Quantitative

Developing the Pedagogical Skills and Science Expertise of Teachers in Underserved Rural Settings

The project will develop and research an innovative model for rural science teacher professional development via technology-mediated lesson study (TMLS). This approach supports translating professional learning into classroom practice by developing a technology-based, social support system among rural teachers.

Lead Organization(s): 
Award Number: 
2101383
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Rural science teachers are often isolated and have few opportunities for meaningful collaboration with fellow teachers, an important source of professional learning. The project will develop and research an innovative model for rural science teacher professional development via technology-mediated lesson study (TMLS). This approach supports translating professional learning into classroom practice by developing a technology-based, social support system among rural teachers. The project will host summer workshops for high school biology and chemistry teachers from four rural Utah regions to learn about 3D science teaching. (3D science teaching incorporates core ideas science disciplines, science research practices, and concepts cutting across disciplines to help students meet performance expectations by engaging with authentic science phenomena.) In the workshops, participants will collaborate with the project team and teachers of the same subject from the same region of the state to co-design 3D science lessons that align with state and national education standards. Building on relationships developed during the workshops, the regional teacher teams will engage in a novel form of professional learning: technology-mediated lesson study. (Lesson study is an instructional inquiry model where teachers work face-to-face in small collaborative groups to craft, deliver, observe, and refine teaching practice.) This project will develop capacity for science teaching for 88 rural science teachers in four regions of the state, who will reach approximately 10,000 rural Utah students each year. Many of the students are members of the sovereign Ute, Paiute, Goshute, Navajo (Diné), and Shoshone Nations. The science lesson plans participants design will be made available to all Utah teachers, and shared with a national audience through a website that shares peer-reviewed science lesson plans. Project research and resources will be further disseminated through conference presentations and publications in peer-reviewed and practitioner journals.

The project will research how TMLS supports teachers in the process of translating professional learning into practice and investigate the impact of changing teachers’ social support network to include teachers of the same subject from other rural schools. The project will study the effects of co-design activities and TMLS cycles on teachers’ changing capacity, practice, and social support system using mixed-methods research. Changes in capacity and practice will be examined qualitatively through interviews, video observations of classroom teaching, and TMLS meetings. The effects of TMLS on teachers’ social support system will be analyzed quantitatively using social network analysis to identify individuals who act as information hubs for 3D science teaching. These teachers will be interviewed to better understand their social interactions. Using design-based implementation research, the project will iteratively improve the professional learning experience collaboratively with the science teacher leaders who participate in the project.

Learning about Viral Epidemics through Engagement with Different Types of Models

The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models.

Award Number: 
2101083
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

The project will develop new curriculum and use it to research how high school students learn about viral epidemics while developing competencies for scientific modeling. The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models. This project will address the gap by studying student learning with different types of models and will use these findings to develop and study new curriculum materials that incorporate multiple models for teaching about viral epidemics in high school biology classes. COVID-19 caused devasting impacts, and marginalized groups including the Latinx community suffered disproportionately negative outcomes. The project will directly recruit Latinx students to ensure that design products are culturally responsive and account for Latinx learner needs. The project will create new pathways for engaging Latinx students in innovative, model-based curriculum about critically important issues. Project research and resources will be widely shared via publications, conference presentations, and professional development opportunities for teachers.

The project will research three aspects of student learning: a) conceptual understandings about viral epidemics, b) epistemic understandings associated with modeling, and c) model-informed reasoning about viral epidemics and potential solutions. The research will be conducted in three phases. Phase 1 will explore how students make sense of viral epidemics through different types of models. This research will be conducted with small groups of students as they work through learning activities and discourse opportunities associated with viral epidemic models. Phase 2 will research how opportunities to engage in modeling across different types of models should be supported and sequenced for learning about viral epidemics. These findings will make it possible to revise the learning performance which will be used to develop a curricular module for high school biology classes. Phase 3 will study the extent to which students learn about viral epidemics through engagement in modeling practices across different models. For this final phase, teachers will participate in professional development about viral epidemics and modeling and then implement the viral epidemic module in their biology classes. A pre- and post-test research design will be used to explore student conceptual understandings, model-informed reasoning, and epistemic understandings.

Education and Experience: Do Teacher Qualifications in Career-Focused STEM Courses Make a Difference?

