To encourage the spread of high-quality summer learning programs, The Wallace Foundation launched the More Time for Learning initiative in 2010. As part of that effort, The Foundation has selected six urban districts for a summer learning demonstration project. ]The goal of the summer learning demonstration is to provide low-income children with summer programs that combine academics and enrichment. It also aims to provide policymakers with evidence on whether and how districts can eliminate summer learning loss and produce lasting academic gains. In summer 2011 and summer 2012, The Foundation supported voluntary summer school programs in each of the five districts and program improvements in preparation for a randomized controlled trial (RCT). The RCT will gather evidence regarding the effectiveness of the program. Students selected to participate in programming will do so for two consecutive summers -- in 2013 and 2014. The study will compare academic and non-academic results for those who are selected versus those who are not selected to understand the effectiveness of the program. Results from the study will help districts improve their voluntary summer learning programs and provide evidence regarding effectiveness that could help districts across the nation make good decisions about summer programs for their students.

This research project is designed to explore and understand teaching from the social justice perspective. The study seeks to explore the factors that contribute to why teachers will use this perspective in their classrooms, the perception of students and its effects on student achievement. The project will employ quantitative techniques that harness the expertise of the two principal investigators with experience in teaching and evaluating teachers as a principal as well as educational statistics. The study will focus on the CLASS protocol scores as our independent observations of teaching from a social justice perspective and the student TRIPOD survey with the 7Cs (Care, Control, Clarify, Challenge, Captivate, Confer, and Consolidate) as the student perceptions. The research will use school and teacher characteristics to predict the likelihood of teaching from this perspective. The project will also use student and school characteristics as controls to predict the effect of teaching from the social justice perspective on student achievement. The study will also examine whether the teaching perspective may have a differential effect on at-risks students.

In this project, we intend to open the "black box" of teacher value added using data from MET. During the last decade the federal government and many states have taken a series of steps to hold schools accountable for the performance of their students. The implementation of these policies has drawn the attention of many social scientists, leading to a prolific literature in economics on teacher effectiveness. However, most articles have characterized teacher effectiveness using fixed/random effects. While this type of technique can be very helpful to identify "good" or "bad" teachers, it does not provide any information regarding teaching practices that lead to better student outcomes. First, we intend to determine whether more detailed data at the classroom/teacher level can help to explain variation in teacher effectiveness. Because MET provides detailed information on teacher practices and student characteristics, it constitutes a unique opportunity to analyze in more detail the different determinants of teacher effectiveness. Second, we would like to study whether the effectiveness of teaching methods varies by the composition of the peer group. For example, some teachers may emphasize vertical teaching practices (i.e. teachers primarily lecture, students take notes or read textbooks, and teachers ask students questions), while others prefer horizontal practices (i.e. students work in groups, do projects together). Most likely these "styles" will have different impacts on the learning process. Furthermore, peers may be more important in a context of horizontal teaching practices, where the interactions between students are a key component of the learning process.

To encourage the spread of high-quality summer learning programs, The Wallace Foundation launched the More Time for Learning initiative in 2010. As part of that effort, The Foundation has selected six urban districts for a summer learning demonstration project. ]The goal of the summer learning demonstration is to provide low-income children with summer programs that combine academics and enrichment. It also aims to provide policymakers with evidence on whether and how districts can eliminate summer learning loss and produce lasting academic gains. In summer 2011 and summer 2012, The Foundation supported voluntary summer school programs in each of the five districts and program improvements in preparation for a randomized controlled trial (RCT). The RCT will gather evidence regarding the effectiveness of the program. Students selected to participate in programming will do so for two consecutive summers -- in 2013 and 2014. The study will compare academic and non-academic results for those who are selected versus those who are not selected to understand the effectiveness of the program. Results from the study will help districts improve their voluntary summer learning programs and provide evidence regarding effectiveness that could help districts across the nation make good decisions about summer programs for their students.

