/science class, it's OK to make mistakes as long as you are learning” and “ In our math/science class, getting right answers is very important“ and for each of the goal structure scales. 3.3.3. Perceived teacher respect To assess perceived teacher respect, items from a scale developed by Murdock, Hale, and Weber (2001) were used. The perceived teacher respect scale encompassed five items (a ¼ 0.88; HLM ¼ 0.80). A sample item is, “I feel like I matter in this class.” 3.3.4. Perceived teacher competency Items adapted from the same scale developed by Murdock et al. (2001) were also used to assess perceived teacher competency. The perceived teacher competency measure was comprised of 12 items, and was highly reliable (a ¼ 0.91; HLM ¼ 0.79). One sample item is, “My teacher answers my questions in a way that helps me understand the material.” 3.3.5. Teacher self-efficacy Teacher self-efficacy was measured using the Woolfolk-Hoy and Hoy (1990) adapted 22-item scale based on Gibson and Dembo’s (1984) Teacher Efficacy Scale. The teacher self-efficacy scale was reliable (a ¼ 0.71) and a sample item is, “When a student gets a better grade than he/she usually gets, it is usually because I found better ways of teaching that student.”

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4.2. Predicting student perceptions

3.3.6. Teacher ratings of aptitude, effort and achievement Single item ratings for each construct on a 7-point Likert scale were collected from each teacher who individually rated each student in the selected mathematics or science classroom. Teachers were provided with a table listing all of the students in their class on each line. Three columns were labeled: aptitude, effort, and achievement. Teachers were asked to consider each attribute within the context of their class and rate the student between 1 (very low) to 7 (very high). Multilevel reliabilities were examined for each rating. Achievement has the highest reliability (HLM ¼ 0.86), followed by aptitude (HLM ¼ 0.76) and effort (HLM ¼ 0.68).

Multilevel modeling methods were used to analyze the perception data. This approach is necessary to address the nested structure (e.g., students within classrooms) of the data. All analyses were completed using SAS® software (SAS Institute; Cary, NC). Continuous predictor variable were centered at their grand mean values. Unconditional multilevel models were conducted for each student perception outcome of interest as well as for perceived goal structures. Students' perceptions of goal structures were included to contrast as environment variables, in addition to the perceived teacher characteristics. Whereas teachers' self-efficacy has been linked to teachers reported use of instructional practices aligned with a mastery goal structure (Midgley et al., 1995; Wolters & Daugherty, 2007), there has been no examination of students’ perceptions of mastery goal structures in relationship to teacher self-efficacy. This model with no predictors was used to calculate the intraclass correlation coefficient (ICC) using the ratio of between class variance to total variance. For perceived teacher competence, the amount of variance in the dependent variable determined to be between classrooms was 22% and for perceived teacher respect the ICC was also 22%; indicating that a significant amount of variance in the dependent variables is present between classrooms rather than perceptions being only a within class difference. The ICCs for perceived mastery and performance goal structures were 21% and 10% respectively. The next set of analyses were for the purpose of evaluating the predictive power of student and teacher characteristics and motivational beliefs in explaining student perceptions of their teachers’ competence and respect. Multilevel models in which student-level motivational variables (i.e., personal mastery goals, personal performance goals, and self-efficacy) were entered at level one and teacher-level variables (i.e., self-efficacy and class level) were entered at level two and were examined for each of the outcome variables of perceived teacher competence and perceived teacher respect. All continuous predictor variables were grand mean centered. At the teacher level, two dummy coded predictors represented whether the class was a special curriculum (0 ¼ regular curriculum and 1 ¼ advanced or remedial curriculum). This multilevel model was tested for each of the four teacher perception variable (i.e., perceived respect, perceived competence, perceived mastery goal structure, perceived performance goal structure) and included nine fixed effects and two random effects:

3.3.7. Class type Each class was identified as remedial, advanced, or typical depending on the course description and departmental listings. Remedial courses included developmental mathematics courses and remediation courses in both mathematics and science for students who had previously failed a required mathematics or science course. Advanced courses included Advanced Placement (AP) and International Baccalaureate (IB) program courses. Typical courses were all general mathematics and science courses.

