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School Psychology Review 2018, Volume 47, No. 2, pp. 153–166 DOI: 10.17105/SPR-2017-0070.V47-2

Examining How Proactive Management and Culturally Responsive Teaching Relate to Student Behavior:

Implications for Measurement and Practice

Kristine E. Larson Elise T. Pas

Johns Hopkins University

Catherine P. Bradshaw University of Virginia

Michael S. Rosenberg State University of New York–New Paltz

Norma L. Day-Vines Johns Hopkins University

Abstract. The discipline gap between White students and African American students has increased demand for teacher training in culturally responsive and behavior management practices. Extant research, however, is incon- clusive about how culturally responsive teaching practices relate to student behavior or how to assess using such practices in the classroom. Identifying proactive behavior management and culturally responsive teaching practices that are associated with positive student behavior may inform teacher training and bolster efforts to reduce dispar- ities in behavioral and academic performance. The current study examined the association between student behav- iors and the observed use of and teacher self-reported efficacy in using culturally responsive teaching and proactive behavior management practices. Data were collected from 274 teachers in 18 schools. Structural equation modeling indicated a statistically significant association between observations of culturally responsive teaching and proactive behavior management practices, with observed positive student behaviors in classrooms. Implications for mea- surement and practice are discussed.

Keywords: Positive Behavior Support, School Discipline, Teachers, Prevention, Structural Equation Modeling

Even after decades of research, African American stu- dents continue to be disproportionally represented in exclusion- ary disciplinary actions such as office referrals, suspensions, expulsions, and referrals to the office and school counselors for disruptive behavior (Bryan, Day-Vines, Griffin, & Moore- Thomas, 2012; Gregory, Skiba, & Noguera, 2010; Noltemeyer & Mcloughlin, 2010; Vincent, Sprague, & Tobin, 2012;

Wallace, Goodkind, Wallace, & Bachman, 2008). Disproportionality refers to a phenomenon whereby students, relative to their proportion in the population, experience over- representation or underrepresentation along a specific data point (Bryan et al., 2012). Of particular concern is the overrep- resentation of African American students in discipline data, as research suggests they are three times as likely to get suspended

Author Note. We thank Katrina Debnam, Jessika Bottiani, Sandra Hardee, and Lana Bates for their assistance in developing the Double Check framework. Additionally, we thank Laurie deBettencourt for her feedback on earlier drafts of this paper. Support for this project was provided by grants from the Institute of Education Sciences (R305A150221 and R324A110107) and the Spencer Foundation, awarded to Catherine Bradshaw.

Correspondence regarding this article should be addressed to Kristine E. Larson, Johns Hopkins University, Bloomberg School of Public Health, 415 N. Washington Street, Office 503, Baltimore, MD 21231, e-mail: [email protected]

Copyright 2018 by the National Association of School Psychologists. ISSN 0279-6015, eISSN 2372-966x

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as White students (Losen & Gillespie, 2012) and lose approx- imately twice as many days of instruction as a result of exclu- sionary discipline as White students (Vincent et al., 2012). Given that most referrals that lead to exclusionary discipline practices are written by teachers for disruptive behaviors that begin in the classroom, it is argued that disproportionality and the subsequent school-to-prison pipeline begin in the classroom and therefore must be addressed in the classroom.

Although there are well-established benefits of teachers engaging in positive and proactive behavior management strategies to prevent and respond to behavioral infractions (Sugai & Horner, 2002, 2006), research demonstrates that their use does not adequately meet the behavioral needs of all students (Siwatu & Starker, 2010) or close the discipline gap for African American students (Vincent, Swain-Bradway, Tobin, & May, 2011). Specifically, such positive behavior supports reduce the overall use of such exclusionary disci- plinary responses (e.g., Bradshaw, Mitchell, & Leaf, 2010), although African American students are still disproportionally represented. Extant literature exploring teachers’ use of cul- turally responsive practices is currently inconclusive (Bottiani, Larson, Debnam, Bischoff, & Bradshaw, 2017); however, it is hypothesized that using such practices would further and more equitably improve student behavioral outcomes and reduce disproportionality. Furthermore, the best approach to measurement of such practices is unknown. Thus, more research is needed on culturally responsive practices, partic- ularly in relation to student outcomes.

The purpose of the current study was to utilize a multi- method approach to assess teachers’ use of both proactive behavior management and culturally responsive teaching practices and to examine the extent to which both were asso- ciated with student behaviors observed at the classroom level. We were particularly interested in contrasting teacher self-re- ported efficacy for engaging in such practices as well as obser- vations conducted within the classroom to determine whether differences existed between teacher beliefs and observed practice. In fact, much of the research to date has relied on self-reported measures of culturally responsive teaching (Chu, 2013; Chu & Garcia, 2014; Siwatu, 2007, 2009, 2011; Siwatu & Starker, 2010); the inclusion of both self-reported data and observations of culturally responsive teaching, in addition to social desirability bias, allowed us to advance prior research on this topic and inform our understanding of measurement issues related to culturally responsive teaching. This line of inquiry serves as a critical starting point for the identification of indicators and measurement modalities, as well as promis- ing teacher practices, which can then be used to inform further measurement and intervention research.

