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Classroom environment and student learning: Classroom-level effects on achievement trajectories in late elementary school

Dissertation
Author: Clare Smith Gaskins
Abstract:
This study uses a three-level model (within-student, between-student, and between-classroom) to examine the effects of 4th and 5 th grade classroom environments on student achievement trajectories during the school year. Between-classroom differences in teacher warmth and classroom order were tested as predictors of student rates of achievement growth, controlling for classroom poverty as well as student characteristics. Classroom order and poverty added incrementally to students' rates of achievement growth when student level demographic and behavioral effects were included in the model. Cross-level analyses identified the moderating effects of classroom environment on achievement growth for at-risk students with higher levels of classroom order promoting greater rates of math achievement growth among disadvantaged minority students.

TABLE OF CONTENTS LIST OF TABLES ...................................................................................................... viii LIST OF FIGURES ....................................................................................................... ix ABSTRACT ................................................................................................................... x

Chapter

1 INTRODUCTION .............................................................................................. 1 Between-Classroom Differences and Achievement ........................................... 2 Between-Student Differences and Achievement ................................................ 5 Summary and Aims ............................................................................................ 8

2 METHOD ......................................................................................................... 10 Participants ....................................................................................................... 10 Procedure .......................................................................................................... 10 Measures ........................................................................................................... 11 Student Demographic Characteristics ..................................................... 11 Interpersonal Functioning ....................................................................... 12 Peer victimization ........................................................................ 12 Disruptive behavior ..................................................................... 12 Home Environment ................................................................................. 13 Parental involvement in academics ............................................. 13 Sleep problems ............................................................................ 14 Classroom Environment .......................................................................... 15 Teacher warmth ........................................................................... 15 Classroom order ........................................................................... 15 Classroom Composition .......................................................................... 16 Grade ...................................................................................... 16 Classroom poverty ....................................................................... 16 Academic Achievement .......................................................................... 16 Analytic Plan .................................................................................................... 17

3 RESULTS ......................................................................................................... 19 Preliminary Analyses ........................................................................................ 19 Unconditional Model ........................................................................................ 19 Conditional Models .......................................................................................... 20 Student-Level Effects on Student Learning ............................................ 20

vii Classroom-Level Effects on Student Learning ....................................... 21 Classroom Effects with Student Characteristics Controlled ................... 23 Classroom Environment as a Moderator of Student-Level Risk Status ........................................................................................... 23 Supplementary Analyses: Classroom Disruptive Behavior versus Classroom Order .......................................................................... 24

4 DISCUSSION ................................................................................................... 25 Limitations ........................................................................................................ 29 Summary and Future Directions ....................................................................... 30

Appendix

A TABLES ........................................................................................................... 32 B FIGURES ......................................................................................................... 40

REFERENCES ............................................................................................................. 41

viii

LIST OF TABLES Table A.1 Descriptive Statistics for Demographic, Interpersonal Functioning, Home Environment, and Classroom Environment Measures ................. 32 Table A.2 Correlations Among Student-Level Variables ....................................... 33 Table A.3 Three-Level Unconditional HLM Model for Math and Reading Achievement Trajectories ........................................................................ 34 Table A.4 Estimation of Univariate and Multivariate Student-Level Effects on Math and Reading Achievement Trajectories .................................... 36 Table A.5 Estimation of Univariate and Multivariate Classroom-Level Effects on Math and Reading Achievement Trajectories ........................ 38

ix

LIST OF FIGURES Figure B.1 Moderating Effect of Classroom Order on Disadvantaged Minority and Non-Minority Students' Math Achievement Growth ....... 40

x

ABSTRACT This study uses a three-level model (within-student, between-student, and between- classroom) to examine the effects of 4 th and 5 th grade classroom environments on student achievement trajectories during the school year. Between-classroom differences in teacher warmth and classroom order were tested as predictors of student rates of achievement growth, controlling for classroom poverty as well as student characteristics. Classroom order and poverty added incrementally to students’ rates of achievement growth when student level demographic and behavioral effects were included in the model. Cross-level analyses identified the moderating effects of classroom environment on achievement growth for at-risk students with higher levels of classroom order promoting greater rates of math achievement growth among disadvantaged minority students.