Using high school statewide longitudinal data from Maryland from 2012-2022, this study will first document who has taught STEM-CTE courses over this period. After exploring the teaching landscape, the study will then explore whether qualifications (i.e., education, credentials, teaching experience) of teachers in STEM-CTE high school courses were associated with their students’ success.

Lead Organization(s): 
Award Number: 
2101163
Funding Period: 
Sun, 08/01/2021 to Mon, 07/31/2023
Full Description: 

When high school students take “STEM-CTE” (i.e., career and technical education courses in science, technology, engineering, and mathematics fields), they have much stronger outcomes across the school-to-college/career pipeline, including lower dropout rates and better attendance in high school, stronger math achievement in 12th grade, and higher odds of pursuing advanced STEM courses in high school and college. Growing teacher research shows that teachers matter for students’ success, particularly in STEM. In particular, research has established that teacher education and credentials in STEM fields, as well as years of classroom teaching experiences are key teacher factors in supporting student outcomes. However, there has been limited prior research regarding (a) who teaches STEM-CTE courses and (b) whether the benefits of these courses and pathways are driven or influenced by specific characteristics of STEM-CTE teachers. This project will aim to explore these questions.

Using high school statewide longitudinal data from Maryland from 2012-2022, this study will first document who has taught STEM-CTE courses over this period. The dataset includes approximately 5,000 unique teacher observations and approximately 500,000 unique student observations. After exploring the teaching landscape, the study will then explore whether qualifications (i.e., education, credentials, teaching experience) of teachers in STEM-CTE high school courses were associated with their students’ success. Indicators of success in the dataset include end-of-course grades, STEM-CTE concentration/industry-recognized credentialing, advanced STEM coursetaking (e.g., honors, AP, IB, dual-enrollment), STEM standardized test scores, math SAT/ACT scores, attendance/suspension rates, on-time graduation, and reduced dropout. Data analysis includes multivariate regression analyses, supplemented with tests for nonrandom sorting of teachers to students.

Fostering Computational Thinking through Neural Engineering Activities in High School Biology Classes

This project will develop and study a curriculum and app that support computational thinking (CT) in a high school biology unit. The project will engage students in rich data practices by gathering, manipulating, analyzing, simulating, and visualizing data of bioelectrical signals from neural sensors, and in so doing give the students opportunities to apply CT principles.

Lead Organization(s): 
Award Number: 
2101615
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Computational thinking (CT) is a set of processes to identify and solve problems using algorithms or steps, and can be applied not only in computer science but in other disciplines. This project will develop and study a curriculum and app that support CT in a high school biology unit. Through a month-long neural engineering unit, approximately 500 students in 18 classes will measure their own muscle and brain activity with a low-cost, portable, wearable technology. Students will then analyze the data and design a brain-computer interface to turn neural signals into real-world output (e.g., a mechanical claw controlled by brain activity). The curriculum will be supported by: (1) a web-based instructional application that will guide students through the neural engineering design process; (2) neuroscience and engineering PhD students and postdocs acting as STEM mentors; and (3) a professional development program for teachers and mentors. The goal is to increase the students’ knowledge and interest regarding neurobiology, engineering, and computational thinking. This can contribute to their long-term capacity to pursue STEM careers. By integrating CT education into high school science, this expands the accessibility of the engineering and computing experiences beyond other efforts that focus primarily on programming and computer science courses.

The project will engage students in rich data practices by gathering, manipulating, analyzing, simulating, and visualizing data of bioelectrical signals from neural sensors, and in so doing give the students opportunities to apply computational thinking principles. The project will produce curriculum materials for the neural sensors and associated data practices. It will develop an app to help students design and construct a brain-computer interface, including computational elements like coding blocks, sensor and data simulation, and connecting to external devices. The five proposed research questions of the study are: How does students’ CT change throughout their participation in the neural engineering design process? What is the cross-cultural validity of two CT scales in a sample of high school students in the US? How does the process of collecting and analyzing real-world data relate to students’ experience of he engineering design process? How do students’ attitudes toward STEM change over the course of their participation in a neural engineering design process? How does teachers’ self-efficacy for fostering CT in their students via engineering design change through their participation in professional development and in implementation of the proposed curriculum?