This research investigates different methods for quantifying teacher effectiveness, specifically value added models (VAMs). Educational measurement methods are best tested and researched using real data. The use of the Longitudinal Database from Measures of Effective Teaching (MET) project would enhance the results for the current NSF funded grant: RealVAMs and other closely related research projects (IES and other) by allowing us to compare and contrast varying estimates of teacher effectiveness. Using the data, we will apply a multidimensional VAM (MVAM), and compare the estimates from the multidimensional model to the teacher effectiveness estimates reported in the MET study.

Improving student engagement is a current focus of schools in many countries. Yet, empirical evidence on the relationship between the social influences of schools and teachers' collective efficacy for student engagement is limited. This study seeks to examine the relationship between the social variables of schools (perception of leadership, professional development, and the use of feedback) and teachers' collective efficacy for student engagement. Extant data from 276 teachers in six large school districts in the United States will be supplied through the Measures of Effective Teaching project. Specifically, we will use multiple regression to analyze teacher survey data from the Teacher Working Conditions Survey.

This project will utilize the MET data to examine an initial validity argument for the application of the Developing Mathematical Thinking (DMT) observation protocol as a measure of mathematics instructional quality. The instrument was developed by the Initiative for Developing Mathematical Thinking (IDMT) group at Boise State University over the past several years. It is based on a social-constructive instructional framework and was built upon over multiple professional development projects. The framework focuses on the following five dimensions of practice; (1) taking students' ideas seriously, (2) encouraging multiple strategies and models, (3) pressing students conceptually, (4) addressing misconceptions, and (5) focusing on the structure of the mathematics. The research consists of three phases. Phase one, expert raters will score videos during this phase to serve as standards during the phase two observer training and scoring process. Phase two consists of training observers followed by observations of the MET video files to establish scores for the five dimensions of the DMT observation instrument and an overall score. This data will be utilized to examine the relationship between expert raters' and observers' scores, interrater reliability, and statistical scaling of theoretical constructs. Lastly, during phase three the MET data will be used in conjunction with the DMT observation protocol data collected in phase two to evaluate convergence and divergence of related and unrelated traits respectively. It is expected that across data collection methodologies similar dimensions from other measures of teaching quality will demonstrate convergent evidence and that unrelated traits will demonstrate divergent evidence.

Assessment of individuals' proficiency at complex tasks is often accomplished by observation and rating. Teachers or testing agencies, for example, rate students' essays and their solutions to complex problems in mathematics and science. Ratings, however, may change over time due to changes in the way the rater perceives the work and/or changes in individuals' proficiency. The material being rated also may reflect more than one dimension of proficiency. Finally, summaries of these ratings may be misleading when the data collection design includes groupings (schools, hospitals, etc.) that introduce extraneous statistical dependence into the rating data. This project will expand the Hierarchical Rater Model (HRM), a multilevel item response theory model that accounts for dependencies between multiple ratings of the same work, into a framework that will accommodate (a) variation in ratings over time; (b) multidimensional assessments; and (c) clusters and other hierarchical structure introduced by the data collection design. This new framework will allow the HRM to provide estimates of the overall proficiencies of individuals on the rated tasks, as well as estimates of precision, accuracy, and other rater characteristics, under a broad variety of practical rating situations. Analytical work, simulation studies, and real data applications will be used to explore and demonstrate the feasibility and applicability of the expanded HRM framework. The research will culminate with a new HRM framework with unified notation and formulations so that researchers may specify and estimate special cases of the generalized model as needed.