1 Chapter 1 INTRODUCTION One of the primary concerns driving educational research is the need to better understand how academic settings influence student learning (Bryk & Raudenbush, 1988). Classroom settings are likely to influence student learning especially during elementary school when students spend the majority of their school day and instructional time with the same teacher and classmates. Yet, there is limited empirical evidence of an association between classroom environment and rates of student learning. Although some have investigated classroom factors with residual change in achievement (Hamre & Pianta, 2005; Morrison & Connor, 2002), few studies have modeled classroom effects on achievement growth. (Burchinal, Peisner- Feinberg, Pianta, & Howes, 2002; Pianta, Belsky, Vandergrift, Houts, & Morrison, 2008). Achievement growth, a measure that reflects student learning, is estimated by modeling linear trajectories of three or more repeated measures of achievement. Several studies have addressed school-level effects on achievement trajectories (Aikens & Barbarin, 2008; Bryk & Raudenbush, 1988; McCoach, O’Connell, Reis, & Levitt, 2006), but to our knowledge, no study investigating classroom effects on achievement trajectories has nested students within classrooms. Gaps in research on classroom effects may be due to challenges associated with collecting repeated measures of achievement during an academic year. Studies of classroom effects must also consider student-level characteristics that influence achievement trajectories. A growing and well-established

2 literature links achievement outcomes to individual differences in students’ psychosocial functioning, home environment and demographics. With the advent of longitudinal growth models, researchers have been able to tease apart the effects of student variables on students’ level of achievement at any discrete point in time versus achievement growth. Whereas starting levels of achievement are largely accounted for by between-student factors such as student poverty (McCoach et al., 2006) and parent involvement (Aikens & Barbarin, 2008), achievement growth is influenced by school factors such as school poverty (Aikens & Barbarin, 2008; Bryk & Raudenbush, 1988) or the classroom environment (Pianta et al., 2008). These findings suggest that school- and classroom-level variables may explain differences in achievement growth and should be incorporated in models that examine between-student effects on starting levels of achievement. By using repeated measures of achievement over the course of one school year, the current study will investigate classroom factors associated with achievement growth in late elementary school while controlling for student-level characteristics. Between-Classroom Differences and Achievement

Two dimensions of the classroom environment, teacher warmth and classroom order, have been identified as particularly important in promoting student learning. From a systems perspective, the classroom social climate is shaped by teacher-student relationships and classroom order. Classroom order and positive relationships are thought to promote student morale, increase interest in instructional topics, and thereby lead to improved achievement (Moos, 1991). A number of studies have linked measures of teacher warmth, order, and emotional support to achievement outcomes (Bennacer, 2000; Birch & Ladd, 1997; Burchinal et al., 2002; Fraser, 1991;

3 Fraser & Fisher, 1982; Hamre & Pianta, 2005; Pianta et al, 2008). Intervention research also indicates that safety, support, and order within the classroom are conducive to learning (Rimm-Kaufman & Chiu, 2007; Zins, Weissberg, Wang & Walberg, 2004). However, few have examined whether classroom environment impacts achievement growth. Studies of classroom environment and student achievement have used observational measures as well as teacher and student reports. Teacher reports of the quality of teacher-student relationships assess the degree of closeness and support that students experience in the classroom and have been linked to student achievement outcomes (Burchinal et al., 2002; Hamre & Pianta, 2001; Hughes, Luo, Kwok, & Loyd, 2008; O’Connor et al., 2007; Pianta & Stuhlman, 2004). Teacher-reported closeness (i.e., warmth), has positive associations with academic performance in early elementary school (Birch & Ladd, 1997) and has been associated with gains in language skills for disadvantaged minority elementary school students (Burchinal et al., 2002). These studies investigated teacher-reported relationship quality as a between-student factor as opposed to a between-classroom variable. Classroom observations have also been used to measure aspects of the classroom environment. The NICHD studies have highlighted substantial between-classroom variability in instructional and emotional support (NICHD ECCRN, 2005; Pianta, La Paro, Payne, Cox, & Bradley, 2002; Pianta, Belsky, Houts, Morrison, & NICHD ECCRN, 2007) and have linked these dimensions to student achievement (Downer & Pianta, 2006; Hamre & Pianta, 2005; Pianta et al., 2008). Instructional support captures the degree to which teachers provide instruction, encourage student responsibility, and engage students in instructional conversation. Emotional support encompasses teacher