Empowering Teachers to See and Support Student Use of Crosscutting Concepts in the Life Sciences

The project focuses on the development of formative assessment tools that highlight assets of students’ use of crosscutting concepts (CCCs) while engaged in science and engineering practices in grades 9-12 Life Sciences.

Lead Organization(s): 
Award Number: 
2100822
Funding Period: 
Sun, 08/01/2021 to Wed, 07/31/2024
Full Description: 

The project focuses on the development of formative assessment tools that highlight assets of students’ use of crosscutting concepts (CCCs) while engaged in science and engineering practices in grades 9-12 Life Sciences. In response to the calls set forth by the Framework for K-12 Science Education and Next Generation Science Standards (NGSS), the field has most successfully researched and developed assessment tools for disciplinary core ideas and the science and engineering practices. The CCCs, which serve as the connective links across science domains, however, remain more abstractly addressed. Presently, science educators have little guidance for what student use of CCCs looks like or how to assess and nurture such use. This project, with its explicit attention to the CCCs, advances true three-dimensional scientific understanding in both research and the classroom. Leveraging formative assessment as a vehicle for student and teacher development taps into proven successful instructional strategies (e.g., sharing visions of successful learning, descriptive feedback, self-assessment), while also advancing formative assessment, itself, by strengthening and illustrating how these strategies may focus on the CCCs. Further, a strengths-based approach will center culturally related differences in students’ use of CCCs to achieve more equitable opportunities to engage in classroom sensemaking practices. This work impacts the field of science education by 1) enabling a more thorough realization of NGSS ideals, 2) strengthening teachers’ abilities to identify diverse demonstrations of CCCs, and 3) showcasing the impact of novel classroom tools to sharpen teachers’ abilities to solicit, notice, and act upon evidence of emergent student scientific thinking within their instructional practices.

This design-based implementation research project will engage teachers in the iterative development and refinement of rubrics that support three-dimensional science understanding through formative assessment. The high school biology classrooms that compose the study site are engaged in ambitious science teaching-inspired instruction. An inductive, bottom-up approach (Brookhart, 2013) will allow researchers, teachers, and students to co-construct rubrics. Analysis of classroom observations, artifact collection, interviews with teachers and students, and expert-panel ratings will produce a rubric for each CCC that integrates relevant science and engineering practices and is applicable across a range of disciplinary core ideas. These rubrics will illustrate progressions of increasingly advanced use of each of the CCCs, to guide the construction, pursuit, and assessment of learning goals. There will be two design cycles that allow for the collection of validity evidence and produce rubrics with the potential for broad application by educators. Complementary lines of qualitative and quantitative (i.e., psychometric) analysis will contribute to development and validation of the rubrics and their formative uses. Project inquiry will focus on 1) how the rubrics can represent CCCs for key disciplinary practices, 2) the extent to which teachers’ and students’ understandings of the rubrics align, and 3) how implementation of the rubrics impacts teachers’ and students’ understandings of the CCCs.

Exploratory Evidence on the Factors that Relate to Elementary School Science Learning Gains Among English Language Learners

This project will provide evidence on how school, classroom, teacher, and student factors shape elementary school science learning trajectories for English learners (ELs). The project will broaden ELs’ participation in STEM learning by investigating how individual, classroom, and school level situations such as instructional practices, learning environments, and characteristics of school personnel relate to EL elementary school science learning.

Lead Organization(s): 
Award Number: 
2100419
Funding Period: 
Sat, 05/15/2021 to Sun, 04/30/2023
Full Description: 

The nation’s schools are growing in linguistic and cultural diversity, with students identified as English learners (ELs) comprising more than ten percent of the student population. Unfortunately, existing research suggests that ELs lag behind other students in science achievement, even in the earliest grades of school. This project will provide evidence on how school, classroom, teacher, and student factors shape elementary school science learning trajectories for ELs. The project will broaden ELs’ participation in STEM learning by investigating how individual, classroom, and school level situations (inputs) such as instructional practices, learning environments, and characteristics of school personnel relate to EL elementary school science learning. Specifically, this study explores (1) a series of science inputs (time on science, content covered, availability of lab resources, and teacher training in science instruction), and (2) EL-specific inputs (classroom language use, EL instructional models, teacher certification and training, and the availability of EL support staff), in relation to ELs’ science learning outcomes from a national survey.