Proactive Behavior Management

Student engagement and achievement are associated with teachers’ use of evidence-based and proactive classroom management practices (Dunlap, Iovannone, Wilson, Kincaid, & Strain, 2010; Simonsen, Fairbanks, Briesch, Myers, &

Sugai, 2008). Examples of such practices include clearly stat- ing expectations, anticipating when students may struggle, and precorrecting for undesired behaviors (e.g., reminding students before they transition to a new activity what behav- iors to engage in as a way to avoid them talking to one another and getting off-task; Dunlap et al., 2010; MacSuga-Gage, Simonsen, & Briere, 2012; Pisacreta, Tincani, Connell, & Axelrod, 2011; Simonsen et al., 2008). Research suggests that a broader set of positive instructional and behavioral manage- ment practices, including providing students with behav- ior-contingent praise and increasing opportunities to respond, are also associated with improved student academic behaviors (Dufrene, Lestremau, & Zoder-Martell, 2014; Sutherland, Wehby, & Copeland, 2000; Sutherland, Wehby, & Yoder, 2002). However, most of the research on such management strategies has been conducted with small samples of teachers and among students with specific disabilities. Moreover, school-wide implementation of proactive and positive behav- ior management practices (e.g., setting clear behavioral expectations and reinforcing the meeting of these expecta- tions) has been shown to reduce disciplinary referrals and suspensions in general (Bradshaw et al., 2010) but has shown a limited impact on disproportionality (Vincent et al., 2011). As such, additional research is needed to examine associa- tions of the use of such practices with student behavior in larger samples of classrooms, including ethnically diverse general education classrooms.

Culturally Responsive Teaching

Culture has been defined as the integrated pattern of human behavior (e.g., thoughts, communication, action, cus- toms, beliefs, values, and instructions) of a racial, ethnic, reli- gious, or social group (Day-Vines et al., 2007; Leighton, 1982). Some have described culture as a spectrum, ranging from surface elements (e.g., food, language, dress) to deeper components (e.g., notions of self, norms, prejudices; Hammond, 2014; Weaver, 1986). Scholars suggest that a “dis- connect” between the school and home, in terms of culture, may contribute to disproportionality (Cholewa & West- Olatunji, 2008). Thus, it is hypothesized that educators must understand the association between a student’s culture and behavior (Cholewa & West-Olatunji, 2008; Hosp & Hosp, 2001; Skiba, Poloni-Staudinger, Gallini, Simmons, & Feggins-Azziz, 2006) and incorporate the student’s culture into their teaching (Gay, 2002; Ladson-Billings, 1995a, 1995b; Villegas & Lucas, 2002) to improve the outcomes of students from ethnic/racial minority backgrounds. The under- standing and incorporation of a student’s culture into the classroom is referred to as culturally responsive teaching or culturally responsive pedagogy. Scholars generally agree that the basic principles of culturally responsive teaching include having the knowledge, dispositions, and skills necessary to teach in a diverse society (Villegas & Lucas, 2002).

Engaging in culturally responsive teaching generally begins with knowledge of culture in a broad sense, teachers’

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clear understanding of their own and others’ cultures, and an ability to connect to their students through this understanding (Gay, 2002; Ladson-Billings, 1995a, 1995b, 2001; Villegas & Lucas, 2002). Strategies to foster this connection may include integrating artifacts that reflect a student’s interests and using real-world examples and problems to solve during instruction to connect students to their community, national, and global identities (Bouillion & Gomez, 2001). Additionally, in recog- nizing and responding to variability in how students demon- strate knowledge, teachers may provide opportunities for students to coteach or cofacilitate lessons (Emdin, 2008). Moreover, scholars suggest that teachers may accommodate different communication styles through varying their own communication (Bondy et al., 2007; Day-Vines & Day- Hairston, 2005). For example, teachers may use humor to engage students, defuse problems, or set expectations (Bondy et al., 2007), or they may provide direct commands when ask- ing students to complete a task, as some students respond better to this approach (Day-Vines & Day-Hairston, 2005).

Little empirical research has examined the extent to which culturally responsive teaching strategies are associated with student outcomes (Ahram, Fergus, & Noguera, 2011; Bottiani et al., 2017; Moore & Ratchford, 2007; Reglin, Akpo-Sanni, & Losike-Sedimo, 2012). The few studies examining this association have typically used small sam- ples, analyzed data using descriptive statistics, and relied heavily on disciplinary and special education referral data (Ahram et al., 2011; Moore & Ratchford, 2007; Reglin et al., 2012). Although referral data can provide information on shifts in the degree of disproportionality, using such data in isolation does not allow one to parse out whether student behavioral or referral process changes are the mechanism for change. Further, much of the research lacked a rigorous (i.e., randomized) research design; thus, one cannot draw causal conclusions about whether a change is associated with improved teacher practices. Moreover, this research has relied heavily on teacher-reported data and assessed efficacy rather than actual teacher practices (Chu, 2013; Chu & Garcia, 2014; Siwatu, 2007, 2009, 2011; Siwatu & Starker, 2010). As such, additional research that incorporates obser- vations of both teacher behaviors and student outcomes is needed.

Teacher Self-Efficacy and Social Desirability

Self-efficacy is an individual’s belief or confidence in his or her capabilities to execute specific actions or tasks (Bandura, 1977). Interest in teacher self-efficacy began with general teacher self-efficacy (Dembo & Gibson, 1985) and shifted to focus on more specific areas of teacher self-efficacy, including classroom management (Emmer & Hickman, 1991; Lin, Gorrell, & Taylor, 2002; Woolfolk, Rosoff, & Hoy, 1990) and teaching students from diverse backgrounds (Banks, Dunston, & Foley, 2013; Chu, 2013; Guyton & Wesche, 2005; Pang & Sablan, 1998; Siwatu, 2007; Sorrells, Schaller, & Yang, 2004; Tucker et al., 2005). Collecting self-efficacy

data can be a time- and cost-efficient method to assess teach- ers’ abilities and a proxy for teacher practices. Several studies have found that self-efficacy in behavior management is asso- ciated with reductions in disruptive student behaviors (Reinke, Herman, & Stormont, 2013) and indicators of dis- proportionality (e.g., Peters, Kranzler, Algina, Smith, & Daunic, 2014; Reinke et al., 2013). Specifically, teachers with a greater sense of self-efficacy in behavior management report externalizing behaviors of African American students to be less problematic and more similar to their White coun- terparts than teachers with lower self-efficacy in behavior management (Peters et al., 2014). There is likely a transac- tional association between efficacy and behavior such that teachers with higher self-efficacy in behavior management engage in improved practices that result in improved student behavior, and improved behavior leaves teachers feeling more efficacious. Thus, teacher self-efficacy in behavior management, as well as actual use of culturally responsive teaching may play an important role in student outcomes. However, further research incorporating efficacy and actual strategy use is needed  (Bondy, Ross, Gallingane, & Hambacher, 2007; Brown, 2004).