We explore the role of peers in contributing to the achievement gap as students age. We do this in the context of a dynamic model, which accounts for human capital accumulation and the role of peers to vary with students' ages. We also allow peer effects to vary by the race and ability of the students. An important confounding factor is that teacher quality is generally unobserved, making it difficult to separate an effect of peers from teachers. Modeling the human capital accumulation process provides new insight into how to identify peer effects even when there is nonrandom assignment to teachers. Furthermore, detailed information on teacher effectiveness permit new ways of controlling for teacher quality. We corroborate the effectiveness of our method by comparing results when students are randomly assigned to teachers to when there is nonrandom assignment. We use our parameter estimates to quantify the contributions of peers and teachers to the achievement gap at different ages. The project is consistent with the goals of the MET project because understanding the role of peers is a crucial element of understanding teacher effectiveness.

High quality instruction is necessary for students of all ages to develop a deep understanding of mathematics. To truly understand both a teacher's impact on his/her students and how best to improve student learning, a richer picture of the classroom experience than can be provided from test scores is required. This dissertation analyzes how learning occurs in classrooms from two viewpoints: 1) from an individual perspective and 2) from a classroom perspective. The first perspective views learning as an individual process and seeks to explain the differential effect of instruction on student learning via students' perceptions of the learning environment. The second part of this dissertation considers how classroom-level achievement gains can be understood as arising from patterns of instructional practices and suggests that there are multiple pathways for instruction to produce learning. The data to be used in this study come from coded videotaped observations of up to 2,000 fourth through ninth grade mathematics instructors from the Measures for Effective Teaching (MET) study (2009-2011). Videos were coded using three observation protocols and students were surveyed once during the school year about their perceptions of the classroom. Despite the identification of certain best practices in mathematics instruction, researchers and policymakers fail to understand how several aspects of mathematics instruction work together to yield gains in student achievement. Combining instructional practices and situating them within a classroom context allows researchers, practitioners, and policymakers to gain a better understanding of the complex phenomena surrounding classroom instruction.

The project will examine the dimensionality of student survey measures and classroom observation scores using data collected with the Tripod student surveys and the Framework for Teaching and the Class observational frameworks. Findings will be compared with analyses using data from outside of the MET project.

High-quality teacher-student relationships in elementary school has been linked to academic achievement (Hamre & Pianta, 2001) and children's feelings of well-being, academic engagement, and performance (Hamre & Pianta, 2006). Relationship characteristics such as caring, empathy, and mutual respect serve as protective factors, particularly for students of color and those from economically disadvantaged backgrounds. The proposed project will examine if teacher student interactional quality is more a function of student sorting or a function of teacher quality in economically disadvantaged students in grades 4 through 8. There is no other dataset that provides these relationship measures coupled with student outcomes and teacher randomization. We will use multiple measures to help inform whether the teacher student relationship quality has a causal impact on economically disadvantaged student outcomes, including engagement and academic achievement. Leveraging the randomization along with two years of student and teacher demographic information will be used to identify if teacher interactional quality has an impact on student outcomes, including engagement and academic achievement. We plan to assess the impact of academic gains for students from economically disadvantaged backgrounds by accessing student status such as free-reduced lunch and value-added measures. Specific data on subgroups will help inform generalizability of the findings and determine how representative the analytic sample is of the district as a whole. Observational data, another measure of effectiveness, will be used to examine interactions in the classroom, classroom environment, and teachers' reflections, such as emotional support, classroom organization, and instructional support.

Recent evidence from economics and psychology highlights the importance of traits other than general intelligence for success in school and in life (Almlund et al., 2011; Borghans et al., 2008; Moffitt et al., 2011), and disparities in these noncognitive skills appear to contribute to the academic achievement gap separating wealthy from disadvantaged students (Evans and Rosenbaum, 2008). In recent years, educators and policymakers have become interested in measuring and developing students' noncognitive skills (see, e.g. Yeager et al., 2013); however, there is little agreement on which traits are most important and their malleability in school settings. Therefore, I hope to shed light on this topic by examining two primary questions: 1. What is the relationship between students' noncognitive skills and student achievement? 2. Do schools (and teachers) have measurable effects on students' noncognitive skills? Specifically, two student noncognitive measures will be at the core of my study: Grit and Implicit Theory of Intelligence (i.e. "Growth Mindset"), provided through student survey data as part of the Measures of Effective Teaching (MET) project. My analysis will explore a variety of education production function models in a regression framework, with an aim to create value-added models of grit and growth mindset which estimate the teacher and school effects on these noncognitive student outcomes. My goal is to understand whether teachers and schools identified as most effective at raising student test scores are also the most effective at improving other noncognitive student outcomes.