4 sensitivity, intrusiveness, detachment, over-control, classroom climate, and classroom management. Both dimensions have been linked to achievement outcomes, particularly for at-risk students (Hamre & Pianta, 2005). In a study designed to examine the longitudinal relation between classroom quality and achievement trajectories over the course of elementary school, classroom emotional support emerged as a correlate of achievement growth in reading and math (Pianta et al., 2008). Student-reported perceptions of the classroom environment have also been examined in relation to academic achievement (Bennacer, 2000; Crosnoe et al., 2004; Dunn & Harris, 1998; Fraser, 1991; Fraser & Fisher, 1982). Student perceptions of classroom order and organization have emerged as robust predictors of achievement outcomes (Bennacer, 2000: Fraser, 1991; Fraser & Fisher, 1982). However, like the NICHD observational studies, studies using student reports have investigated the perceived classroom environment as a between-student variable (Bennacer, 2000; Dunn & Harris, 1998). One study that used aggregated perceptions of students linked these classroom environment measures to students’ aggregated academic outcomes (Fraser & Fisher, 1982). Few studies have used multi-level modeling to nest students within classrooms or have aggregated student reports to test the degree to which perceptions of the classroom are shared by all students (e.g.,Verkuyten & Thijs, 2002). The classroom environment is shaped in part by the demographics of the students who compose the class. When student demographics are aggregated at a school level, schools with greater proportions of students from high socio-economic backgrounds tend to have higher achievement test scores (Fowler & Walberg, 1991). School-level SES explains variance in achievement scores above and beyond

5 individual characteristics, including the socio-economic status of the individual student (Ma & Klinger, 2000; Willms & Raudenbush, 1989). In one of the first studies to examine school-level poverty effects on achievement trajectories from first to third grade (Bryk & Raudenbush, 1988), school poverty was related to not only to starting levels of reading and mathematics achievement in first grade, but also to rates of reading achievement growth. More recently, Aikens and Barbarin (2008) examined the extent to which family, school, and neighborhood factors accounted for the impact of socioeconomic status on students’ early reading. Family factors accounted for starting reading levels; however, school and neighborhood poverty were more strongly associated with rates of growth in reading (Aikens & Barbarin, 2008). Between-Student Differences and Achievement

Several student-level variables should be considered when examining the effects of classroom environments on student learning. Students’ disruptive behavior and exposure to peer victimization have been repeatedly linked to lower achievement levels and may also impede students’ school engagement and rates of achievement growth. The effect of disruptive and aggressive behavior on student achievement has been extensively investigated (Hinshaw, 1992; Trzesniewski, Moffitt, Caspi, Taylor, & Maughan, 2006) and implicated in poor performance on achievement tests (Chen, Rubin, & Li, 1997; Jimerson, Egeland, & Teo, 1999), poor academic competence in adolescence (Masten et al., 2005), and lower rates of high school graduation (Kupersmidt & Coie, 1990; Risi, Gerhardstein, & Kistner, 2003). Peer victimization during late elementary school has been implicated in poor school adjustment (Graham, Bellmore, & Mize, 2006; Juvonen, Nichina, & Graham, 2000), lower achievement levels (Schwartz, Chang, & Farver, 2001) and residual change in student achievement