Measuring self-efficacy has figured prominently in cul- turally responsive research because knowledge and attitude are key characteristics of a culturally responsive teacher (Gay, 2002; Ladson-Billings, 1995a, 1995b, 2001; Villegas & Lucas, 2002). However, research, particularly in the counsel- ing field, suggests that self-reports of multicultural self-effi- cacy, or the aggregate attitudes/beliefs, knowledge, and skills necessary to work with individuals from a variety of cultural groups (e.g., racial, ethnic, gender, social class, and sexual orientation), are likely to be influenced by teachers’ social desires to provide positive reports about themselves (Constantine, 2001; Katz & Hoyt, 2014; Larson & Bradshaw, 2017; Ohm & Rosen, 2011). An improvement on the current self-reported literature would take such social desirability bias into account when measuring self-reports of culturally respon- sive teaching (Spanierman et al., 2011). Determining whether individuals seek social approval on self-report measures is important to advance the field, as is determining whether those ratings are also related to observations of teacher behaviors.

Current Study

The purpose of this study was to examine teachers’ use of proactive behavior management and culturally responsive teaching practices simultaneously to determine whether they were associated with student behaviors observed at the classroom level. We utilized a quantitative, multimethod approach, through which we collected both teacher self-re- ported efficacy and behavioral observations of proactive behavior management and culturally responsive teaching. We used this approach to address multiple gaps in the liter- ature on culturally responsive teaching, which has largely excluded quantitative analysis of how this teaching method

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associates with student behavior and has mainly relied on self-reported survey research.

Extant literature suggests that self-efficacy is tied to teacher behaviors (i.e., the use of specific teaching strate- gies; Siwatu, 2009) and that the use of proactive behavior management (Simonsen et al., 2008) and culturally respon- sive teaching practices (Moore & Ratchford, 2007) is asso- ciated with higher rates of positive student behavior. Thus, we hypothesized that higher self-reported ratings of self-ef- ficacy and ratings by observers of both culturally responsive teaching and behavior management would be related to observed student behavior. Additionally, since the literature suggests that there may be an association between social desirability bias and teacher self-reports (see Constantine, 2001; Crowne & Marlowe, 1960; Katz & Hoyt, 2014; Larson & Bradshaw, 2017; Ohm & Rosen, 2011), we controlled for social desirability bias. We also controlled for select teacher characteristics, such as race, role (i.e., general educator vs. special educator), and number of years in the teaching role, as prior research suggests that multicultural self-efficacy is associated with practitioner characteristics (see Constantine, Juby, & Liang, 2001; Granello & Wheaton, 1998; Larson & Bradshaw, 2017; Neville, Spanierman, & Doan, 2006). Furthermore, we adjusted for years of experience, as teach- ers who are newer to the field may lack the experience and expertise needed to integrate culturally responsive practices, like other effective behavior management practices, into their teaching (Boyd, Grossman, Lankford, Loeb, & Wyckoff, 2009; Clotfelter, Ladd, & Vigdor, 2007; Easton- Brooks & Davis, 2009). Educational research has rarely considered these characteristics when exploring self-reports as well as observations of culturally responsive teaching (Chu & Garcia, 2014; Daunic, Correa, & Reyes-Blanes, 2004; Imler, 2009).

METHOD

Survey and observational data from a larger study were used to examine the associations between teachers’ use of proactive behavior management and culturally responsive teaching practices with observed student behaviors at the classroom level. The sections that follow provide information about the participants, the procedure for data collection, and the measures used in the current study.

Participants

Self-report and observation data were obtained from 274 teachers in 18 schools (n = 106 elementary school teach- ers in 9 elementary schools; n = 168 middle school teachers in 9 middle schools). All teachers were participating in an intervention study; however, only the baseline (i.e., preinter- vention) data from that project were used for the current study. All schools were located in one district that included suburban and urban fringe settings and served a diverse student body (see Table 1).

Across the 18 schools, based on full enrollment data, about 41% of the students were White, nearly one third (34%) of the students were African American, and about 13% of students were Hispanic/Latino. Enrollment data also reflected that approximately half of the students in these schools

Table 1. Demographics of Teachers and Schools in Current Study

Teacher Characteristic

N (%) N = 274

Age

20–30 85 (30)

31–40 73 (26)

41–50 62 (23)

51–60 47 (17)

61+ 9 (3)

Gender

Female 237 (86)

School Level

Pre-K/Kindergarten 25 (9)

Elementary 72 (26)

Middle 130 (47)

Multiple Grades 49 (18)

Race/Ethnicity

Caucasian/White 221 (80)

African American/Black 34 (12)

Hispanic/Latino 4 (1)

Asian/Pacific Islander 2 (1)

Native American/American 2 (1)

Other 13 (5)

Teacher Role

General Educator 237 (86)

Middle School 168 (61)

Years of Teaching in Role

0–3 71 (26)

4–8 74 (27)

9+ 131 (47)

School Demographics M (SD)

Percent of African American Students 34.38 (17.41)

Percent of Hispanic Students 12.68 (6.10)

Percent of Students Receiving FARMs 50.05 (22.66)

Note. School demographic data are collected annually by the state and made openly accessible and are from the study year. FARM = free and reduced-priced meals.