The Pilot Study of an Effective Teaching and Cognitive Science Video Scoring Scheme is designed to address recent interest in the application of cognitive science research about learning processes to the improvement of teaching practice. While theoretical and rhetorical arguments have been made to bolster the idea that teachers whose instruction is congruent with learning principles from cognitive science would be more effective than teachers whose instruction is not, there is little empirical evidence at the classroom level to support this argument. Further, the extent to which key learning principles from cognitive science have been integrated into teaching practice is unknown. This study will develop and pilot a new classroom observation instrument -- The Cognitive Principles of Learning (CPOL). The CPOL instrument will be used to score videos of two mathematics lessons for 50 different 4th and 5th grade teachers who participated in the Measures of Effective Teaching (MET) project. The instrument will focus on the degree to which teachers' instruction is congruent with a set of 10 principles of learning that have been demonstrated to produce efficient, long-lasting, and deep learning in basic cognitive studies of learning and memory: Anchoring, Cognitive Disequilibrium, Guided Instruction, Multiple Examples, Quizzing, Segmentation, Self-Explanation, Signaling, Variable Practice, and Worked Examples. Teachers' scores on the instrument will be used to examine relations among instructional practice, cognitive science, and student achievement gains. The results of this study will contribute new knowledge to both the fields of education and cognitive science.

Student learning largely depends on the quality of teaching they receive at schools. Different student populations (such as English language learners versus non-English language learners and students with disabilities versus students without disabilities) may require teachers with different expertise in teaching. We aim to examine the consistency of effectiveness measures for teachers teaching different student populations using the Measures of Effective Teaching Longitudinal Database (MET LDB). Specifically, we will study: 1) Whether teacher value-added scores are consistent when they teach different student populations; 2) Whether teacher classroom observation ratings are consistent when they teach different student populations; 3) Whether the relationships between value-added scores and classroom observation ratings are consistent when teachers teach different student populations; 4) How teacher characteristics are related to their effectiveness measures when they teach different student populations. The results of this study contributes to our understanding of the fairness and validity of effectiveness measures for teachers teaching different student populations.

The 3 IU School of Education faculty who will work on the project have different research questions in mind, all are related to evaluating teaching and its impact on students. We propose to explore differences between instruments for video assessment side and for standardized testing. First, 1 member of the team will investigate the quality of mathematics teachers' instruction and how it develops across time. Second, focusing on the sample of biology videos, another team member will focus on identifying elements of inquiry instruction and investigate the relationship between inquiry teaching and student outcomes. Finally, one member of the team plans to look at the sensitivity of the links to different methods of computing value-added.

Through the Race to the Top and Teacher Incentive Fund grant programs, as well the Elementary and Secondary Education Act flexibility waivers, the U.S. Department of Education has emphasized the policy of evaluating educator effectiveness and providing educators useful and timely feedback needed to improve practice and, ultimately, student achievement. The current study is an intervention study designed to examine the implementation and impacts of a package of performance evaluation system components that include features that are currently promoted in policy discussions. The evaluation system components include measures of student achievement growth, classroom observations, and measures of principal leadership. Based on these measures, teachers, leaders and districts will receive timely and constructive feedback on teacher and principal performance. The components are being implemented by the study's implementation team in a subset of schools in a sample of districts that do not already have an evaluation system similar to that being studied. The study will address the following key research questions:

• What is the impact of the performance evaluation system on student achievement? On teachers' classroom practices? On teacher mobility? On the nature and extent of professional development activities pursued by teachers and principals?
• What are districts' and educators' experiences with implementation?