4. Results 4.1. Descriptives Preliminary analysis including descriptives and unconditional models were examined to investigate classroom level differences in the outcome variables. Overall means and standard deviations as well as correlation coefficients for all student level variables are presented in Table 1. Means for the 51 classrooms ranges from 1.32 to 3.27 for perceived teacher competence and from 1.26 to 3.67 for perceived teacher respect. Mean teacher ratings of student attributes at time 2 were 5.66 (SD ¼ 1.47) for effort, 4.24 (SD ¼ 1.36) for achievement, and 5.46 (SD ¼ 1.27) for aptitude. Of the 51 courses, 13 were advanced, 10 were labeled remedial, and the remaining 30 were typical. The mean for teacher self-reported efficacy was 3.32 with a standard deviation of 0.42. There was no statistical difference in mean self-reported teaching self-efficacy between course levels, F(2, 50) ¼ 0.19, p > 0.05.

Perception of teacherij ¼ g00 þ g01 Teacher Self  Efficacy þ g02 Remedial þ g03 Advanced þg04 Teacher Self  EfficacyRemedial þ g05 Teacher Self  EfficacyAdvanced þg10 Student Mastery Goal þ g20 Student Performance Goal þ g30 Self­Efficacy þ m0j þ rij

Table 1 Descriptive statistics of student level variables. Measure

1

2

3

4

5

6

7

1. 2. 3. 4. 5. 6. 7.

2.82 (0.82) 0.60** 0.23** 0.07 0.23** 0.16** -0.02

2.74 (0.91) 0.34** 0.16** 0.28** 0.25** -0.03

1.52 (0.98) -0.00 0.05 0.07 0.32**

2.89 (0.94) 0.69** 0.69** -0.28**

2.63 (0.83) 0.79** 0.20**

2.46 (0.87) -0.06

1.13 (0.75)

Student Self-Efficacy Student Mastery Goal Student Performance Goal Perceived Teacher Respect Perceived Teacher Competency Perceived Mastery Goal Structure Perceived Performance Goal Structure

Note. *p < 0.05. **p < 0.01.

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Table 2 HLM models of student perception outcomes.

Parameter

Level One (Student) Intercept Mastery Goal Perf. Goal Self-Efficacy Level Two (Class) Teacher Self-Eff. Remedial Level Advanced Level Variance Est. ICC BIC

Teacher Competence

Teacher Respect

Model 1

Model 1

Model 2

Model 2

Mastery Goal Structure

Perf. Goal Structure

Model 1

Model 1

Model 2

Model 2

Parameter Estimate (SE)

Parameter Estimate (SE)

Parameter Estimate (SE)

Parameter Estimate (SE)

2.38 (0.11)** 0.18 (0.05)** 0.03 (0.04) 0.11 (0.05)*

2.46 (0.11)** 0.18 (0.05)** 0.04 (0.04) 0.12 (0.05)*

2.58 (0.13)** 0.18 (0.06)** 0.07 (0.05) 0.03 (0.07)

2.65 (0.14)** 0.17 (0.06)** 0.08 (0.05) 0.02 (0.06)

2.22 (0.11)** 0.19 (0.05)** 0.01 (0.04) 0.03 (0.06)

1.60 (0.10)** 0.11 (0.04)* 0.28 (0.04)** 0.01 (0.05)

e

0.37 (0.14)** 0.54 (0.22)* 0.20 (0.13)

e

0.44 (0.18)** 0.57 (0.27)* 0.14 (0.16)

0.21 997.450

0.17 990.98

0.22 1123.00

0.18 1117.19

2.32 (0.12)** 0.19 (0.05)** 0.01 (0.04) 0.04 (0.06)

0.13 (0.11) 0.10 (0.17) 0.13 (0.10)

0.29 (0.15) 0.47 (0.25) 0.29 (0.14)* 0.21 1051.10

0.18 1047.27

1.62 (0.10)** 0.10 (0.05)* 0.28 (0.04)** 0.01 (0.05)

0.08 930.48

0.08 933.43

Note: Perf. ¼ Performance. Eff. ¼ Efficacy. Est. ¼ Estimates. ICC. ¼ IntraClass Correlation. BIC. ¼ Bayesian Criterion. (SE) ¼ Standard Error. * p < 0.05. **p < 0.01.