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received free and reduced-priced meals (FARMs). Based on observational data, where observers recorded their count of White students, approximately 60% (n = 3,129) of the stu- dents in the classrooms visited were recorded as White. The sample included only general educators (86%, n = 237) and special educators (14%, n = 39) responsible for delivering core content (i.e., English, Math, Science, Social Studies) within general education classrooms. Most teachers were women (86%; n = 237) and White (80%; n = 221); approxi- mately 26% (n = 71) of the teachers were in their first three years of teaching.

Procedure

Data were collected as a baseline measure for a larger intervention study of a professional development and coach- ing intervention targeting culturally responsive teaching prac- tices and positive and proactive behavior management. Teacher participation was voluntary, and consent was pro- vided to complete surveys and to allow for external observa- tions to be conducted in the classroom. Self-report surveys were administered via a secure online survey system. Participating teachers received a $10 gift card in appreciation of their time taken in completing the survey. Among the par- ticipating teachers, 95% completed the self-report survey and 89% had observations conducted.

Observations of teachers’ classrooms were collected by observers trained by the research team in 248 classrooms prior to the participants being informed of their intervention status. All observational data collectors received training in four stages: (a) an initial didactic session, (b) on-site practice, (c) on-site interobserver agreement or reliability, and (d) on-site recalibration. Each data collector was trained until they reached a reliability criterion of 80% (for additional information on the scale and its administration, see Debnam, Pas, Bottiani, Cash, & Bradshaw, 2015; Pas, Cash, O’Brennan, Debnam, & Bradshaw, 2015). Dates for obser- vations were coordinated with administrators, and teachers were notified that observers would come to their classrooms at some time during the days selected. The specific times within those prescheduled dates were selected by the research team observers; if there was a test or the teacher present was not the usual teacher (i.e., a substitute), the observer would return to the classroom at a different time to conduct the observation.

Measures

Data were collected via an online self-report survey and from classroom observations. The survey included demo- graphic questions and Likert-type items, with 1 = strongly disagree to 6 = strongly agree. Four survey scales were of interest for this study and are described below.

Observational data were collected using the Assessing School Settings: Interactions of Students and Teachers direct observational measure (ASSIST; Rusby, Taylor, & Milchak,

2001), which assesses information about various student and teacher behaviors. During a 15-min observation, ASSIST- trained data collectors, who were unaware of the purpose of the research study and the teachers’ intervention status, tallied the number of teacher and student behaviors observed across several dimensions. At the end of each 15-min observation session, data collectors left the teacher’s classroom and imme- diately completed a series of global rating items. Global rat- ings were scored on a 5-point Likert-type scale, with 0 = Never and 4 = Almost continuously or Often occurred (6+ times). Three of the global rating scales (i.e., Student Cooperation, Teacher Proactive Behavior Management, and Teacher Culturally Responsive Strategies) were of interest in this study. Together, these data were used to examine the extent to which culturally responsive teaching and proactive behavior management practices were associated with student behaviors. A recent generalizability study (G-study) was con- ducted of the ASSIST and reported strong reliability of the scores (Abry, Cash, & Bradshaw, 2017).

Student Behavior Outcome Student engagement in positive behavior was measured

using the Student Cooperation scale on the ASSIST; this 7-item scale includes indicators of how often students abided by school rules, norms, and expectations for academic readi- ness. Sample items include: Students are focused and engaged and Students comply. Higher scale scores reflected greater student cooperation. This scale demonstrated adequate inter- nal validity in prior research (Pas et al., 2015) and internal reliability in the current study (α = .92).

Teacher Self-Efficacy in Behavior Management Five items were used to measure teachers’ self-reported

ability to manage challenging student behaviors. Three items on the measure originated from the Teacher Efficacy Scale (Hoy & Woolfolk, 1993) and two additional questions were added from previous research (Pas, Bradshaw, & Hershfeldt, 2012). Example items are: If a student becomes disruptive and noisy, I feel assured that I now have some techniques to redi- rect him/her quickly and I can effectively work with deviant or disruptive students. This five-item measure demonstrated adequate internal consistency in previous research (Pas et al., 2012) and in the current study (α = .80). Higher scale scores indicated greater teacher self-efficacy to manage behavior problems.

Observed Proactive Behavior Management The Proactive Behavior Management subscale of the

ASSIST is comprised of 4 items and assesses how often teach- ers implemented practices that prevented or represented a positive response to behavioral disruptions (α = .66). Sample items include the following: The teacher gives clear instruc- tions and directives to students; The teacher is consistent, even-handed, and firm when necessary; The teacher clearly explains learning objectives prior to and/or during the lesson through summary or reorientation statements; and The teacher praised students for specific behaviors or using social

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skills. Higher scale scores reflected a greater use of proactive behavior management strategies.

Self-Efficacy in Culturally Responsive Teaching The Multicultural Efficacy Scale (MES; Guyton &

Wesche, 2005) is a 14-item scale that assesses one’s efficacy to implement skills needed to teach in multicultural settings (α = .81). Sample items include the following: I can adapt instructional methods to meet the needs of learners from diverse groups, I can help students work through problem situations caused by stereotypical and/or prejudicial atti- tudes, and I can develop activities that increase the self-con- fidence of diverse students. Higher scale scores indicated greater self-efficacy in culturally responsive teaching.

Observed Use of Culturally Responsive Teaching The Teacher Culturally Responsive Strategies subscale

of the ASSIST assesses the use of culturally responsive teach- ing practices in the classroom (7-item scale; α = .73). The seven items on this scale were: Teacher connects lessons to real world examples, Teacher integrates cultural artifacts reflective of students’ interests into learning activities, Teacher engages in storytelling or sharing, Teacher uses positive humor to engage students or defuse problems, Teacher gives students opportunities to coteach or cofacilitate learning, Teacher gives direct commands, and Teacher employs rhythm or “call and response” instructional strategies. Higher scale scores reflect greater observed use of culturally responsive teaching strategies.