6 (Buhs, 2005; Buhs, Ladd, & Herald, 2006; Schwartz, Gorman, Nakamoto, & Toblin, 2005). Aspects of the home environment may also influence students’ motivation and ability to learn. Parent support for academics and involvement during elementary school has been associated with better teacher reports of academic progress (Englund, Luckner, Whaley & Egeland, 2004), grades (Rogers, Theule, Ryan, Adams, & Keating, 2009), and lower rates of high school dropout (Barnard, 2004). Meta- analyses reveal a small to moderate relationship between parent involvement and academic achievement (Fan & Chen, 2001) and, among urban elementary students, a moderate to large relationship (Jeynes, 2005). Studies linking parent involvement to achievement growth are less conclusive. Parent involvement has been associated with increases in literacy from kindergarten to 5 th grade (Dearing, Kreider, Simpkins, & Weiss, 2006) but, in a separate longitudinal study of reading trajectories, parent involvement was unrelated to rates of reading growth from kindergarten to 3 rd grade (Aikens & Barbarin, 2008). Sleep quantity and quality have also emerged as factors that impact school performance and learning (Curcio, Ferrara, & De Gennaro, 2006; Mitru, Millrod, & Mateika, 2002; Wolfson & Carskadon, 2003). Although chronic sleep disturbance may be due to biological problems (e.g., asthma, sleep apnea), poor sleep hygiene might also reflect aspects of the home environment such as the degree to which parents monitor and structure sleep routines or the likelihood of disruptions due to a chaotic or crowded living environment, which could influence the quality and quantity of a child’s sleep (Buckhalt, El-Sheikh, & Keller, 2007; Sadeh, Raviv, & Gruber, 2000). Regardless of their origin, sleep problems may contribute to difficulties at

7 school. Sleep quality has been linked to cognitive functioning (Buckhalt et al., 2007), school functioning (Meijer, Habekothe, & Van Den Wittenboer, 2000), and achievement outcomes (Meijer, 2008). Students’ ethnicity and social class often account for variability in achievement outcomes. Although the size of racial and ethnic achievement gaps have fluctuated over time, research suggests that differences in achievement levels of disadvantaged minority versus non-minority students persist (Lee, 2002). Socio- economic status is a consistent and strong predictor of academic achievement, such that economically disadvantaged children are more likely to achieve at lower levels than their peers (Duncan & Brooks-Gunn, 2000) and are more likely to experience downward deflections (i.e., negative residual change) in achievement between first and sixth grade (Jimerson et al., 1999). A final student-level factor that accounts for differences in achievement outcomes is special education status. Research indicates that special education status is negatively associated with performance on achievement tests (Reynolds & Wolfe, 1999) as well as deflections in achievement during elementary school (Jimerson et al., 1999). Research on cross-level interactions between student level variables and classroom context has typically focused on behavioral outcomes, such as aggressive behavior, academic focus, and social behavior (Barth, Dunlap, Dane, Lochman, & Wells, 2004; Bennett, Elliott, & Peters, 2005; Chang, 2004) or the quality of teacher- student relationships (Buyse, Verschueren, Doumen, Van Damme, & Maes, 2008) and achievement motivation (Lau & Nie, 2008). Yet, several studies indicate that aspects of the classroom environment may moderate achievement outcomes for students at risk for school difficulties. Burchinal et al. (2002) found that African-American

8 children who had close relationships with their teachers gained language skills in early elementary school. Morrison and Conner (2002) reported that first grade students with poor word decoding skills demonstrated gains in word decoding when placed in classrooms in which instructional activity was primarily directed by the teacher (teacher-managed instruction) and performed worse in classrooms in which instructional activity was primarily controlled by the child (child-managed instruction). Hamre and Pianta (2005) found that at risk students in first grade classrooms with high levels of instructional and emotional support had achievement scores and teacher-student relationship quality commensurate with low-risk peers by the end of the school year. Summary and Aims