In Model 1, the student level variables of self-efficacy, personal mastery goals, and personal performance goals were entered at level one, accounting only for a small portion of the between class variance in perceived performance goal structure. There was no change in the ICCs for perceived respect and perceived mastery goals which remained at 22% and 21% respectively. The ICC for perceived competence only dropped from 22% to 21% and

outcome. Teachers rated these attributes at both time 1 and time 2. In our analyses, the teacher's rating of student from time 2 was the dependent variable and their corresponding rating from time 1 was used as control variable in order to assess change in rating. The multilevel model that was tested for each of the three teacher ratings variable (i.e., achievement, effort, aptitude) included seven fixed effects and two random effects:

Teacher Ratingij ¼ g00 þ g01 Teacher Self  Efficacy þ g02 Remedial þ g03 Advanced þg04 Teacher Self  EfficacyRemedial þ g05 Teacher Self  EfficacyAdvanced þg10 Teacher Rating Time 1 þ u0j þ rij

perceived performance goal structure dropped from 10% to 8%. The majority of between class differences in these dependent variables remains to be explained. In Model 2, teacher characteristics including teacher selfefficacy and class level dummy variables were entered as well as the interaction terms. Teacher self-efficacy was found to be a significant predictor of between class variability for both perceived teacher competence and perceived teacher caring. Both perceived teacher competence and perceived respect were lower in remedial classes. Teacher self-efficacy and advanced course level were not significant predictors for either of the perceived goal structures. Perceived mastery goal structure was lower in advanced classrooms. The interaction terms between course level and teacher self-efficacy were tested, but were non-significant in all four models and were subsequently dropped from the model. The between class variance dropped for all of the models except perceived performance goal structure which remained at 8%. Perceived respect and perceived mastery goal structures both dropped to 18% from 22% and 21% respectively. The ICC for perceived competence dropped from 21% to 17%. Coefficients and ICCs for Models 1 and 2 for each of the dependent variables are in Table 2. 4.3. Predicting teacher perceptions Again, multilevel regression analyses were used to examine teachers' perceptions of students. As with student perception variables, null models were examined for teacher ratings of effort, achievement, and aptitude. Aptitude was included as a comparison

We hypothesized that any improvements in effort and achievement would more likely be viewed as related to teacher's own self-efficacy beliefs; whereas aptitude is generally seen as a more fixed attribute of a student and not necessarily subject to being changed over the course of an academic year, and therefore not likely to be related to the teacher's own self beliefs. In each of the null models, significant between teacher variance was found at time 2. However, the ICC of primary interest in this analysis is the amount of variance between teachers when controlling for time 1 ratings or rather the variability in amount of change in effort, achievement, and aptitude. The ICC in achievement, controlling for time 1 rating was quite high at 56%; whereas the ICCs for effort and aptitude were much lower, 17% and 15% respectively (Table 3). Over time teachers did change their perceptions of all three outcome variables. This variability over time was concentrated primarily within classrooms for effort and aptitude, however for achievement the variability was higher between teachers as evidenced by the ICC greater than 50%, likely due to ability grouping and class levels. In the next model, teacher self-efficacy and level of class was entered in the model as well as the interaction terms. The ICCs for each model dropped as expected. Achievement dropped from 56% to 49%, effort dropped from 15% to 6%, and aptitude dropped from 17% to 12%. Teacher self-efficacy was not a significant predictor for any of the three teacher rating outcomes. However, course level was significant for teacher rated effort and aptitude. Remedial courses resulted in lower ratings of both effort and aptitude. In advanced courses, teachers rated effort higher and surprisingly