Social Desirability The Marlowe–Crowne Scale of Social Desirability

(Crowne & Marlowe, 1960) is one of the most widely used measures of social desirability; it measures the extent to which survey respondents answer questions in a manner that they believe will be viewed favorably by others and that indi- viduals are not always able to agree or disagree (α = .62). Items include: I am always courteous, even to people who are disagreeable and I never hesitate to go out of my way to help someone in trouble. The original Marlowe–Crowne measure included 33 items and had an internal consistency of .88 and a test-retest correlation of .89 (Crowne & Marlowe, 1960). Shortened forms of the Marlowe–Crowne scale have been shown to be reliable (Ballard, 1992; Fischer & Fick, 1993; Strahan & Gerbasi, 1972) with a Kuder–Richardson coeffi- cient of .62 (Strahan & Gerbasi, 1972). Higher scale scores indicate a higher degree of social desirability bias (i.e., the respondent is more likely to seek social approval from others). In the context of other self-report scales, this measure would indicate the extent to which a person may have answered in a socially desirable manner, and thus serves as a potentially important control variable in the current study (Larson & Bradshaw, 2017).

Teacher Demographics Teachers provided self-reported basic demographic

data on the online survey. Specifically, teachers reported their

racial/ethnic group (i.e., Native American/American Indian, Asian/Pacific Islander, Black/African American, White, Hispanic/Latino, Native Hawaiian or Other Pacific Islander, and Other). In addition, teachers reported their role in the school as either a general or special educator. Lastly, teachers reported the number of years they had been teaching in their role. Since teachers are believed to become more effective with experience (Boyd et al., 2009; Clotfelter et al., 2007; Easton-Brooks & Davis, 2009), we included a variable indi- cating the extent to which a teacher was new in his or her career (0 = 0–3 years, 1 = 4 or more years).

Analyses

We used structural equation modeling (SEM) using Mplus version 7.3 (Muthén & Muthén, 2012) to examine our research aims (see Figure 1).

SEM allowed simultaneous testing of the association and directionality among the latent variables of interest, which are presumed to reflect a construct that is not directly observable (Kline, 2011; Schreiber, Nora, Stage, Barlow, & King, 2006; Teo, 2010). Using latent variables in SEM allows for an entire model based on an a priori theory to be estimated and generates an accurate estimate of measurement error (Kline, 2011; Schreiber et al., 2006). Specifically, the error variance in SEM is estimated for the entire model, thereby freeing the latent variables themselves from measurement error (Kline, 2011; Schreiber et al., 2006). SEM also provides information about the association among the variables and the indicators that comprised each latent variable and scale (Kline, 2011). The items reported for each of the measures described previously were used to create a latent construct for each scale. Finally, when modeling scales as latent, using the items as indicators, and utilizing the maximum likelihood method, teachers with data on at least some of the items for each construct can be retained. Despite this, we performed a missing value analysis (MVA), the findings of which are pre- sented in the Results section.

Prior to analyzing the structural equation model, a con- firmatory factor analysis (CFA) was examined to replicate earlier measurement work conducted on the ASSIST (e.g., Debnam et al., 2015; Pas et al., 2015). In addition, demo- graphic variables, including teacher role (1 = general educa- tor, 0 = special educator), experience in role (0 = 0–3 years, 1 = 4 or more years), gender (0 = male, 1 = female), and race (0 = Non-White, 1 = White) were included as manifest covari- ates (i.e., observed, nonlatent) in the model.

Fit indices were examined to determine the fit between the SEM models and the observed data. Specifically, the root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker–Lewis Index (TFI), and weighted root mean residual (WRMR) were computed to determine model fit (Kline, 2011) for both the CFA and the SEM. Fit indices for the CFA indicated that the items adequately loaded onto their respective a priori scales (RMSEA = .022, CFI = .968, TLI = .966, WRMR = 1.196). Prior research suggests the

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following values for adequate model fit: RMSEA < .06, CFI > .95, and TFI > .95, and WRMR is close to 1.0 (Hu & Bentler, 1999; Kline, 2011; Schreiber et al., 2006). We took into con- sideration that survey and observation items were ordinal by using weighted least squares means and variance adjusted (WLSMV) estimation. Finally, given that teachers were clus- tered into 18 schools, we used the type = complex statement and group-mean centered all variables to ensure that parame- ter, standard error, and p-value estimates accounted for this clustering (Stapleton, McNeish, & Yang, 2016). The range and means of scale scores on the observations were normally distributed and utilized the full range of possible responses on the 5-point Likert scale (see Table 2).

RESULTS

This section summarizes the findings from the analysis regarding the association among teachers’ use of proactive

behavior management and culturally responsive teaching practices with observed student behaviors at the classroom level. A description of the analysis of missing data is provided followed by results from the SEM analysis.

Missing Data

An analysis of missing data was conducted to evaluate the amount, distribution, and pattern of missing data. MVA via the SPSS software was used to highlight patterns of missing values (Tabachnick & Fidell, 2013). Data were present for more than 95% of the dataset. Specifically, missing data on scales ranged from 0–10% (M = 4.90; SD = 9.24). The highest per- centage of missing data was from observations in the class- rooms. Specifically, about 10% (n = 26) of data were missing for classroom observation variables (e.g., culturally responsive teaching, student cooperation, and teacher proactive behavior management). One teacher (0.4%) was missing data on the

Figure 1. Structural Equation Model Displaying Standardized and Statistically Significant Associations

Note. Circles represent latent factors comprised of scale items. Squares represent manifest (i.e., measured) variables. “ASSIST” indicates observed variables whereas “survey” indicates self-reported scales. Fit indices: RMSEA = .022, CFI = .968, TLI = .966, WRMR = 1.196; *p < .05, **p < .01, ***p < .001. This model does not include non-statistically significant findings for predictor variables (e.g., teacher has 4+ years of experience and teacher is White).