This study provides a comprehensive analysis of English learners’ (ELs) science learning in the early grades and the English learner instructional inputs and science instructional inputs that best predict early science outcomes (measured by both standardized science assessments and teacher-rated measures of science skills). The study uses the nationally representative Early Childhood Longitudinal Study (ECLS-K:2011) and employs a regression framework with latent class analysis to identify promising inputs that promote early science learning for ELs. Conceptually, rather than viewing the school-based inputs in isolation, the study explores how they combine to enhance students’ science learning trajectories. The study addresses the following research questions: How do science test performance trajectories vary across and within EL student groups in elementary school? How do access to school, teacher, and classroom level science and EL inputs vary across and within EL student groups in elementary school? Which school, teacher, and classroom level science and EL inputs are predictive of greater science test performance gains and teacher-rated science skills in elementary school? Are the relationships among these school, teacher, and classroom level inputs and student test performance and teacher-rated science skills different for subgroups of EL students, particularly by race/ethnicity or by immigration status? Are there particular combinations of school, teacher, and classroom level inputs that are predictive of science learning gains (test scores and teacher-rated skills) for ELs as compared to students more broadly?

Improving Professional Development in Mathematics by Understanding the Mechanisms that Translate Teacher Learning into Student Learning

This project explores the mechanisms by which teachers translate what they learn from professional development into their teaching practice. The goal of this project is to study how the knowledge and skills teachers acquire during professional development (PD) translate into more conceptually oriented mathematics teaching and, in turn, into increased student learning.

Lead Organization(s): 
Award Number: 
2100617
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

A great deal is known about the effects of mathematics teacher professional development on teachers' mathematical knowledge for teaching. While some professional development programs show meaningful changes in teacher knowledge, these changes do not always translate into changes in teacher practice. This project explores the mechanisms by which teachers translate what they learn from professional development into their teaching practice. The goal of this project is to study how the knowledge and skills teachers acquire during professional development (PD) translate into more conceptually oriented mathematics teaching and, in turn, into increased student learning. The project builds on a promising video-based PD that engages teachers in analyzing videos of classroom mathematics teaching. Previous research indicates that teachers who can analyze teaching by focusing on the nature of the mathematical learning opportunities experienced by students often teach more effectively. The researchers aim to better understand the path teachers follow as they develop this professional competency and translate it into more ambitious teaching that supports richer student learning. The lack of understanding of how a PD program can reach students is a significant barrier to improving the effectiveness of PD. To build this understanding, the researchers aim to test and refine an implementation theory that specifies the obstacles teachers face as they apply their learning to their classroom teaching and the contextual supports that help teachers surmount these obstacles. Lessons learned from understanding the factors that impact the effects of PD will help educators design PD programs that maximize the translation of teacher learning into student learning.

The project will recruit and support a cohort of teachers, grades 4–5 (n=40) and grades 6–7 (n=40) for three years to trace growth in teacher learning, changes in teaching practices, and increases in student learning. The PD will be provided throughout the year for three consecutive years. The researchers will focus on two mathematics topics with a third topic assessed to measure transfer effects. Several cycles of lesson analysis will occur each year, with small grade-alike curriculum-alike groups assisted by trained coaches to help teachers translate their growing analysis skills into planning, implementing, and reflecting on their own lessons. Additional days will be allocated each year to assist the larger groups of teachers in developing pedagogical content knowledge for analyzing teaching. The research focuses on the following questions: 1) What are the relationships between teacher learning from PD, classroom teaching, and student learning, how do hypothesized mediating variables affect these relationships, and how do these relationships change as teachers become more competent at analyzing teaching?; and 2) How do teachers describe the obstacles and supports they believe affect their learning and teaching, and how do these obstacles and supports deepen and broaden the implementation theory? Multi-level modeling will be used to address the first question, taking into account for the nested nature of the data, in order to test a model that hypothesizes direct and indirect relationships between teacher learning and teaching practice and, in turn, teaching practice and student learning. Teachers will take assessments each year, for each mathematics topic, on the analysis of teaching skills, on the use of teaching practices, and on students’ learning. Cluster analysis will be used to explore the extent to which the relationship between learning to analyze the mathematics of a lesson, teaching quality, and student achievement may be different for different teachers based on measured characteristics. Longitudinal analysis will be used to examine the theoretical relationships among variables in the hypothesized path model. Teachers’ mathematical knowledge for teaching, lesson planning, and textbook curricular material use will be examined as possible mediating variables between teacher learning and teaching practice. To address the second research question, participants will engage in annual interviews about the factors they are obstacles to doing this work and about the supports within and outside of the PD that ameliorate these obstacles. Quantitative analyses will test the relationships between the obstacles and supports with teacher learning and classroom teaching. Through qualitative analyses, the obstacles and supports to translating professional learning into practice will be further articulated. These obstacles and supports, along with the professional development model, will be disseminated to the field.