Improving student achievement in science by focusing on curricular and classroom practice has long been a focus of educational reform in the United States. In particular, advocates for reform encourage reformed teaching practices that are (a) standards based, (b) inquiry oriented, and (c) student centered. The Next Generation Science Standards and Framework for K-12 Science Education embed reformed teaching as a central component of science education. Recent efforts have investigated teacher implementation of reformed teaching practices and the relationship between reformed teaching practices and student achievement but have been limited with respect to size, context, assessment, and randomization of students. This study aims to extend previous research by examining the extent to which teachers enact reformed teaching practices, the relationship between teaching enactment of reformed teaching and student achievement, and the teacher- and school-level variables that are associated with reformed teaching in the sample of biology teachers in the MET longitudinal database. The main research questions are: (1) To what extent do teachers implement reformed teaching practices in science? (2) What is the relationship between teacher enactment of reformed teaching and student achievement? (3) What school and teacher level variables are associated with reformed teaching practices in science? Student achievement measures, video recorded classes, and surveys from 9th grade biology teachers in the MET database will be used. This study will use the Reformed Teaching Observation Protocol to rate videos as a measure of enactment of reformed teaching practices.

Research has corroborated the common perception that being taught by an effective teacher has important consequences on student outcomes. As a result, the unequal access to effective teaching is a long-standing policy concern and recent public and private efforts to close the achievement gap between disadvantaged and more advantaged students increasingly focus on redistributing effective teachers. As the pool of high quality teachers might not be easily expanded, at least in the short term, and it is not clear that most effective teachers will also be as effective when faced with a different classroom composition, identifying optimal re-assignment policies to increase overall student outcomes while reducing the achievement gap is not straightforward. To address this challenge this project follows methods developed in (Graham et al., 2011) and apply them to identify the most promising teacher assignment policies or teachers of diverse quality that could help reduce the student achievement gap without sacrificing overall student outcomes. Our methods will be applied to data from the Bill and Melinda Gates Foundation Methods for Effective Teaching (MET) project. This application will help us analyzing the results and feasibility of the teacher re-assignment policies recommended by our research, and the sensitivity of the results to alternative measures of teaching quality. In addition, the randomization component of the project during the second year is a key feature of the data that will help identification in our methods.

Few studies analyze teacher report of working conditions as a means of exploring underlying social and emotional implications for teacher performance. This study will examine the relationship between teacher perceptions of working conditions and effective teaching. Data were collected from fourth and fifth grade teachers (n=470) in both years of the Measures of Effective Teaching (MET) project study. Data for year 1 and 2 is analyzed separately. Descriptive statistics are reported for teacher working conditions. Next, factor analyses are used to determine underlying social and emotional constructs in the survey data. Finally, the strength of association between these factors and observed teacher effectiveness are explored using structural equation modeling. Implications for the findings are discussed.

The purpose of this study will be to examine the relationship between classroom emotional climate and academic achievement in the areas of reading and math for fourth and eighth grade special education students participating in the Measures of Effective Teaching (MET) project. In looking at the relationship between classroom emotional climate and academic achievement for students receiving special education students, a non-experimental, cross-sectional, predictive study will be conducted. Through the act of teaching and spending time in a shared space, teachers and students interact with each other. These interactions result in the formation of relationships between the teacher and students. Classroom emotional climate is the result of those relationships and can be defined as "the extent to which the classroom climate is characterized by positive relationships, enjoyment and excitement, feelings of comfort, and experiences of appropriate levels of autonomy" (Reyes, Brackett, Rivers, White, & Salovey, 2012, p. 704). Further, classroom emotional climate can be categorized as positive or negative (Hafen et al., 2014). Unfortunately, students receiving special education services do not always achieve at the same rate as their non-disabled peers (U.S. Department of Education, 2013). As students with unique learning needs, special education students may be more sensitive to factors that impact academic achievement. Although literature exists describing the relationship between classroom emotional climate with academic achievement of general education students, there is little research explaining the impact of emotional climate on students with disabilities. Results from the proposed study will provide needed insight into the issue.