In sum, there are few studies that consider the effects of classroom context on students’ achievement growth over the course of a school year. This study is among the first to use a three-level hierarchical design to examine two aspects of the classroom environment, order and teacher warmth, as factors that promote student learning. By using three repeated measures of achievement during a single school year, the design represents an improvement over studies that employ a single measure of student achievement or residual change scores that are generally spuriously and negatively correlated with initial status (Bryk & Raudenbush, 1987). Further, by aggregating student perceptions within classrooms, the study measures shared aspects of the classroom environment. Aggregation of student reports within a classroom has the potential to provide an efficient, scalable approach to tapping important classroom dimensions linked to student learning. Finally, the three-level design allows for testing of classroom level effects while controlling for student-level factors that have been

9 previously linked to achievement. It also facilitates analysis of the cross-level interaction (or “fit) between classroom environments and individual student characteristics (Bryk & Raudenbush, 1988). This study has three aims. The first is to identify dimensions of the classroom environment that account for variability in growth in student achievement. We expect that classrooms high in order and teacher warmth will promote faster rates of achievement growth and that students in high poverty classrooms will grow at slower rates. The second aim is to test whether classroom factors account for differences in achievement trajectories above and beyond student-level factors (interpersonal functioning, home environment, demographic characteristics) that commonly account for achievement level. We anticipate that, while disruptive behavior, peer victimization, parent involvement, sleep problems, and demographics will explain some differences in students’ achievement trajectories, classroom factors will account for additional variability in achievement outcomes than student predictors alone. The final aim is to examine whether at-risk students’ learning benefits more from some types of classroom environments than from others (e.g., classroom factors may moderate the effect of minority status on students’ rates of achievement growth).

10 Chapter 2 METHOD Participants

A total of 893 students (386 fourth graders and 507 fifth graders) from 39 classrooms in seven schools within an urban-suburban public school district participated in this study. Approximately one-third of the sample was enrolled in one of two intermediate schools located in a small city within the school district, while the other two-thirds of the sample were enrolled in elementary schools in a suburban location. The sample was evenly distributed by gender (49.3% female), predominantly minority (43.0% African-American, 13.7% Hispanic, and 6.2% Asian-American), nearly half of the students qualified for free or reduced lunch assistance programs (48.3%), and 14% were in special education. Regular education classes were recruited to participate in this study, the majority of which integrated special education students. The proportion of special education students within study classrooms ranged from 0% to 39%. Thirty-six of the 39 homeroom teachers completed on-line surveys for each of the students in their class. There were no differences in demographic characteristics, achievement, interpersonal functioning, home environment, or classroom environment for the 68 students with missing teacher data. Procedure

Seven elementary and intermediate school building principals volunteered to participate in the study. The University’s Institutional Review Board approved a

11 waiver of parental consent. As required by the waiver, no identifying information about students was provided to or collected by the researchers. Study data (student surveys, teacher surveys, MAP assessments and demographic data from the school district) were linked solely by student identification numbers. Two weeks prior to the scheduled data collection, fourth and fifth grade students at participating schools were provided with a letter to their parents informing them of the study. The letter instructed parents to contact their child’s teacher or building principal if they were unwilling to allow their child to participate. Student surveys were completed during the fall in computer classrooms at each school. Students were provided with oral as well as on-screen written instructions about the voluntary and confidential nature of the survey. They were asked to raise their hands at any time during the survey if they did not understand a word, question, or were unwilling to complete the survey. Graduate and undergraduate research assistants were available at each data collection to answer student questions. The survey included 75 items and took students an average of 17 minutes to complete. Fourth and fifth grade homeroom teachers were recruited to participate in the study via e-mail. Teachers who agreed to participate were sent an e-mail with a link and directions for completing the 28-item survey for each student. Teachers were reimbursed with a payment of $5 for each survey they completed. Measures

Student Demographic Characteristics

Student gender, disadvantaged minority, free-/reduced-lunch, and special education data were provided by the school district. Each of these variables was dummy coded.