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Table 3 HLM models of teacher perceptions of students. Achievement Parameter

Level One (Student) Intercept Time 1 Control Level Two (Classroom) Teacher Self-Efficacy (TSE) Remedial Level Advanced Level TSE * Remedial Level Variance Estimates IntraClass Correlation (ICC) Bayesian Criterion (BIC)

Model 1

Effort Model 2

Model 1

Aptitude Model 2

Model 1

Model 2

Parameter Estimate (SE)

Parameter Estimate (SE)

Parameter Estimate (SE)

4.13 (0.15)** 0.66 (0.04)**

4.25 (0.18)** 0.66 (0.04)**

5.23 (0.09)** 0.65 (0.04)**

5.18 (0.10)** 0.64 (0.04)**

5.21 (0.08)** 0.71 (0.04)**

e

0.21 (0.37) 8.88 (3.12)** 0.57 (0.33) 2.64 (0.88)**

e

0.04 (0.19) 8.70 (1.78)** 0.43 (0.17)* 2.44 (0.51)**

0.56 1239.09

0.49 1225.03

0.15 1453.72

0.06 1429.19

5.34 (0.09)* 0.74 (0.04)** 0.02 (0.19) 6.22 (1.70)* 0.35 (0.16)* 0.73 (0.04)**

0.17 1263.44

0.12 1245.73

Note: (SE) ¼ Standard Error. TSE ¼ Teacher Self-Efficacy. * p < 0.05. **p < 0.01.

aptitude lower as compared to teacher ratings in typical classrooms. The interaction between teacher self-efficacy and remedial course level was significant for all three teacher ratings. In each case, as teacher self-efficacy increases, teachers’ ratings of achievement, effort, and aptitude increase in remedial classrooms. The coefficients for the interaction terms indicate that ratings in both effort and achievement are over 1 standard deviation, whereas the increase for aptitude is less than 0.5 standard deviations. The interaction term between teacher self-efficacy and advanced course was non-significant in all three models and was dropped from the model. Coefficients and ICCs for Models 1 and 2 for each of the dependent variables are in Table 3. 5. Discussion Perceptions are important. Student perceptions about their teachers influence their in class decisions about how to interact and engage in learning (Bru et al., 2002; Gorham & Christophel, 1992). Teachers' perceptions about their students influence the judgements that they make about students and impact their approaches  & Sullivan, 2009; Martin, to teaching (Cho & Shim, 2013; Hardre 2006). Teacher self-efficacy has been suggested in previous studies as both an antecedent and a consequence of instructional practice (Holzberger et al., 2013; Wolters & Daugherty, 2007). The current study contributes to this line of investigation with findings that both the context of learning, as represented by course level and the teachers' self-efficacy beliefs, influence the perceptions that teachers have of their students and explain variance in students' perceptions of their teacher's competence and respect. After controlling for students' self-efficacy, personal mastery goals, and personal performance goals in a multi-level model, increased teaching self-efficacy was significantly associated with student perceived teacher competence and perceived respect. Results suggest that teachers' sense of efficacy for teaching influences students' perceptions, either because of the confidence they project, or because teachers' sense of efficacy to some extent is a reflection of the students in the classroom. Both lines of reasoning are congruent with Bandura's (1986) assertion of contextual influences on efficacy beliefs. Furthermore, the findings of this study align with Raudenbush et al. (1992) study in which they found 44 percent of the total variance in high school teachers' self-efficacy was attributed to intra-teacher variation; most often influenced by the students within a classroom, and in particular the academic difficulty level of the course. Prior research has suggested that teachers' beliefs about themselves influence both their teaching and the quality of their