Developing and Researching K-12 Teacher Leaders Enacting Anti-bias Mathematics Education (Collaborative Research: Elliott)

The goal of this project is to study the design and development of community-centered, job-embedded professional development for classroom teachers that supports bias reduction. The project team will partner with three school districts serving racially, ethnically, linguistically, and socio-economically diverse communities, for a two-year professional development program.

Lead Organization(s): 
Award Number: 
2101667
Funding Period: 
Sun, 08/01/2021 to Thu, 07/31/2025
Full Description: 

There is increased recognition that engaging all students in learning mathematics requires an explicit focus on anti-bias mathematics teaching. Teachers, even with positive intentions, have biases, causing them to treat students differently and impacting how they distribute students’ opportunities to learn in K-12 mathematics classrooms. Research is needed to examine models of mathematics teacher professional development that explicitly addresses bias reduction. The goal of this project is to study the design and development of community-centered, job-embedded professional development for classroom teachers that supports bias reduction. The project team will partner with three school districts serving racially, ethnically, linguistically, and socio-economically diverse communities, for a two-year professional development program. The aim is to reduce bias through: analyzing and designing mathematics teaching with colleagues, students, and families to create classrooms and schools based on community-centered mathematics; engaging in anti-bias teaching routines; and building relationships with parents, caretakers, and community members. The project team will study teacher leader professional development, including the professional development model, framework, and tools, along with what teacher leaders across district contexts and grade-levels take up and use in their instructional practice.  This will potentially have wider implications for supporting more equitable mathematics teaching and leadership. Project activities, resources, and tools will be shared with the broader community of mathematics educators and researchers for use in other contexts.

The goal of this two-phase, design based research project is to iteratively design and research teacher leaders’ (TLs) participation in community-centered, job-embedded professional development and investigate their subsequent impact on classrooms, schools, and districts. The project builds on the existing Math Studio professional development model to create a Community Centered Math Studio, integrating the Anti-bias Mathematics Education Framework into the work. The project seeks to understand how the professional development model supports the development of teacher leaders' knowledge, dispositions, and practices for teaching and leading anti-bias mathematics education, and how teachers' subsequent classroom practice can cultivate students' mathematical engagement, discourse, and interests. The project will measure aspects of teacher knowledge and classroom practice by integrating existing classroom observation rubrics and STEM interest surveys to assess the impact on teacher classroom practice and student outcomes. The project will engage 12 TLs and approximately 60 additional teachers working with those TLs in two years of professional development using the Community Centered Math Studio Model to support anti-bias mathematics teaching. Data will be collected for all teachers related to their participation in the professional learning, with six teachers being followed for additional data collection and in-depth case studies. The project's outcomes will contribute to theories of how TLs build adaptive expertise for teaching and leading to reduce bias in classrooms, departments, schools, and districts. In addition, the project will contribute new and adapted research instruments on anti-bias teaching and leading. The research outcomes will add to the growing research base that describes the nature of equitable mathematics teaching in K-12 classrooms and increases access to meaningful mathematics for students, teachers, and communities.

The Impact of COVID on American Education in 2021: Continued Evidence from the Understanding America Study

This study will build upon the team's prior research from early in the pandemic. Researchers will continue to collect data from families and aims to understand parents’ perspectives on the educational impacts of COVID-19 by leveraging a nationally representative, longitudinal study, the Understanding America Study (UAS). The study will track educational experiences during the Spring and Summer of 2021 and into the 2021-22 school year.