We have requested access to the database to further validate and develop an instrument that we are using for part of our field observation protocol, gathering data about classroom teachers' work for the longitudinal mixed methods study, "An Exploration of Novice Teachers' Core Competencies: Impact on student achievement, and effectiveness of preparation." Licensure policies and accreditation requirements at the national and state levels described expectations for the knowledge, skills, and dispositions that are presumed important to teachers' eventual success in the classroom. These expectations represent "Core Competencies" (CCs). Previous research on CCs is limited in that expectations have been determined by studying high quality teachers only, often selected based on principal recommendations. The purpose of this study is to provide additional information describing the relationship between novice teachers' CCs and student outcomes. Using surveys, transcriptions, analysis of program documents (including assessments, classroom observations), and statistical modeling, the researchers will answer two questions. First, can teachers' exposure to the CCs as taught in teacher preparation programs be validly and reliably described and quantified? Second, what is the relationship between teachers' exposure to the CCs as taught in teacher preparation programs and students' academic achievement growth in K12 settings? The team will first design survey items and document coding protocols to assess each competency. After administering the survey, the team will evaluate the reliability and validity of the resulting measures. The team then plans to collect data from surveyed teachers, professors and other personnel in preparation programs preparing teachers, and the students of program graduates teaching in K12 settings, to explore whether students' achievement is related to teachers' measured CCs.

The classroom is a foundational place to build literacy skills for both fluent and language minority students. One particularly important feature of the classroom environment centers around the ways in which teachers engage students within discussion and talk. Although research has established guidelines that encourage talk (Goldenberg, 1992), such recommendations are not making their way into classrooms. "Good classroom discussions are notable not only for their desirable attributes, but also for their rarity,"(Goldenberg, 1992, p. 318). This is particularly challenging as our new educational standards movement, the Common Core, demands critical thinking, reasoning, and evaluation that often stems from high quality classroom discussions. Currently, researchers report that teachers are doing the majority of talking within classrooms, with estimates suggesting teachers embody 75% of the talk within a classroom and the 20 to 30 students within the classroom share the remaining 25%. Our research aims to analyze a large dataset of classroom videos (Measures of Effective Teaching Longitudinal Database) in order to determine the discourse features currently enacted within classrooms across different content areas. In particular, we are interested in the characteristics of classroom discourse such as the ratio of teacher to student talk and examining what the talk consists of as well as the mediators of language use such as the teacher moves, materials, gestures, nonverbal communication, movement, questioning techniques, management structures, groupings, instructional context and other factors that promote high quality student talk. We will also link these aspects of classroom discourse with student performance on academic achievement measures.

As spurred by Race to the Top, the states are increasingly focused on developing innovations and reforms to ensure equitable distribution of effective teachers among schools. Hence it is important for the policy makers to get a better understanding of how teacher quality and effectiveness differ across schools. Empirical studies have only begun to analyze the teacher effectiveness gap between high-need and low-need schools. Very few prior studies have examined the impact of working conditions on the gap in teacher effectiveness and turnover patterns. High turnover is highly indicative of less effective teaching-learning environment. Earlier researchers have investigated the effect of such teacher characteristics as experience, education, salary etc on teacher turnover decisions; however these studies have not linked teachers' knowledge, pedagogy, instructional practices, and school conditions to the effective teaching and its subsequent impact on turnover decisions. Given that teacher effectiveness and turnover intentions influence student achievement, this study will have important policy implications. The proposed study will use two waves of data on measures of teacher effectiveness and teacher working conditions from 2009 to 2011, and use a series of quantitative strategies to address the following research questions: (1) using propensity score matching analysis to examine whether there is a significant gap in teacher effectiveness between high-need and low-need schools; (2) using decomposition analysis to examine the contributions of working conditions on the teacher effectiveness gap; (3) using logistic regression model to examine the influences of working conditions on teachers' turnover intentions across teacher subgroups.