12 Interpersonal Functioning

Measures of peer victimization and disruptive behavior were derived from items that assessed the frequency with which specific interpersonal events occurred during the past week at school (Esposito, Kobak, & Little, 2005; Little & Kobak, 2003). Students were given the following directions: “Think about the past week at school. How often did each of the following events happen during the past week at school?” Four response choices were provided for each event: (1 = 0 times, 2 = 1-2 times, 3 = 3-5 times, 4 = 6 or more times). Peer victimization. Students reported on four items based on the Perceptions of Peer Support Scale which measures the frequency of negative peer events associated with victimization experiences (PPSS; Kochenderfer & Ladd, 1996). Peer victimization items included: “Another student picked on me,” “Another student said mean things to me,” “Another student said bad things about me to other students,” and “Another student hit or pushed me.” All items were rated on a 1 to 4 scale with higher values indicating more frequent peer victimization experiences and were averaged to form a composite (M = 1.73, SD = .79). The measure had good internal consistency in this sample, α = .83. Disruptive behavior. Students reported on three items measuring the frequency with which they engaged in disruptive behavior, as well as four items measuring the frequency of aggression towards peers. The items were based on a measure of negative disciplinary interactions between students and teachers (Esposito, Kobak, & Little, 2005; Little & Kobak, 2003) and a measure of peer aggression (BASC; Reynolds & Kamphaus, 2002). Examples of the disruptive behavior and aggression items include: “Was sent out of class by a teacher” and “Teased another

13 student.” All items were rated on a 1 to 4 scale with higher values indicating more frequent disruptive-aggressive behavior and were averaged to form a composite (M = 1.37, SD = .53). The measure had good internal consistency in this sample, α = .87. Teachers reported on students’ aggressive behavior with a composite of eight items selected from the Achenbach Child Behavior Checklist - Teacher’s Report Form (TRF; Achenbach & Rescorla, 2001). Three response choices were provided for each item: (0 = not true, 1 = somewhat or sometimes true, 2 = very true or often true). The eight aggression items were averaged (M = .20, SD = .40) and had an internal consistency of .93. Student reports of disruptive behavior and teacher reports of aggression were significantly correlated (r = .51, p < .001). Therefore, the student and teacher measures were aggregated by standardizing both variables and calculating the mean of the two standardized variables. As shown in Table 1, skewness and kurtosis coefficients were calculated for each of the study variables. Variables with skewness or kurtosis coefficients greater than 1.0 were log transformed. After transformation, the skewness and kurtosis coefficients for the peer victimization variable were reduced to .52 and -.90 respectively. The transformed disruptive behavior variable had skewness and kurtosis coefficients of .83 and -.26 respectively. Home Environment Measures

Parental involvement in academics. Students reported on parental involvement in their academic work with five items developed based on research of parental involvement at school (Fan & Chen, 2001; Hong & Ho, 2005). Students were asked to rate how true statements were in regards to their parents’ involvement. Statements included: “My parent helps me with my homework” and “My parent talks

14 with my teachers.” Four response choices were provided for each item (1 = not at all, 2 = a little, 3 = somewhat, 4 = a lot). The items were averaged (M = 3.20, SD = .60) with higher scores indicating greater parental involvement in academics. The internal consistency of the measure in this sample was α = .68. Sleep problems. Students reported on the quality of their sleep during the past two weeks with eight items derived from the School Sleep Habits Survey (Wolfson & Carskadon, 1998). Five response choices were provided for each item: (1 = never, 2 = once, 3 = twice, 4 = several times, 5 = every day/every night). The items were averaged (M = 2.31, SD = .75) to provide a general measure of sleep quality with higher scores indicating poorer sleep quality. The internal consistency of the measure in this sample was α = .73. Correlations between the student demographic, interpersonal functioning, and home environment measures are presented in Table 2. Disadvantaged minority and free-/reduced-lunch students reported higher levels of disruptive behavior in school than their peers. Special education students tended to report more difficulties with interpersonal functioning and less parental involvement than their regular education peers. Interpersonal problems were highly correlated and also associated with sleep problems. Boys and girls did not differ in achievement scores and only moderate gender differences were evident in student reports of disruptive behavior and parent involvement in academics. Therefore, gender was not considered in subsequent analyses.