Award Number: 
2120194
Funding Period: 
Mon, 03/01/2021 to Mon, 02/28/2022
Full Description: 

The COVID-19 epidemic has been a tremendous disruption to the education of U.S. students and their families, and evidence suggests that this disruption has been unequally felt across households by income and race/ethnicity. While other ongoing data collection efforts focus on understanding this disruption from the perspective of students or educators, less is known about the impact of COVID-19 on children’s prek-12 educational experiences as reported by their parents, especially in STEM subjects. This study will build upon the team's prior research from early in the pandemic. Researchers will continue to collect data from families and aims to understand parents’ perspectives on the educational impacts of COVID-19 by leveraging a nationally representative, longitudinal study, the Understanding America Study (UAS). The study will track educational experiences during the spring and summer of 2021 and into the 2021-22 school year. The team will analyze outcomes overall and for key demographic groups of interest as students and teachers return to in-person instruction during 2021. This RAPID project allows critically important data to continue to be collected and contribute to continued understanding of the impacts of and responses to the pandemic by American families.

Since March of 2020, the UAS has been tracking the educational impacts of COVID-19 for a nationally representative sample of approximately 1,400 households with preK-12 children. Early results focused on quantifying the digital divide and documenting the receipt of important educational services--like free meals and special education servicesafter COVID-19 began. This project will support the continued targeted administration of UAS questions to parents about students’ learning experiences and engagement, overall and in STEM subjects, data analysis, and dissemination of results to key stakeholder groups. Findings will be reported overall and across key demographic groups including ethnicity, disability, urbanicity, and socioeconomic status. This project will also produce targeted research briefs addressing pressing policy questions aimed at supporting intervention strategies in states, districts, and schools moving forward. Widespread dissemination will take place through existing networks and in collaboration with other research projects focused on understanding the COVID-19 crisis. All cross-sectional and longitudinal UAS data files will be publicly available shortly after conclusion of administration so that other researchers can explore the correlates of, and outcomes associated with, COVID-19.

Improving Evaluations of STEM Programs: An Empirical Investigation of Key Design Parameters

This study seeks to further understanding of the STEM learning environment by 1) examining the extent to which mathematics and science achievement varies across students, teachers, schools, and districts, and 2) examining the extent to which student, teacher, school, and district characteristics that are found in state administrative databases can be used to explain this variation at each level.

Lead Organization(s): 
Award Number: 
2000388
Funding Period: 
Mon, 06/15/2020 to Wed, 05/31/2023
Full Description: 

To improve science, technology, engineering, and mathematics (STEM) outcomes in K-12 classrooms, it is critical to understand the landscape of the STEM learning environment. However, the STEM learning environment is complex. Students are nested within teachers, and teachers are nested within schools (which in turn are nested within districts), which implies a multilevel structure. To date, most empirical research that uses multilevel modeling to examine the role of higher levels on variation in student outcomes does not examine the teacher level. The reason is that for many states, data linkages between students and teachers have been difficult to achieve. However, in the last five years, this situation has improved in many states, which makes this work now possible. This study seeks to further understanding of the STEM learning environment by 1) examining the extent to which mathematics and science achievement varies across students, teachers, schools, and districts and 2) examining the extent to which student, teacher, school, and district characteristics that are found in state administrative databases can be used to explain this variation at each level. This work will support advances in research and evaluation methodologies that will enable researchers to design more rigorous and comprehensive evaluations of STEM interventions and improve the accuracy of statistical power calculations. Broad dissemination of the resulting tools and techniques will provide access through freely available websites, and workshops and training opportunities to build capacity in the field for STEM researchers to design cluster randomized trials (CRTs) to answer questions beyond what works to for whom and under what conditions.

This project will contribute to 1) describing and explaining the landscape of the STEM learning environment, an environment which includes students, teachers, and schools, and 2) applying this empirical information in the design of STEM intervention studies to enable researchers to extend beyond the usual questions about if the intervention works and for which types of students or schools. By adding teacher level variables, this analysis would account for key teacher characteristics that may moderate the treatment effect. The research will also increase the efficiency in the design of CRTs of STEM interventions. Specifically, the findings from this study will improve the internal validity and cost-efficiency of evaluations of STEM interventions by increasing the accuracy of estimates for the full range of parameters needed to conduct power analyses, particularly when the teacher level is included. The high cost associated with CRTs makes it critical to plan accurate trials that do not overestimate the required sample size, and hence cost more than necessary, or underestimate the sample size and thereby reduce the potential to generate high-quality evidence of program effectiveness. Including the teacher level in intervention studies, a critical level in the delivery of any intervention, will allow for more testing of teacher characteristics that may moderate intervention effects.

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