Extensive research has highlighted the key role that teacher effectiveness plays in shaping student success. Little is known, however, about whether teacher effectiveness varies according to the specific subgroup of students being taught. For example, are teachers who are effective with white, middle class students also effective with black, working class students? Several qualitative studies have suggested that white teachers often have trouble teaching across racial divides, but large-scale statistical analyses have long been hindered by a lack of appropriate data. The proposed research will utilize data from the Measures of Effective Teaching (MET) project to systematically explore whether teacher effectiveness varies across student subgroups. In so doing, it will extend existing knowledge and address an area that the MET research reports highlighted as needing further study.

Since one goal of the effort to include information from classroom observations in state evaluations of teacher performance is to provide diagnostic information to the teachers who are evaluated, this study will evaluate the extent to which the set of instructional observation protocols applied in the Measures of Effective Teaching Study can be used to provide teachers with meaningful, reliable diagnostic score profiles of their instructional behaviors. Fitting cognitive diagnostic models to item-level data from the observation protocols and Student Perception Survey, I will attempt to identify and characterize substantively interesting subgroups (classes) of middle school English language arts and mathematics teachers with similar patterns of instructional behavior. I will examine the extent to which these subgroup distinctions can be used to provide reliable diagnostic profiles capturing multiple distinct aspects of instructional quality. If meaningful teacher subgroups can be identified, structural equation models will be used to relate teachers' instructional classifications to performance on the outcomes that would typically be observed in current practice: principals' teacher effectiveness ratings, student achievement test scores, and National Board of Professional Teaching Standards scores. Discussion will focus both on any modifications to the observational protocols suggested by the analyses, and on the quality of the diagnostic information generated and its likely utility for teachers.

The team of UC Berkeley researchers will examine the psychometric properties of the four classroom observation instruments and student survey instruments included in the MET Longitudinal Database. More specifically, researchers will examine how the Classroom Assessment Scoring System (CLASS) and Framework for Teaching (FFT) differ across content and grade level and between raters. CLASS and FFT scores will be correlated with Mathematical Quality of Instruction (MQI) and Protocol for Language Arts Teaching Observations (PLATO). Constructs for each the four assessments will be examined for common underpinnings across instruments. Researchers will also be looking at the factorial structure of the Tripod Assessment.

During the past decade, cluster randomized trial (CRT) has become an increasingly popular design choice for impact studies of educational interventions. While CRTs are particularly well-suited for interventions implemented at the cluster level, they typically require a much larger sample size to achieve sufficient statistical power relative to studies with individual-level random assignment. Accurate power calculations are thus essential for a well-planned CRT. Research on the design parameters for teacher outcomes, unfortunately, is virtually non-existent. With little empirical guidance, education researchers designing CRTs that examine teacher outcomes often have to make arbitrary choices of the values of key design parameters or simply apply conventional design parameter values for student outcomes to teacher outcomes. Doing so, however, may lead to either under-powered studies that fail to detect meaningful treatment effects or over-powered studies that waste precious resources. The primary purpose of the proposed project is to address this need by filling in the critical gap in the literature with a comprehensive compilation of values of ICCs for different types of teacher outcomes (knowledge, practice, and effectiveness), drawing on empirical data from a variety of sources. In addition, we will assess the effect of covariates adjustment on the variance components and the precision of impact estimates for teacher outcomes. The empirical estimates of key design parameters for teacher outcomes produced from this project will offer much needed guidance for educational researchers in the planning of well-designed and adequately powered CRTs assessing the impacts of interventions on teacher outcomes.