15 Classroom Environment

Teacher warmth. Students reported on teacher-student relations with four items derived from the School Climate Survey (Bear, 2006). Teacher warmth items included: “Teachers treat students with respect,” “Teachers care about students,” “I like my teachers,” and “Teachers let you know when you are doing a good job.” Students chose between four response options: (1 = disagree a lot, 2 = disagree, 3 = agree, 4 = agree a lot). The items were averaged (M = 3.39, SD = .61) with higher scores indicating a higher degree of teacher warmth. The scale had an internal consistency of .79 in this sample. Classroom means of the student-reported teacher warmth variable were calculated. Teacher warmth scores ranged from 2.79 to 3.78. Classroom order. Students reported on order in their classroom with a composite of three items derived from the Classroom Environment Scale (CES; Trickett & Moos, 1974). Classroom order items included: “Students fool around a lot in this class,” “The teacher often has to tell students to calm down,” and “Students interrupt the teacher when he/she is talking.” Items were measured on a 1 to 4 scale and reverse-coded so that higher scores indicated greater order. The items were averaged (M = 2.10, SD = .79) and had an internal consistency of .76. Classroom means of the order variable were calculated by aggregating individual student reports. Classroom order scores ranged from 1.51 to 3.16. In order to measure the degree to which students nested within the same class shared perceptions of the classroom, intra-class correlations for teacher warmth and classroom order were calculated (see Table 1). The Spearman-Brown formula applied to the ICC estimates the reliability of the class-mean rating (Ludtke, Robitzsch, Trautwein, & Kunter, 2009). Based on Spearman-Brown calculations using an average class size of 23, the reliabilities of the class-mean ratings for teacher

16 warmth and classroom order were .66 and .85 respectively. Although the reliability of the class-mean for teacher warmth is somewhat low the reliabilities of the aggregated student perceptions are satisfactory. Classroom Composition

Grade. The grade level of each classroom was dummy-coded (0 = 4 th

grade; 1 = 5 th grade) and included as a control variable for between-classroom differences. Seventeen fourth grade classrooms and 22 fifth grade classrooms were represented in the study. Classroom poverty. The percentage of students who qualify for free- /reduced-lunch assistance was calculated for each classroom. The percentage of classroom poverty ranged from 18.5% to 88.5%. Academic Achievement

Student achievement was assessed using the Measures of Academic Progress (MAP; Northwest Evaluation Association), a state-aligned, computerized, adaptive, RIT (Rasch Unit)-scaled assessment program. MAP assessments are developed from a large pool of items that have been calibrated for their difficulty on the RIT scale (Cronin, Dahlin, Adkins, & Kingsbury, 2007). This scaling approach enables users to measure student performance and growth over time and across grade. State-aligned tests are created by reviewing state standards and selecting a smaller pool of items that reflect those standards. Each MAP assessment is adaptive in design so there are no ceiling or floor effects, and items reflect a student’s current performance rather than their grade level.

Full document contains 64 pages
Abstract: This study uses a three-level model (within-student, between-student, and between-classroom) to examine the effects of 4th and 5 th grade classroom environments on student achievement trajectories during the school year. Between-classroom differences in teacher warmth and classroom order were tested as predictors of student rates of achievement growth, controlling for classroom poverty as well as student characteristics. Classroom order and poverty added incrementally to students' rates of achievement growth when student level demographic and behavioral effects were included in the model. Cross-level analyses identified the moderating effects of classroom environment on achievement growth for at-risk students with higher levels of classroom order promoting greater rates of math achievement growth among disadvantaged minority students.