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teacher efficacy for behavior management scale. Teachers were not missing data on the multicultural efficacy scale or social desirability scales. Additionally, data collectors observed tran- sitions in only 35% of classrooms in the sample and only one of the items on the student cooperation scale asked about tran- sitions; as such, 65% of the data were considered missing for one item on the student cooperation scale. Little’s test of Missing Completely at Random, however, was not statistically significant for any value (χ = 317.98, p > .05), thereby suggest- ing that missing data were missing completely at random (Little, 1988). As such, most data were present for the majority of the variables (≥ 90%) and handling such a small amount of missing data using any missing data techniques is not necessary and would yield similar results (Tabachnick & Fidell, 2013).

Structural Equation Model

Positive Student Behavior We fit a model to test our hypothesis that higher ratings

of student behavior would be provided by observers in class- rooms where teachers reported higher self-efficacy in both behavior management and culturally responsive teaching and were observed using culturally responsive teaching and pro- active behavior management practices. Fit indices indicated that the data adequately fit this model (RMSEA = .022, CFI = .968, TLI = .966, WRMR = 1.196). The SEM results indicated that observations of culturally responsive teaching

(see Table 3) were statistically significant and positively asso- ciated with student behavior outcome, such that a change of onestandard deviation in culturally responsive teaching strat- egies was associated with a 0.12-point increase in the observer ratings of student behavior.

Observations of proactive behavior management were also statistically significant and positively associated with stu- dent behavior outcome. Specifically, an increase of one standard deviation in proactive behavior management strategies was associated with a 0.84-point increase in student behavior out- come. Although both observational measures of teacher strate- gies were associated with positive student behavior, teacher self-efficacy of behavior management and teacher self-efficacy of culturally responsive teaching were not (See Table 3).

Association Between Measures

Self-Reports and Observations of Constructs The model also allowed for examination of covariance

between the self-efficacy and observational measures. Findings indicated that there were statistically significant associations between the two observations of teacher strategy use (ψ = .60, p < .001) and between the two self-efficacy scales (ψ = .57, p < .001). Across measures (i.e., between effi- cacy and observed use of strategies), observations of teacher proactive behavior management were negatively associated with teacher self-efficacy of behavior management

Table 2. Descriptive Statistics of Measures and Correlations

Measure Range M (SD)

Teacher Self-Reported Measures

SDB 2.90–5.70 4.46 (0.56)

MES 3.29–5.86 4.62 (0.47)

TEBM 2.20–6.00 4.51 (0.69)

Observational Measures

TPBM 1.25–4.00 3.06 (0.61)

SBOP 1.00–4.00 3.24 (0.66)

CRTO 0.00–4.00 1.21 (0.92)

Measure MES TEBM TPBM SBOP

TEBM .51**

TPBM −.07 −.05

SBOP −.07 −.02 .74**

CRTO −.00 .01 .38** .47**

Note. The teacher self-reported measures were on a 6-point Likert scale, with possible scale scores ranging from 1 to 6. The observational measures were on a 5-point Likert scale, with possible scale scores ranging from 0 to 4. SDB = Social Desirability Bias; MES = Multicultural Efficacy Scale; TEBM = Teacher Efficacy in Behavior Management; TPBM = Teacher Proactive Behavior Management; SBOP = Positive Student Behavior; CRTO = Culturally Responsive Teaching Strategies–Observed. **p < .01.

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(ψ = −0.12) and self-efficacy of culturally responsive teaching (ψ = −0.18; ps < .05; see Table 3).

Social Desirability Bias Social desirability was modeled as a latent construct to

control for the possibility that measures could be influenced by such bias. Results indicated that social desirability was statistically significant and positively associated with the self-efficacy reports of culturally responsive teaching (ψ = .46, p < .001) and teacher efficacy in behavior manage- ment (ψ = .57, p < .001). In other words, higher ratings of teacher self-efficacy for culturally responsive teaching was related to higher social desirability bias, highlighting the importance of including this variable in the study. In contrast, observation measures were not associated with self-reported social desirability (See Table 3).

Teacher Characteristics Several teacher characteristics were statistically signifi-

cantly associated with self-efficacy and observation measures. Specifically, general educators reported less self-efficacy in

behavior management than special educators (ψ = −.15, p < .01) and were observed to use greater culturally respon- sive teaching strategies (ψ = .15, p < .01). Moreover, females reported lower self-efficacy related to culturally responsive teaching than males (ψ = −.13, p < .01).

DISCUSSION

The purpose of this study was to determine whether teachers’ self-efficacy and observations of culturally responsive teaching and proactive behavior management were associated with observed student behavior at the classroom level. We hypothesized that teachers’ use of culturally responsive teach- ing and proactive behavior management practices (as rated by external observers), together with higher teacher-reported self-efficacy in using such practices, would be associated with more favorable student behaviors, even after controlling for teacher social desirability and teacher characteristics. Taken together, the SEM results indicate partial support for our hypothesized model; our analyses indicate that observations of

Table 3. Standardized Parameter Estimates for Structural Model (N = 274)

Coefficient SE p-value

Predicting SBOP

Behavior Management Measures

TEBM 0.08 0.05 .10

TPBM 0.84*** 0.04 .00

Culturally Responsive Teaching Measures

MES −0.03 0.04 .43

CRTO 0.12* 0.06 .04

Standardized Covariates TEBM TPBM MES CRTO

Social Desirability Bias .57*** .00 .46*** .07

General Educator −.15** −.04 −.06 .15*

4+ Years Teaching in Role −.04 .01 .03 .08

Teacher Is White −.06 −.07 −.06 .01

Teacher Is Female .01 .05 −.13* .09

Standardized Covariances TEBM TPBM MES CRTO SBOP

TEBM −.12* .57*** .01

TPBM −.18* .60***

MES .01

ICC 0.10 0.00 0.10 0.01 0.20

Note. Model displays standardized regression coefficients loadings. SBOP = Positive Student Behavior; TEBM = Teacher Efficacy in Behavior Management; TPBM = Teacher Proactive Behavior Management; MES = Multicultural Efficacy Scale; CRTO = Culturally Responsive Teaching Strategies–Observed; ICC = interclass correlations. *p < .05; **p < .01; ***p < .001.