interactions with students (Holzberger et al., 2014) and it is these interactions upon which the perceptions and judgments of students are based. Our findings indicate that teacher self-efficacy plays a role in students' perceptions of teacher competence and teacher respect, but not in students' perceptions of classroom goal structures. Teachers with higher self-efficacy project this confidence through their actions and interactions with students in the classroom. When students observe teachers confidence with difficult subjects such as science and mathematics, this provides them with a vicarious experience and could in turn also impact their own self-efficacy, and likely will impact their engagement and achievement in these courses. These findings also align with Bandura's assertions about the sources of self-efficacy (i.e., mastery experiences, vicarious experiences, social persuasion, physiological state; 1977). Indeed students with higher levels of self-efficacy were more likely to rate their teacher higher in competence which could be representative of this feedback loop. Teacher self-efficacy was not related to student perceptions goal structures, this is perhaps indicative of the current assessment climate. Theoretically, one might expect that higher efficacy teachers would be more focused on student learning as compared to performance and students should perceive a stronger focus on mastery goals with higher self-efficacy teachers; however, the increased focus on testing in K-12 schools, and attempts to tie teacher quality to test scores likely obscures any systematic differences in teacher self-efficacy between performance and mastery goal structure. Additionally, student self-efficacy was not related to perceptions of teacher respect. Theoretically, this pattern is also in line with Bandura's (1986) social cognitive theory where one would expect the environment, the behavior, and the individual to all influence one another. Therefore, it makes sense that a self-efficacy belief would be related to a rating of competence in another individual and not related to a rating of respect; however empirical evidence is limited to this study and more research is needed. Of interest, is the statistically significant lower ratings of teachers of remedial courses by their students; these coefficients are comparable to the impact of teacher self-efficacy on student perceptions. Prior research has indicated that inter-rater reliability of these constructs at the classroom level is essential when using these variables as classroom aggregates in multilevel models (Miller & Murdock, 2007). Even though aggregate ratings are not used in the current study but instead these perceptions are outcome variables, it is important to recognize that there is a high level of consistency among students rating the same teacher on these constructs. Reliabilities at the classroom level for all student

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perception constructs in the current study are greater than 0.75. Overall, students in remedial courses perceived lower teacher competence and lower levels of teacher respect as compared to students in standard courses. Conversely, students in advanced classes perceived no significant differences in teacher competence or respect as compared to the perceptions of students in standard courses. Perhaps this is related to findings in teachers' perceptions of their students, where teachers of students in remedial courses consistently rated these students as lower in achievement and effort; similar to teacher ratings of lower track students as having less engagement, as found in Raudenbush et al., 1992 study. It is likely that these struggling students are a greater challenge to the teacher and more taxing in terms of instructional methods, and as a results students could perceive the teacher's struggles as evidence of less competence and/or lower respect. Additional research, perhaps of a qualitative nature would be informative to better understand what specific teacher interactions or behaviors students are considering when responding to teacher perception items. When teachers perceive their students as lower achieving, perhaps they see a greater challenge and question their ability to reach the optimal student achievement outcomes that they may believe are easier to achieve with more academically talented students. Although teacher self-efficacy did not have a significant influence on the change in teacher ratings of effort, achievement, and aptitude across the academic year, the academic level of the course did influence these ratings. Teachers rated these students as decreasing in all three constructs across the academic year for students in courses considered to be at a remedial level. In achievement the average rating was 4.25 on the 7-point Likert scale, however for students in remedial courses this rating is 8.88 points lower (or 4.63) which is an average decrease in achievement. This pattern is repeated with teacher ratings of effort (3.52) and to a lessor extreme with aptitude (-0.88). In contrast, when rating the students in more advanced courses, teachers did not assess a greater positive growth for these students. Students in advanced courses were not significantly different in achievement from ratings of students in standard courses. There was a small but statistically significant positive change in effort (0.43) in advanced courses and a small decrease in aptitude (-0.35) for these students. Essentially teachers' ratings of advanced students change very little across the academic year, whereas ratings of remedial students decreased substantially across the year. There were no demographic or teacher self-efficacy differences across levels of courses, including gender, years of teaching experience, experience teaching the specific level course, or in degree area or level. Most interesting is the finding that in remedial classes, teachers with higher self-efficacy beliefs actually rated students in these classes as increasing in achievement and effort by a significant value and even a small increase in aptitude. The larger increases in achievement and effort are likely a reflection of the teachers’ beliefs that they can be instructionally effective; these constructs should be the most influenced by a teacher whereas aptitude would be viewed as a more fixed trait and less effected by any teacher belief or behavior. 5.1. Limitations and future directions Because it has already been established that high self-efficacy teachers behave differently than those with lower-efficacy (e.g., Caprara et al., 2006; Evers et al., 2002; Guo et al., 2012), we presume that the relationships we found in this study between teachers' self-efficacy and students' perceptions of their teachers' respect and competence were a function of teachers' classroom behaviors. However, teachers’ actual behaviors were not measured