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teachers’ use of both culturally responsive and proactive behav- ior management practices were associated with observed pos- itive student behavior, whereas teachers’ self-efficacy regarding their use of such skills was not. Prior research suggests that proactive behavior management is important to positive student behavior (Dunlap et al., 2010; Simonsen et al., 2008). In fact, when observers in this study noted higher frequencies of pro- active behavior management practices (e.g., providing clear instructions, clearly explaining learning objectives, praising students for specific behaviors), they also observed greater stu- dent cooperation and engagement in expected behaviors. Similarly, the teachers’ use of culturally responsive teaching practices (e.g., lessons relating to the real world, using positive humor, employing rhythmic call and response) was also related to more positive ratings of observed student behavior. Using Cohen’s (1992) magnitude interpretation, our statistically sig- nificant results suggest that culturally responsive teaching has a limited association with positive student behavior, over and above effect of proactive behavior management. Conversely, it is worth noting that the association between observed proactive behavior management and positive student behavior was con- siderably larger than the association between culturally respon- sive teaching and positive student behavior. Further, the average scores on the culturally responsive teaching practices scale were somewhat low (i.e., 1.21 on a scale up to 4), which indi- cates additional room for growth on this skill. Nonetheless, the relative magnitude of the culturally responsive teaching finding is a novel contribution of this study.

On the other hand, teachers’ self-efficacy of culturally responsive teaching and behavior management was not posi- tively associated with the observed student outcomes. These results were unexpected considering the number of studies that use self-efficacy measures to assess aspects of culturally responsive teaching (Chu, 2013; Chu & Garcia, 2014; Siwatu, 2007, 2009; Siwatu & Starker, 2010), as well as other teach- er-efficacy related research dating back to the mid-1980s (Dembo & Gibson, 1985; Emmer & Hickman, 1991; Lin et al., 2002; Midgley, Feldlaufer, & Eccles, 1989; Riggs & Enochs, 1990; Soodak & Podell, 1993; Soodak, Podell, & Lehman, 1998; Starko & Schack, 1989; Woolfolk, Rosoff, & Hoy, 1990). Teachers’ self-efficacy to engage in behavior management and culturally responsive teaching was nega- tively associated with observed teacher use of proactive behavior management. An earlier study found inconsistent associations (i.e., some desired and some undesired) with observations of teacher strategies and self-reports of efficacy (see Debnam et al., 2015). The findings of the current study suggest that self-reported self-efficacy measures may not be the most valid indicators of actual use of culturally responsive practices and that, optimally, future research would integrate direct observations of teacher practices and student behavior in addition to self-report measures of actual use, rather than self-reported self-efficacy to implement practices.

We also considered a variety of teacher-level demo- graphic variables as possible covariates. For example, we found that the race/ethnicity of the teacher was not a statistically

significant predictor of efficacy or the observation measures of behavior management or culturally responsive teaching. Although the lack of an association between teacher race/eth- nicity and student behavior is consistent with prior research (Pas & Bradshaw, 2014), the lack of an association between race/ethnicity and culturally relevant outcomes was inconsis- tent with prior research. In fact, there is considerable interest in policies and programs that aim to increase the number of racial/ ethnic minority teachers as an approach for reducing dispari- ties; much of this interest is based on emerging research which suggests that exposure to same-race teachers is associated with reduced rates of exclusionary discipline for African American students (Lindsay & Hart, 2017). Similarly, we were surprised that years of experience was not a statistically significant pre- dictor of observed or self-reported efficacy in behavior man- agement or culturally responsive teaching, as prior work has suggested that early career teachers may not be as adept at using these approaches as are their more experienced peers (Boyd et al., 2009; Clotfelter et al., 2007; Easton-Brooks & Davis, 2009). This finding suggests that other variables in the model may have accounted for these associations; however, additional research is needed to better understand whether there is a poten- tial link between years of teaching experience and behavior management or culturally responsive teaching.

Strengths and Limitations

There are several strengths of the current study, includ- ing the use of a multimethod approach that controls for poten- tial confounding variables such as social desirability and teacher characteristics. The relatively high racial and socioeco- nomic diversity of the student sample was also a strength, as was the use of SEM to simultaneously model associations between all constructs of interest. Nonetheless, there are some limitations to consider. For example, the data were cross-sec- tional and thus we cannot make causal assumptions. Moreover, regarding measurement, we used slightly abbreviated self-re- port scales from the original measures to reduce participant burden and to cover a wide range of constructs, and this resulted in reduced internal consistency. This issue may be particularly pronounced for the social desirability scale.