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in this study; a future investigation linking teacher self-beliefs, teacher behaviors, and student perceptions would provide a more thorough way to test the mechanism by which teacher self-efficacy impacts the students' classroom perceptions. Furthermore, recall that teacher competence and perceived respect were lower in remedial classes where students presumably find school more difficult than in other course tracks. Given that our study was limited to mathematics and science courses which are typically perceived as more difficult subjects, future investigations of the relations between teacher self-efficacy and student perceptions might also examine the moderating role of subject area. Although the finding that teacher self-efficacy influenced student evaluations in remedial classrooms only was interesting, a lack of better longitudinal information and a larger sample of remedial classrooms makes it difficult to clearly define what contributed to this result. Did teacher self-efficacy relate to perceived student ratings because of pedagogical differences that spurred differences in student behavior? Or were lower efficacy teachers simply apt to judge students more harshly? Future investigations of the role of teacher self-efficacy within remedial classrooms only is a topic worthy of investigation. Finally, our conceptualization of teacher self-efficacy was limited to a unidimensional construct and dealt with teaching generally. Given that teachers' self-efficacy appears to be communicated to students in some real ways such that it affects how they view their instructors, future research in this area might give some thoughtful consideration to the various dimensions of self-efficacy and how they might differentially influence student outcomes. For example, student perceptions of competence might be more strongly related to teachers ‘subject area’ efficacy while their selfefficacy for classroom management and/or relationship development might be a better predictor of perceived respect. Moreover, delineating between personal self-efficacy and outcome expectations might prove useful when examining the influence of teaching self-efficacy on perceptions of students. Theoretically, if one has low outcome expectations, their own self-efficacy might have less of an influence on how they evaluate their students than if these expectations are higher. More research in this area of student and teacher perceptions is needed to both better understand the reciprocal effects between teachers and students as well as the stability of self-efficacy. Klassen, Tze, Betts, and Gordon (2011) have noted deficiencies in the literature in terms of teacher self-efficacy and stability. Additionally, Holzberger et al. (2013) have examined reciprocal relationships between teacher self-efficacy and student perceptions of classroom instructional practices and challenged some of the existing assumptions about teacher self-efficacy; further, they found that teacher self-efficacy beliefs changed over time and in response to classroom interactions. Future research that examines the competence and outcome expectancy components of selfefficacy may better be able to disentangle why class academic level interacts with teacher self-efficacy as this relationship may exist because class level is more strongly related to the outcome expectation component of teacher self-efficacy. As noted previously, qualitative work may be especially helpful in gaining a better understanding of student perceptions of teacher behaviors. In the area of goal theory, qualitative work has already investigated students’ interpretations of mastery goal structure items and found that social aspects of the classroom come into play when students made judgements about their classroom goal structures even though the commonly used scale items are more behavioral in nature (Patrick & Ryan, 2009). Understanding the influence of individual differences in motivational beliefs and characteristics alone does not capture the complex classroom environment. A better understanding of what

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