Furthermore, we only conducted one 15-min observa- tion on the ASSIST for each teacher. Although multiple obser- vations are recommended when it comes to observational assessment of teacher practices (Cantrel & Kane, 2013), it was not feasible to do so in the current study. This is a limita- tion of the current research; however, the collection of multi- ple waves of observational data is also not likely to be feasible for school personnel in practice, and thus, this research may provide feedback to use in practice with teachers to improve their classroom practices. Moreover, it is challenging to cap- ture all of the possible strategies to address “culture” in a single observation measure, which further illustrates the need for additional measure development and testing. Taken together, these findings highlight the importance of multi- method approaches to assessing teacher and student

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behaviors. Future research should incorporate multiple obser- vations which may be able to capture a broader range of teacher and student behaviors, as well as ensure the greatest reliability. Another potential concern is that both the observa- tional indicators were assessed by the same observers using the ASSIST and, therefore, have shared method variance which may impact construct validity. Thus, the inclusion of other data sources, such as school discipline records and stu- dent reports would further enhance our understanding of the pattern of findings across multiple data sources as well as provide additional insight into disproportionality. It would also be helpful to consider the outcomes for disproportionality more specifically and to include specific measures of both race and socioeconomic status in relation to disproportional- ity; this information was not available in the current study.

The district, principals, and teachers all volunteered to participate in the project, which may reflect some level of selection bias toward schools and participants that are inter- ested in contributing to the research on issues related to cul- turally responsive teaching. Finally, the participating teachers only worked in elementary and middle schools. Therefore, additional research is needed to provide data for high school teachers, and larger samples should be used to allow for com- parisons across the different school levels.

Conclusions and Implications

Taken together, these findings suggest that there are statistically significant associations between observations of culturally responsive teaching and proactive behavior man- agement and positive student behaviors; however, the findings seem to be most salient for observations rather than for self-reported indicators of efficacy in behavior management and culturally responsive practices. Although this study was nonexperimental, it appears possible that the cumulative use of culturally response teaching strategies could prove prom- ising in helping to address the exclusionary discipline crisis. These practices include making the curriculum relevant to students (e.g., connecting it to real-world examples and incor- porating cultural artifacts), varying the way in which students engage and display understanding (e.g., coteaching), and varying the way in which teachers communicates (e.g., using humor, providing direct commands). Determining whether the use of such strategies is associated with a reduction in disparities in exclusionary discipline actions between African American students and White students remains an important next step in this line of research, and certainly an area needing a stronger empirical base (Bottiani et al., 2017).

The current findings also highlight the importance of incorporating both self-reports of efficacy and observed teacher practice as well as other data sources (Chu, 2013; Chu & Garcia, 2014; Imler, 2009; Siwatu, 2007, 2009; Siwatu & Starker, 2010) when conducting studies related to culturally responsive teaching. Similarly, the observed link between both of the self-reported measures (i.e., teacher efficacy in behavior management and multicultural efficacy), but neither

of the observational measures (i.e., from the ASSIST), and the social desirability measure highlights the importance of accounting for social desirability bias in future self-report research (Larson & Bradshaw, 2017).

Regarding implications for practice, school psycholo- gists may want to collect data using both self-reported and observational data in the classroom in terms of proactive behavior management and culturally responsive teaching, as measured here. Such data can inform professional develop- ment efforts to improve a range of student outcomes. School psychologists may also want to provide coaching or consul- tation support to individual teachers to further augment school-wide professional development activities in these areas. The use of observational approaches, rather than rely- ing on self-reports, may be best for identifying teachers most in need of support. For example, school psychologists could, either independently or in conjunction with administrators and behavior support teams, administer items from the ASSIST culturally responsive practices measure when con- ducting classroom observations as well as walk-throughs. Such observational data could also be helpful in evaluating the broader impact of programs and professional develop- ment efforts aimed at reducing disproportionality and the discipline gap.

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Date Received: April 27, 2017 Date Accepted: January 3, 2018

Guest Editor: Anne Gregory

AUTHOR BIOGRAPHICAL STATEMENTS

Kristine E. Larson, EdD, is a postdoctoral research fellow at the Johns Hopkins University, Bloomberg School of Public Health. Her research focuses on factors related to teachers’ abilities to manage student behaviors through the use of general and culturally responsive classroom management strategies, and more broadly on improving school climate. She also works as a systems coach to assist principals in using data to improve school climate as part of the Maryland Safe and Supportive Schools (MDS3) research grant, implementing school-wide positive behavioral interventions and supports (SW-PBIS) at their facilities, and using the Classroom Check-Up (CCU) coaching model to improve teacher practice.

Elise T. Pas, PhD, is an associate scientist in the Department of Mental Health at the Johns Hopkins University, Bloomberg School of Public Health. Her research examines the effectiveness of evidence-based interventions delivered through a multitiered system of supports, coaching interventions, the influence of teacher and school contextual factors on implementation and student outcomes, and the adoption and implementation of positive behavior supports in schools. She holds a doctorate in school psychology from the University of Maryland, College Park.

Catherine P. Bradshaw, PhD, MEd, is a professor and the Associate Dean for Research and Faculty Development at the Curry School of Education at the University of Virginia. Her primary research interests focus on the devel- opment of aggressive behavior and school-based prevention. She has led a number of federally funded randomized trials of school-based prevention programs, including positive behavioral interventions and supports (PBIS) and social–emotional learning curricula.

Michael S. Rosenberg, PhD, is the dean of the School of Education and professor of special education at the State University of New York–New Paltz. He is also professor emeritus at the Johns Hopkins University, where prior to his current position he was a professor and department chair in the Department of Special Education and Associate Dean for Research in the School of Education.

Norma L. Day-Vines, PhD, is a professor of counseling and human services at the Johns Hopkins University and an affiliate faculty member in the Center for Africana Studies. She has published widely on counseling strategies for working more effectively with culturally and linguistically diverse children and adolescents, with a special emphasis on African American youth. Most notably, Dr. Day-Vines developed the Continuum of Broaching Behavior, a conceptual framework for examining how counselors explore the contextual dimensions of race, ethnicity, and culture.

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